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License

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+ +
MIT License
+
+Copyright (c) 2020 Semantic Priming Across Many Languages (SPAML)
+
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+

Power and Sample Size Simulation: Italian Age of Acquisition Norms for a Large Set of Words (ItAoA)

+

Mahmoud +M.Elsherif

+ +

2023-12-27

+ + +
ambrosini_vignette.Rmd
+
+ + + +
+

Vignette Setup: +

+
+
+

Project/Data Title: +

+

Italian Age of Acquisition Norms for a Large Set of Words (ItAoA)

+

Data provided by: Ettore Ambrosini

+
+
+

Project/Data Description: +

+

The age of acquisition (AoA) represents the age at which a word is +learned. This measure has been shown to affect performance in a wide +variety of cognitive tasks (see reviews by Juhasz, 2005; Johnston and +Barry, 2006; Brysbaert and Ellis, 2016), with faster reaction times for +words learned early in life compared to those learned later.

+

There are two main approaches to derive AoA data. First, objective +AoA measures can be obtained by analysis of children’s production +(Chalard et al., 2003; Álvarez and Cuetos, 2007; Lotto et al., 2010; +Grigoriev and Oshhepkov, 2013). Within this approach, children +(classified by age) are asked to name the picture of common objects and +activities. The AoA of a given word is computed as the mean age of the +group of children in which at least 75% of them can name the picture +correctly. Alternatively, subjective AoA can be obtained using adult +estimates (Barca et al., 2002; Ferrand et al., 2008; Moors et al., +2013). Here, adult participants are asked to provide AoA ratings on a +Likert scale (Schock et al., 2012; Alonso et al., 2015; Borelli et al., +2018) or directly in years, indicating the number corresponding to the +age they thought they had learned a given word (Stadthagen-Gonzalez and +Davis, 2006; Ferrand et al., 2008; Moors et al., 2013). Compared to the +use of a Likert scale, the latter method is easier for participants to +use and does not restrict artificially the response range, instead +providing more precise information on the AoA of words’ AoA (Ghyselinck +et al., 2000). It has been shown that the AoA estimates obtained from +the two different methods are highly correlated (Morrison et al., 1997; +Ghyselinck et al., 2000; Pind et al., 2000; Lotto et al., 2010; see also +Brysbaert, 2017; Brysbaert and Biemiller, 2017) and this correlation +still remains significant when other variables, such as familiarity, +frequency, and phonological length, are controlled (Bonin et al., +2004).

+

Only two sets of Italian norms with objective AoA (Rinaldi et al., +2004) and subjective AoA (Borelli et al., 2018) include abstract and +concrete words and different word classes (adjective, noun, and verb), +but they are limited to a relatively small number of word stimuli (519 +and 512 words, respectively). Unfortunately, the lack of overlap between +AoA (Dell’Acqua et al., 2000; Barca et al., 2002; Barbarotto et al., +2005; Della Rosa et al., 2010; Borelli et al., 2018) and +semantic-affective norms (Zannino et al., 2006; Kremer and Baroni, 2011; +Montefinese et al., 2013b, 2014; Fairfield et al., 2017) for Italian +words has prevented direct comparison of different lexical-semantic +dimensions to establish the extent to which they overlap or complement +each other in word processing. An important motivation of the present +study is to extend previous Italian norms by collecting AoA ratings for +a much larger range of Italian words for which concreteness and +semantic-affective norms are now available, thus ensuring greater +coverage of words varying along these dimensions.

+
+
+

Methods Description: +

+

A total of 507 native Italian speakers were enrolled to participate +in an online study (436 females and 81 males; mean age: 20.82 years, SD += 2.22; mean education: 15.16 years, SD = 1.11). We selected 1,957 +Italian words from our Italian adaptations of the original ANEW +(Montefinese et al., 2014; Fairfield et al., 2017) and from available +Italian semantic norms (Zannino et al., 2006; Kremer and Baroni, 2011; +Montefinese et al., 2013). The set of stimuli included 76% of nouns, 16% +of adjectives, and 8% of verbs. The word stimuli were presented in the +same verbal form as the previous Italian norms (e.g., the verbs were +presented in the infinitive form) to preserve consistency with these +data collections (Montefinese et al., 2014; Fairfield et al., 2017). +Word stimuli were distributed on 20 lists containing 97–98 words each. +To avoid primacy or recency effects, the order in which words appeared +on the list was randomized for each participant separately. All lists +were roughly matched for word length, word frequency, number of +orthographic neighbors, and mean frequency of orthographic neighbors. +For each list, an online form was created using Google modules. +Participants were asked to estimate the age (in years) at which they +thought they had learned the word, specifying that this information +should indicate the age at which, for the first time, they understood +the word when someone else used it in their presence, even when they did +not use the word themselves. These instructions and the examples +provided to the participants closely matched those used in a large +number of previous studies (Ghyselinck et al., 2000; Stadthagen-Gonzalez +and Davis, 2006; Kuperman et al., 2012; Moors et al., 2013; Łuniewska et +al., 2016). The task lasted about 40 min.

+
+
+

Data Location: +

+

Included with the vignette and Data Location: https://osf.io/rzycf/

+
+DF <- import("data/ambrosini_data.csv.zip")
+
+DF <- DF %>%
+  arrange(Ita_Word) %>% #orders the rows of the data by the target_name column
+  group_by(Ita_Word) %>% #group by the target name
+  transform(items = as.numeric(factor(Ita_Word)))%>% #transform target name into a item
+  select(items, Eng_Word, Ita_Word, everything()
+         ) #select all variables from items and target_name 
+
+DF <- DF %>% 
+  group_by(Ita_Word) %>%
+  filter (Rating != 'Unknown')
+
+head(DF)
+#> # A tibble: 6 × 5
+#> # Groups:   Ita_Word [1]
+#>   items Eng_Word Ita_Word SS_ID Rating
+#>   <dbl> <chr>    <chr>    <int> <chr> 
+#> 1     1 dazzle   abbaglio   282 16    
+#> 2     1 dazzle   abbaglio   283 10    
+#> 3     1 dazzle   abbaglio   284 12    
+#> 4     1 dazzle   abbaglio   285 10    
+#> 5     1 dazzle   abbaglio   286 8     
+#> 6     1 dazzle   abbaglio   287 9
+
+
+

Date Published: +

+

2019-02-13

+
+
+

Dataset Citation: +

+

Montefinese, M., Vinson, D., Vigliocco, G., & Ambrosini, E. +(2018, November 26). Italian age of acquisition norms for a large set of +words (ItAoA). https://doi.org/10.17605/OSF.IO/3TRG2

+
+
+

Keywords: +

+

age of acquisition, word, lexicon, Italian language, cross-linguistic +comparison, subjective rating

+
+
+

Use License: +

+

CC-By Attribution 4.0 International

+
+
+

Geographic Description - City/State/Country of Participants: +

+

Italy

+
+
+

Column Metadata: +

+
+metadata <- import("data/ambrosini_metadata.xlsx")
+
+flextable(metadata) %>% autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

Variable Name

Variable Description

Type (numeric, character, logical, etc.)

items

Item number

Numeric

Eng_Word

English translation of the item

Character

Ita_Word

Italian translation of the item

Character

SS_ID

Subject ID Number

Numeric

Rating

Age of acquisition rating

Numeric

+
+
+
+

AIPE Analysis: +

+

Note that the data are already in long format (each item has one +row), and therefore, we do not need to restructure the data.

+
+

Stopping Rule +

+

In this dataset, we have 48772 individual words to select from for +our research study. You would obviously not use all of these in one +study. Let’s say we wanted participants to rate 75 pairs of words during +our study (note: this selection is completely arbitrary).

+
+random_items <- unique(DF$items)[sample(unique(DF$items), size = 75)]
+
+DF <- DF %>% 
+  filter(items %in% random_items)
+
+# Function for simulation
+var1 <- item_power(data = DF, # name of data frame
+            dv_col = "Rating", # name of DV column as a character
+            item_col = "items", # number of items column as a character
+            nsim = 10,
+            sample_start = 20, 
+            sample_stop = 100, 
+            sample_increase = 5,
+            decile = .4)
+#> `summarise()` has grouped output by 'sample_size'. You can override using the
+#> `.groups` argument.
+

What is the usual standard error for the data that could be +considered for our stopping rule using the 40% decile?

+
+# individual SEs
+var1$SE
+#>        24        27        29        99       104       109       111       114 
+#> 0.6574699 0.4308132 0.4722993 0.4497407 0.5314132 0.5715476 0.4868949 0.4013311 
+#>       118       201       287       343       376       394       439       451 
+#> 0.4247352 0.6823489 0.2516611 0.3109126 0.6631239 0.3646002 0.5057008 0.5540156 
+#>       458       469       483       500       509       521       553       560 
+#> 0.2242023 0.4028234 0.3302524 0.5102940 0.5867424 0.6327717 0.4214262 0.6161169 
+#>       621       628       635       677       707       780       809       816 
+#> 0.2708013 0.4623130 0.4621688 0.3265986 0.2444040 0.5794250 0.6189238 0.4434712 
+#>       822       840       841       898       912       918       924       938 
+#> 0.4062840 0.3872983 0.5461380 0.3415650 0.4735680 0.3720215 0.5295281 0.6574699 
+#>       985       986      1008      1022      1034      1041      1062      1089 
+#> 0.2928026 0.2835489 0.5781580 0.6715157 0.4206344 0.4200000 0.4082483 0.3015515 
+#>      1096      1155      1187      1223      1227      1248      1256      1282 
+#> 0.2091252 0.3083288 0.2948446 0.6582806 0.3824483 0.6193545 0.2581989 0.2690725 
+#>      1341      1359      1395      1429      1435      1467      1469      1515 
+#> 0.3282276 0.5224302 0.5540156 0.5326662 0.5605949 0.3316625 0.4541143 0.4504812 
+#>      1522      1528      1538      1606      1617      1642      1650      1655 
+#> 0.4393935 0.4512206 0.3969887 0.5595236 0.3214550 0.4446722 0.5648599 0.2715388 
+#>      1660      1835      1865 
+#> 0.3390182 0.3229035 0.3555278
+
+var1$cutoff
+#>       40% 
+#> 0.4048997
+

Using our 40% decile as a guide, we find that 0.405 is our target +standard error for an accurately measured item.

+
+
+

Minimum Sample Size +

+

To estimate the minimum sample size, we should figure out what number +of participants it would take to achieve 80%, 85%, 90%, and 95% of the +SEs for items below our critical score of 0.405?

+
+cutoff <- calculate_cutoff(population = DF, 
+                           grouping_items = "items",
+                           score = "Rating",
+                           minimum = as.numeric(min(DF$Rating)),
+                           maximum = as.numeric(max(DF$Rating)))
+# showing how this is the same as the person calculated version versus semanticprimeR's function
+cutoff$cutoff
+#>       40% 
+#> 0.4048997
+
+final_table <- calculate_correction(
+  proportion_summary = var1$final_sample,
+  pilot_sample_size = DF %>% group_by(items) %>% summarize(n = n()) %>% 
+    pull(n) %>% mean() %>% round(),
+  proportion_variability = cutoff$prop_var
+  )
+
+flextable(final_table) %>% 
+  autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

percent_below

sample_size

corrected_sample_size

80.40000

45

43.27286

88.80000

55

54.58167

91.86667

60

59.97526

97.20000

70

70.19716

+
+

Our minimum sample size is small at 80% (n = 43 as the +minimum). We could consider using 90% (n = 60) or 95% +(n = 70).

+
+
+

Maximum Sample Size +

+

While there are many considerations for maximum sample size (time, +effort, resources), if we consider a higher value just for estimation +sake, we could use n = at 98%.

+
+
+

Final Sample Size +

+

In any estimate of sample size, you should also consider the +potential for missing data and/or unusable data due to any other +exclusion criteria in your study (i.e., attention checks, speeding, +getting the answer right, etc.). In this study, these values can be +influenced by the other variables that we used to select the stimuli in +the study.

+
+
+
+
+ + + + +
+ + + + + + + diff --git a/docs/articles/ambrosini_vignette_files/tabwid-1.1.3/tabwid.css b/docs/articles/ambrosini_vignette_files/tabwid-1.1.3/tabwid.css new file mode 100644 index 0000000..5e31a86 --- /dev/null +++ b/docs/articles/ambrosini_vignette_files/tabwid-1.1.3/tabwid.css @@ -0,0 +1,42 @@ +.tabwid { + font-size: initial; + padding-bottom: 1em; +} + +.tabwid table{ + border-spacing:0px !important; + border-collapse:collapse; + line-height:1; + margin-left:auto; + margin-right:auto; + border-width: 0; + border-color: transparent; + caption-side: top; +} +.tabwid-caption-bottom table{ + caption-side: bottom; +} +.tabwid_left table{ + margin-left:0; +} +.tabwid_right table{ + margin-right:0; +} +.tabwid td, .tabwid th { + padding: 0; +} +.tabwid a { + text-decoration: none; +} +.tabwid thead { + background-color: transparent; +} +.tabwid tfoot { + background-color: transparent; +} +.tabwid table tr { +background-color: transparent; +} +.katex-display { + margin: 0 0 !important; +} diff --git a/docs/articles/ambrosini_vignette_files/tabwid-1.1.3/tabwid.js b/docs/articles/ambrosini_vignette_files/tabwid-1.1.3/tabwid.js new file mode 100644 index 0000000..47070f7 --- /dev/null +++ b/docs/articles/ambrosini_vignette_files/tabwid-1.1.3/tabwid.js @@ -0,0 +1,20 @@ +document.addEventListener("DOMContentLoaded", function(event) { + var els = document.querySelectorAll(".tabwid"); + var tabwid_link = document.querySelector('link[href*="tabwid.css"]') + if (tabwid_link === null) { + const tabwid_styles = document.evaluate("//style[contains(., 'tabwid')]", document, null, XPathResult.ANY_TYPE, null ); + tabwid_link = tabwid_styles.iterateNext(); + } + + Array.prototype.forEach.call(els, function(template) { + const dest = document.createElement("div"); + template.parentNode.insertBefore(dest, template.nextSibling) + dest.setAttribute("class", "flextable-shadow-host"); + const fantome = dest.attachShadow({mode: 'open'}); + fantome.appendChild(template); + if (tabwid_link !== null) { + fantome.appendChild(tabwid_link.cloneNode(true)); + } + }); +}); + diff --git a/docs/articles/barzykowski_vignette.html b/docs/articles/barzykowski_vignette.html new file mode 100644 index 0000000..8cf312d --- /dev/null +++ b/docs/articles/barzykowski_vignette.html @@ -0,0 +1,523 @@ + + + + + + + + +Power and Sample Size Simulation: Cue Word Valence Data Example • semanticprimeR + + + + + + + + + + Skip to contents + + +
+ + + + +
+
+

Power and Sample Size Simulation: Cue Word Valence Data Example

+

Erin M. +Buchanan

+ +

2023-12-27

+ + +
barzykowski_vignette.Rmd
+
+ + + +
+

Vignette Setup: +

+
+
+

Project/Data Title: +

+

Cue Word Triggered Memory’s Phenomenological

+

Data provided by: Krystian Barzykowski

+
+
+

Project/Data Description: +

+

Participants participated in a voluntary memory task, where they were +provided with a word cue in response to which they were about to recall +an autobiographical memory. The item set consists of 30 word cues that +were rated/classified by 142 separate participants.

+
+
+

Methods Description: +

+

They briefly described the content of their thoughts recalled in +response to the word-cue and rated it on a 7-point scale: (a) to what +extent the content was accompanied by unexpected physiological +sensations (henceforth, called physiological sensation), (b) to what +extent they had deliberately tried to bring the thought to mind +(henceforth, called effort), (c) clarity (i.e. how clearly and well an +individual remembered a given memory/mental content), (d) how detailed +the content was, (e) how specific and concrete the content was, (f) +intensity of emotions experienced in response to the content, (g) how +surprising the content was, (h) how personal it was, and (i) the +relevance to current life situation (not included).

+
+
+

Data Location: +

+

Data included within this vignette.

+
+DF <- import("data/barzykowski_data.xlsx") %>% 
+  bind_rows(import("data/barzykowski_data.xlsx", sheet = 2)) %>% 
+  bind_rows(import("data/barzykowski_data.xlsx", sheet = 3)) %>% 
+  bind_rows(import("data/barzykowski_data.xlsx", sheet = 4)) %>% 
+  bind_rows(import("data/barzykowski_data.xlsx", sheet = 5)) %>% 
+  bind_rows(import("data/barzykowski_data.xlsx", sheet = 6)) %>% 
+  bind_rows(import("data/barzykowski_data.xlsx", sheet = 7)) %>% 
+  bind_rows(import("data/barzykowski_data.xlsx", sheet = 8)) %>% 
+  bind_rows(import("data/barzykowski_data.xlsx", sheet = 9)) %>% 
+  bind_rows(import("data/barzykowski_data.xlsx", sheet = 10)) %>% 
+  bind_rows(import("data/barzykowski_data.xlsx", sheet = 11)) %>% 
+  bind_rows(import("data/barzykowski_data.xlsx", sheet = 12)) %>% 
+  bind_rows(import("data/barzykowski_data.xlsx", sheet = 13)) %>% 
+  bind_rows(import("data/barzykowski_data.xlsx", sheet = 14)) %>% 
+  bind_rows(import("data/barzykowski_data.xlsx", sheet = 15)) %>% 
+  bind_rows(import("data/barzykowski_data.xlsx", sheet = 16)) %>% 
+  bind_rows(import("data/barzykowski_data.xlsx", sheet = 17)) %>% 
+  bind_rows(import("data/barzykowski_data.xlsx", sheet = 18)) %>% 
+  bind_rows(import("data/barzykowski_data.xlsx", sheet = 19)) %>% 
+  bind_rows(import("data/barzykowski_data.xlsx", sheet = 20)) %>% 
+  bind_rows(import("data/barzykowski_data.xlsx", sheet = 21)) %>% 
+  bind_rows(import("data/barzykowski_data.xlsx", sheet = 22)) %>% 
+  bind_rows(import("data/barzykowski_data.xlsx", sheet = 23)) %>% 
+  bind_rows(import("data/barzykowski_data.xlsx", sheet = 24)) %>% 
+  bind_rows(import("data/barzykowski_data.xlsx", sheet = 25)) %>% 
+  bind_rows(import("data/barzykowski_data.xlsx", sheet = 26)) %>% 
+  bind_rows(import("data/barzykowski_data.xlsx", sheet = 27)) %>% 
+  bind_rows(import("data/barzykowski_data.xlsx", sheet = 28)) %>% 
+  bind_rows(import("data/barzykowski_data.xlsx", sheet = 29)) %>% 
+  bind_rows(import("data/barzykowski_data.xlsx", sheet = 30)) 
+
+str(DF)
+#> 'data.frame':    918 obs. of  11 variables:
+#>  $ Participant's ID      : num  12 13 14 15 16 17 18 19 20 21 ...
+#>  $ Cue no                : num  1 1 1 1 1 1 1 1 1 1 ...
+#>  $ Physiological reaction: num  1 1 1 1 1 1 2 2 4 2 ...
+#>  $ Effort                : num  4 4 7 4 1 2 4 4 2 3 ...
+#>  $ Vividness             : num  5 6 1 4 2 7 3 6 3 3 ...
+#>  $ Clarity               : num  2 4 1 4 6 7 4 5 4 4 ...
+#>  $ Detailidness          : num  5 5 1 4 4 7 2 3 3 2 ...
+#>  $ Concretness           : num  2 4 3 5 4 7 5 5 3 2 ...
+#>  $ Emotional Intensity   : num  3 1 2 2 1 6 2 1 2 1 ...
+#>  $ How surprising        : num  5 2 1 1 4 4 3 2 5 1 ...
+#>  $ Personal nature       : num  2 1 4 3 1 5 1 1 2 1 ...
+
+
+

Date Published: +

+

No official publication, see citation below.

+
+
+

Dataset Citation: +

+

The cues were used in study published here: Barzykowski, K., +Niedźwieńska, A., & Mazzoni, G. (2019). How intention to retrieve a +memory and expectation that it will happen influence retrieval of +autobiographical memories. Consciousness and Cognition, 72, 31-48. DOI: +https://doi.org/10.1016/j.concog.2019.03.011

+
+
+

Keywords: +

+

cue-word, valence, memory retrieval

+
+
+

Use License: +

+

Open access with reference to original paper +(Attribution-NonCommercial-ShareAlike CC BY-NC-SA)

+
+
+

Geographic Description - City/State/Country of Participants: +

+

Poland, Kraków

+
+
+

Column Metadata: +

+
+metadata <- import("data/barzykowski_metadata.xlsx")
+
+flextable(metadata) %>% autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

Variable Name

Variable Description

Type (numeric, character, logical, etc.)

Participant's ID

Participants’ identification number

Numeric

Cue no

Number of the specific cue they saw

Numeric

Physiological reaction

To what extent the content was accompanied by unexpected physiological sensations (henceforth, called physiological sensation)

Numeric (1 to 7 scale)

Effort

To what extent they had deliberately tried to bring the thought to mind (henceforth, called effort)

Numeric (1 to 7 scale)

Vividness

How vivid the thought was

Numeric (1 to 7 scale)

Clarity

Clarity (i.e. how clearly and well an individual remembered a given memory/mental content)

Numeric (1 to 7 scale)

Detailidness

How detailed the content was

Numeric (1 to 7 scale)

Concretness

How specific and concrete the content was

Numeric (1 to 7 scale)

Emotional Intensity

Intensity of emotions experienced in response to the content

Numeric (1 to 7 scale)

How surprising

How surprising the +
content was

Numeric (1 to 7 scale)

Personal nature

How personal it was

Numeric (1 to 7 scale)

+
+
+
+

AIPE Analysis: +

+

Note that the data is already in long format (each item has one row), +and therefore, we do not need to restructure the data.

+
+

Stopping Rule +

+

In this example, we have multiple variables to choose from for our +analysis. We could include several to find the sample size rules for +further study. In this example, we’ll use the variables with the least +and most variability and take the average of the 40% decile as suggested +in our manuscript. This choice is somewhat arbitrary - in a real study, +you could choose to use only the variables you were interested in and +pick the most conservative values or simply average together estimates +from all variables.

+
+apply(DF[ , -c(1,2)], 2, sd)
+#> Physiological reaction                 Effort              Vividness 
+#>               1.691892               1.577815               1.651065 
+#>                Clarity           Detailidness            Concretness 
+#>               1.651066               1.696818               1.646454 
+#>    Emotional Intensity         How surprising        Personal nature 
+#>               1.753200               1.500973               1.889276
+

These are Likert type items. The variance within them appears roughly +equal. The lowest variance appears to be How surprising, and the maximum +appears to be Personal nature.

+

Run the function proposed in the manuscript:

+
+# set seed
+set.seed(8548)
+# Function for simulation
+var1 <- item_power(data = DF, # name of data frame
+            dv_col = "How surprising", # name of DV column as a character
+            item_col = "Cue no", # number of items column as a character
+            nsim = 10,
+            sample_start = 20, 
+            sample_stop = 100, 
+            sample_increase = 5,
+            decile = .4)
+#> `summarise()` has grouped output by 'sample_size'. You can override using the
+#> `.groups` argument.
+
+var2 <- item_power(DF, # name of data frame
+            "Personal nature", # name of DV column as a character
+            item_col = "Cue no", # number of items column as a character
+            nsim = 10, 
+            sample_start = 20, 
+            sample_stop = 100, 
+            sample_increase = 5,
+            decile = .4)
+#> `summarise()` has grouped output by 'sample_size'. You can override using the
+#> `.groups` argument.
+

What the usual standard error for the data that could be considered +for our stopping rule?

+
+# individual SEs for how surprising 
+var1$SE
+#>         1         2         3         4         5         6         7         8 
+#> 0.2654025 0.1843656 0.2395449 0.2463527 0.2478174 0.2702634 0.2385878 0.1781742 
+#>         9        10        11        12        13        14        15        16 
+#> 0.2643095 0.2784668 0.2803546 0.2595053 0.2568655 0.2387265 0.3268158 0.2692327 
+#>        17        18        19        20        21        22        23        24 
+#> 0.3114397 0.3007016 0.2886410 0.2815891 0.2677375 0.1979609 0.2478808 0.2986490 
+#>        25        26        27        28        29        30 
+#> 0.3589899 0.2982066 0.2921602 0.3035231 0.2643255 0.3249033
+# var 1 cut off
+var1$cutoff
+#>       40% 
+#> 0.2643191
+
+# individual SEs for personal nature
+var2$SE
+#>         1         2         3         4         5         6         7         8 
+#> 0.2870153 0.2839809 0.2432371 0.3319512 0.3600411 0.4064413 0.3389511 0.3191424 
+#>         9        10        11        12        13        14        15        16 
+#> 0.2502489 0.3696715 0.3708976 0.2800560 0.2674643 0.2832563 0.4580862 0.2836613 
+#>        17        18        19        20        21        22        23        24 
+#> 0.3588157 0.3122039 0.3498098 0.3617125 0.3435939 0.3702658 0.3156137 0.2744988 
+#>        25        26        27        28        29        30 
+#> 0.4125648 0.3298670 0.3760496 0.3258969 0.2797701 0.3615385
+# var 2 cut off
+var2$cutoff
+#>       40% 
+#> 0.3177309
+
+# overall cutoff
+cutoff <- mean(var1$cutoff, var2$cutoff)
+cutoff
+#> [1] 0.2643191
+

The average SE cutoff across both variables is 0.264.

+
+
+

Minimum Sample Size +

+

How large does the sample have to be for 80% to 95% of the items to +be below our stopping SE rule?

+
+cutoff_personal <- calculate_cutoff(population = DF, 
+                           grouping_items = "Cue no",
+                           score = "Personal nature",
+                           minimum = as.numeric(min(DF$`Personal nature`)),
+                           maximum = as.numeric(max(DF$`Personal nature`)))
+# showing how this is the same as the person calculated version versus semanticprimeR's function
+cutoff_personal$cutoff
+#>       40% 
+#> 0.3177309
+
+final_table_personal <- calculate_correction(
+  proportion_summary = var1$final_sample,
+  pilot_sample_size = length(unique(DF$`Participant's ID`)),
+  proportion_variability = cutoff_personal$prop_var
+  )
+
+flextable(final_table_personal) %>% 
+  autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

percent_below

sample_size

corrected_sample_size

83.33333

40

31.06408

91.66667

45

37.55466

91.66667

45

37.55466

97.66667

50

44.05820

+
+
+cutoff_surprising <- calculate_cutoff(population = DF, 
+                           grouping_items = "Cue no",
+                           score = "How surprising",
+                           minimum = as.numeric(min(DF$`How surprising`)),
+                           maximum = as.numeric(max(DF$`How surprising`)))
+# showing how this is the same as the person calculated version versus semanticprimeR's function
+cutoff_surprising$cutoff
+#>       40% 
+#> 0.2643191
+
+final_table_surprising <- calculate_correction(
+  proportion_summary = var2$final_sample,
+  pilot_sample_size = length(unique(DF$`Participant's ID`)),
+  proportion_variability = cutoff_surprising$prop_var
+  )
+
+flextable(final_table_surprising) %>% 
+  autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

percent_below

sample_size

corrected_sample_size

89

45

37.88715

89

45

37.88715

97

50

44.40287

97

50

44.40287

+
+

In this scenario, we could go with the point wherein they both meet +the 80% criterion, which is \(n_{personal}\) = 31 to \(n_{surprising}\) = 38. In these scenarios, +it is probably better to estimate a larger sample.

+
+
+

Maximum Sample Size +

+

If you decide to use 95% power as your criterion, you would see that +items need somewhere between \(n_{personal}\) = 44 to \(n_{surprising}\) = 44 participants for both +variables. In this case, you could choose to make the larger value for +participants your maximum sample size to ensure both variables reach the +criterion.

+
+
+

Final Sample Size +

+

You should also consider any potential for missing data and/or +unusable data given the requirements for your study. Given that +participants are likely to see all items in this study, we could use the +minimum, stopping rule, and maximum defined above. However, one should +consider that not all participants will be able to respond to all items +within a memory.

+
+
+
+
+ + + + +
+ + + + + + + diff --git a/docs/articles/barzykowski_vignette_files/tabwid-1.1.3/tabwid.css b/docs/articles/barzykowski_vignette_files/tabwid-1.1.3/tabwid.css new file mode 100644 index 0000000..5e31a86 --- /dev/null +++ b/docs/articles/barzykowski_vignette_files/tabwid-1.1.3/tabwid.css @@ -0,0 +1,42 @@ +.tabwid { + font-size: initial; + padding-bottom: 1em; +} + +.tabwid table{ + border-spacing:0px !important; + border-collapse:collapse; + line-height:1; + margin-left:auto; + margin-right:auto; + border-width: 0; + border-color: transparent; + caption-side: top; +} +.tabwid-caption-bottom table{ + caption-side: bottom; +} +.tabwid_left table{ + margin-left:0; +} +.tabwid_right table{ + margin-right:0; +} +.tabwid td, .tabwid th { + padding: 0; +} +.tabwid a { + text-decoration: none; +} +.tabwid thead { + background-color: transparent; +} +.tabwid tfoot { + background-color: transparent; +} +.tabwid table tr { +background-color: transparent; +} +.katex-display { + margin: 0 0 !important; +} diff --git a/docs/articles/barzykowski_vignette_files/tabwid-1.1.3/tabwid.js b/docs/articles/barzykowski_vignette_files/tabwid-1.1.3/tabwid.js new file mode 100644 index 0000000..47070f7 --- /dev/null +++ b/docs/articles/barzykowski_vignette_files/tabwid-1.1.3/tabwid.js @@ -0,0 +1,20 @@ +document.addEventListener("DOMContentLoaded", function(event) { + var els = document.querySelectorAll(".tabwid"); + var tabwid_link = document.querySelector('link[href*="tabwid.css"]') + if (tabwid_link === null) { + const tabwid_styles = document.evaluate("//style[contains(., 'tabwid')]", document, null, XPathResult.ANY_TYPE, null ); + tabwid_link = tabwid_styles.iterateNext(); + } + + Array.prototype.forEach.call(els, function(template) { + const dest = document.createElement("div"); + template.parentNode.insertBefore(dest, template.nextSibling) + dest.setAttribute("class", "flextable-shadow-host"); + const fantome = dest.attachShadow({mode: 'open'}); + fantome.appendChild(template); + if (tabwid_link !== null) { + fantome.appendChild(tabwid_link.cloneNode(true)); + } + }); +}); + diff --git a/docs/articles/batres_vignette.html b/docs/articles/batres_vignette.html new file mode 100644 index 0000000..f0edd10 --- /dev/null +++ b/docs/articles/batres_vignette.html @@ -0,0 +1,662 @@ + + + + + + + + +Power and Sample Size Simulation: Attractiveness Ratings Example • semanticprimeR + + + + + + + + + + Skip to contents + + +
+ + + + +
+
+

Power and Sample Size Simulation: Attractiveness Ratings Example

+

Erin M. +Buchanan

+ +

2023-12-27

+ + +
batres_vignette.Rmd
+
+ + + +
+

Vignette Setup: +

+
+knitr::opts_chunk$set(echo = TRUE)
+
+# Set a random seed
+set.seed(5989320)
+
+# Libraries necessary for this vignette
+library(rio)
+library(flextable)
+library(dplyr)
+#> 
+#> Attaching package: 'dplyr'
+#> The following objects are masked from 'package:stats':
+#> 
+#>     filter, lag
+#> The following objects are masked from 'package:base':
+#> 
+#>     intersect, setdiff, setequal, union
+library(tidyr)
+library(psych)
+library(semanticprimeR)
+
+# Function for simulation
+item_power <- function(data, # name of data frame
+                       dv_col, # name of DV column as a character
+                       item_col, # number of items column as a character
+                       nsim = 10, # small for cran 
+                       sample_start = 20, 
+                       sample_stop = 200, 
+                       sample_increase = 5,
+                       decile = .5){
+  
+  DF <- cbind.data.frame(
+    "dv" = data[ , dv_col],
+    "items" = data[ , item_col]
+  )
+  
+  # just in case
+  colnames(DF) <- c("dv", "items")
+  
+  # figure out the "sufficiently narrow" ci value
+  SE <- tapply(DF$dv, DF$items, function (x) { sd(x)/sqrt(length(x)) })
+  cutoff <- quantile(SE, probs = decile)
+  
+  # sequence of sample sizes to try
+  samplesize_values <- seq(sample_start, sample_stop, sample_increase)
+
+  # create a blank table for us to save the values in 
+  sim_table <- matrix(NA, 
+                      nrow = length(samplesize_values)*nsim, 
+                      ncol = length(unique(DF$items)))
+
+  # make it a data frame
+  sim_table <- as.data.frame(sim_table)
+
+  # add a place for sample size values 
+  sim_table$sample_size <- NA
+
+  iterate <- 1
+  
+  for (p in 1:nsim){
+    # loop over sample sizes
+    for (i in 1:length(samplesize_values)){
+        
+      # temp that samples and summarizes
+      temp <- DF %>% 
+        group_by(items) %>% 
+        sample_n(samplesize_values[i], replace = T) %>% 
+        summarize(se = sd(dv)/sqrt(length(dv)))
+      
+      # dv on items
+      colnames(sim_table)[1:length(unique(DF$items))] <- temp$items
+      sim_table[iterate, 1:length(unique(DF$items))] <- temp$se
+      sim_table[iterate, "sample_size"] <- samplesize_values[i]
+      sim_table[iterate, "nsim"] <- p
+      
+      iterate <- iterate + 1
+    }
+  }
+
+  # figure out cut off
+  final_sample <- sim_table %>% 
+    pivot_longer(cols = -c(sample_size, nsim)) %>% 
+    dplyr::rename(item = name, se = value) %>% 
+    group_by(sample_size, nsim) %>% 
+    summarize(percent_below = sum(se <= cutoff)/length(unique(DF$items))) %>% 
+    ungroup() %>% 
+    # then summarize all down averaging percents
+    dplyr::group_by(sample_size) %>% 
+    summarize(percent_below = mean(percent_below)) %>% 
+    dplyr::arrange(percent_below) %>% 
+    ungroup()
+  
+  return(list(
+    SE = SE, 
+    cutoff = cutoff, 
+    DF = DF, 
+    sim_table = sim_table, 
+    final_sample = final_sample
+  ))
+
+}
+
+
+

Project/Data Title: +

+

Attractiveness Ratings

+

Data provided by: Carlota Batres

+
+
+

Project/Data Description: +

+

This dataset contains 200 participants rating 20 faces on +attractiveness. Ethical approval was received from the Franklin and +Marshall Institutional Review Board and each participant provided +informed consent. All participants were located in the United States. +Participants were instructed that they would be viewing several faces +which were photographed facing forward, under constant camera and +lighting conditions, with neutral expressions, and closed mouths. Each +participant would have to rate the attractiveness of the presented +faces. More specifically, participants were asked “How attractive is +this face?”, where 1 = “Not at all attractive” and 7 = “Very +attractive”. Participants rated each face individually, in random order, +and with no time limit. Upon completion, participants were paid for +participation in the study.

+
+
+

Methods Description: +

+

The data was collected online using Amazon’s Mechanical Turk +platform.

+
+
+

Data Location: +

+

Included with the vignette.

+
+DF <- import("data/batres_data.sav")
+
+str(DF)
+#> 'data.frame':    200 obs. of  21 variables:
+#>  $ Participant_Number: num  1 2 3 4 5 6 7 8 9 10 ...
+#>   ..- attr(*, "label")= chr "Unique number assigned to each participant"
+#>   ..- attr(*, "format.spss")= chr "F3.0"
+#>   ..- attr(*, "display_width")= int 12
+#>  $ Face_1            : num  1 2 5 2 3 1 2 2 1 2 ...
+#>   ..- attr(*, "label")= chr "Attractiveness rating for face #1"
+#>   ..- attr(*, "format.spss")= chr "F1.0"
+#>   ..- attr(*, "display_width")= int 12
+#>  $ Face_2            : num  1 6 5 2 3 1 3 2 2 2 ...
+#>   ..- attr(*, "label")= chr "Attractiveness rating for face #2"
+#>   ..- attr(*, "format.spss")= chr "F1.0"
+#>   ..- attr(*, "display_width")= int 12
+#>  $ Face_3            : num  3 6 7 7 4 3 5 4 4 4 ...
+#>   ..- attr(*, "label")= chr "Attractiveness rating for face #3"
+#>   ..- attr(*, "format.spss")= chr "F1.0"
+#>   ..- attr(*, "display_width")= int 12
+#>  $ Face_4            : num  3 7 5 3 4 3 3 3 4 3 ...
+#>   ..- attr(*, "label")= chr "Attractiveness rating for face #4"
+#>   ..- attr(*, "format.spss")= chr "F1.0"
+#>   ..- attr(*, "display_width")= int 12
+#>  $ Face_5            : num  5 7 7 5 5 6 3 3 3 3 ...
+#>   ..- attr(*, "label")= chr "Attractiveness rating for face #5"
+#>   ..- attr(*, "format.spss")= chr "F1.0"
+#>   ..- attr(*, "display_width")= int 12
+#>  $ Face_6            : num  5 5 4 5 6 5 4 4 5 3 ...
+#>   ..- attr(*, "label")= chr "Attractiveness rating for face #6"
+#>   ..- attr(*, "format.spss")= chr "F1.0"
+#>   ..- attr(*, "display_width")= int 12
+#>  $ Face_7            : num  5 7 7 7 4 5 4 4 5 4 ...
+#>   ..- attr(*, "label")= chr "Attractiveness rating for face #7"
+#>   ..- attr(*, "format.spss")= chr "F1.0"
+#>   ..- attr(*, "display_width")= int 12
+#>  $ Face_8            : num  4 1 5 3 4 4 4 4 2 4 ...
+#>   ..- attr(*, "label")= chr "Attractiveness rating for face #8"
+#>   ..- attr(*, "format.spss")= chr "F1.0"
+#>   ..- attr(*, "display_width")= int 12
+#>  $ Face_9            : num  3 5 4 4 3 1 2 2 2 2 ...
+#>   ..- attr(*, "label")= chr "Attractiveness rating for face #9"
+#>   ..- attr(*, "format.spss")= chr "F1.0"
+#>   ..- attr(*, "display_width")= int 12
+#>  $ Face_10           : num  4 4 7 2 3 3 3 3 5 4 ...
+#>   ..- attr(*, "label")= chr "Attractiveness rating for face #10"
+#>   ..- attr(*, "format.spss")= chr "F1.0"
+#>   ..- attr(*, "display_width")= int 12
+#>  $ Face_11           : num  2 3 5 4 3 2 3 3 4 2 ...
+#>   ..- attr(*, "label")= chr "Attractiveness rating for face #11"
+#>   ..- attr(*, "format.spss")= chr "F1.0"
+#>   ..- attr(*, "display_width")= int 12
+#>  $ Face_12           : num  4 7 5 4 4 4 3 3 6 1 ...
+#>   ..- attr(*, "label")= chr "Attractiveness rating for face #12"
+#>   ..- attr(*, "format.spss")= chr "F1.0"
+#>   ..- attr(*, "display_width")= int 12
+#>  $ Face_13           : num  3 3 4 5 4 3 3 3 3 2 ...
+#>   ..- attr(*, "label")= chr "Attractiveness rating for face #13"
+#>   ..- attr(*, "format.spss")= chr "F1.0"
+#>   ..- attr(*, "display_width")= int 12
+#>  $ Face_14           : num  5 7 5 5 3 5 5 5 4 2 ...
+#>   ..- attr(*, "label")= chr "Attractiveness rating for face #14"
+#>   ..- attr(*, "format.spss")= chr "F1.0"
+#>   ..- attr(*, "display_width")= int 12
+#>  $ Face_15           : num  3 7 6 3 4 6 3 3 4 4 ...
+#>   ..- attr(*, "label")= chr "Attractiveness rating for face #15"
+#>   ..- attr(*, "format.spss")= chr "F1.0"
+#>   ..- attr(*, "display_width")= int 12
+#>  $ Face_16           : num  4 7 5 5 5 4 4 3 5 3 ...
+#>   ..- attr(*, "label")= chr "Attractiveness rating for face #16"
+#>   ..- attr(*, "format.spss")= chr "F1.0"
+#>   ..- attr(*, "display_width")= int 12
+#>  $ Face_17           : num  4 4 5 3 5 4 3 2 4 2 ...
+#>   ..- attr(*, "label")= chr "Attractiveness rating for face #17"
+#>   ..- attr(*, "format.spss")= chr "F1.0"
+#>   ..- attr(*, "display_width")= int 12
+#>  $ Face_18           : num  3 5 4 6 4 5 4 5 4 2 ...
+#>   ..- attr(*, "label")= chr "Attractiveness rating for face #18"
+#>   ..- attr(*, "format.spss")= chr "F1.0"
+#>   ..- attr(*, "display_width")= int 12
+#>  $ Face_19           : num  3 4 5 6 4 4 4 3 3 4 ...
+#>   ..- attr(*, "label")= chr "Attractiveness rating for face #19"
+#>   ..- attr(*, "format.spss")= chr "F1.0"
+#>   ..- attr(*, "display_width")= int 12
+#>  $ Face_20           : num  4 6 6 3 6 4 3 3 4 3 ...
+#>   ..- attr(*, "label")= chr "Attractiveness rating for face #20"
+#>   ..- attr(*, "format.spss")= chr "F1.0"
+#>   ..- attr(*, "display_width")= int 12
+
+
+

Date Published: +

+

No official publication date.

+
+
+

Dataset Citation: +

+

Batres, C. (2022). Attractiveness Ratings. [Data set].

+
+
+

Keywords: +

+

faces, ratings

+
+
+

Use License: +

+

Attribution-NonCommercial-ShareAlike CC BY-NC-SA

+
+
+

Geographic Description - City/State/Country of Participants: +

+

United States

+
+
+

Column Metadata: +

+
+metadata <- import("data/batres_metadata.xlsx")
+
+flextable(metadata) %>% autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

Variable Name

Variable Description

Type (numeric, character, logical, etc.)

Participant_Number

Unique number assigned to each participant

Numeric

Face_1

Attractiveness rating for face #1

Numeric

Face_2

Attractiveness rating for face #2

Numeric

Face_3

Attractiveness rating for face #3

Numeric

Face_4

Attractiveness rating for face #4

Numeric

Face_5

Attractiveness rating for face #5

Numeric

Face_6

Attractiveness rating for face #6

Numeric

Face_7

Attractiveness rating for face #7

Numeric

Face_8

Attractiveness rating for face #8

Numeric

Face_9

Attractiveness rating for face #9

Numeric

Face_10

Attractiveness rating for face #10

Numeric

Face_11

Attractiveness rating for face #11

Numeric

Face_12

Attractiveness rating for face #12

Numeric

Face_13

Attractiveness rating for face #13

Numeric

Face_14

Attractiveness rating for face #14

Numeric

Face_15

Attractiveness rating for face #15

Numeric

Face_16

Attractiveness rating for face #16

Numeric

Face_17

Attractiveness rating for face #17

Numeric

Face_18

Attractiveness rating for face #18

Numeric

Face_19

Attractiveness rating for face #19

Numeric

Face_20

Attractiveness rating for face #20

Numeric

+
+
+
+

AIPE Analysis: +

+

The data should be in long format with each rating on one row of +data.

+
+# Reformat the data
+DF_long <- pivot_longer(DF, cols = -c(Participant_Number)) %>% 
+  dplyr::rename(item = name, score = value)
+
+flextable(head(DF_long)) %>% autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

Participant_Number

item

score

1

Face_1

1

1

Face_2

1

1

Face_3

3

1

Face_4

3

1

Face_5

5

1

Face_6

5

+
+
+

Stopping Rule +

+
+# Function for simulation
+var1 <- item_power(data = DF_long, # name of data frame
+            dv_col = "score", # name of DV column as a character
+            item_col = "item", # number of items column as a character
+            nsim = 10, 
+            sample_start = 20, 
+            sample_stop = 300, 
+            sample_increase = 5,
+            decile = .4)
+#> `summarise()` has grouped output by 'sample_size'. You can override using the
+#> `.groups` argument.
+

What the usual standard error for the data that could be considered +for our stopping rule using the 40%% decile?

+
+# individual SEs
+var1$SE
+#>     Face_1    Face_10    Face_11    Face_12    Face_13    Face_14    Face_15 
+#> 0.09117808 0.09064190 0.10007472 0.09739767 0.08562437 0.08767230 0.09331351 
+#>    Face_16    Face_17    Face_18    Face_19     Face_2    Face_20     Face_3 
+#> 0.10262632 0.09082536 0.09530433 0.09123386 0.08818665 0.09799754 0.08644573 
+#>     Face_4     Face_5     Face_6     Face_7     Face_8     Face_9 
+#> 0.08915009 0.09127172 0.09078109 0.09968796 0.08977638 0.09481468
+
+var1$cutoff
+#>        40% 
+#> 0.09080765
+

Using our 40%% decile as a guide, we find that 0.091 is our target +standard error for an accurately measured item.

+
+
+

Minimum Sample Size +

+

To estimate minimum sample size, we should figure out what number of +participants it would take to achieve 80%, 85%, 90%, and 95% of the SEs +for items below our critical score of 0.091?

+
+cutoff <- calculate_cutoff(population = DF_long, 
+                           grouping_items = "item",
+                           score = "score",
+                           minimum = 1,
+                           maximum = 7)
+# showing how this is the same as the person calculated version versus semanticprimeR's function
+cutoff$cutoff
+#>        40% 
+#> 0.09080765
+

Please note that you will always need to simulate larger than the +pilot data sample size to get the starting numbers. We will correct them +below. As shown in our manuscript, we need to correct for the +overestimation of sample sizes based on the original pilot data size. +Given that the pilot data is large: 200, this correction is especially +useful. This correction is built into our function.

+
+final_table <- calculate_correction(
+  proportion_summary = var1$final_sample,
+  pilot_sample_size = nrow(DF),
+  proportion_variability = cutoff$prop_var
+  )
+
+flextable(final_table) %>% 
+  autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

percent_below

sample_size

corrected_sample_size

80.0

230

54.60714

90.5

245

62.29201

90.5

245

62.29201

97.0

255

68.01402

+
+

Our minimum suggested sample size does not exist at exactly 80% of +the items, but instead we can use the first available over 80% +(n = 55 as the minimum).

+
+
+

Maximum Sample Size +

+

While there are many considerations for maximum sample size (time, +effort, resources), the simulation suggests that 68 people would ensure +nearly all items achieve cutoff criterions.

+
+
+

Final Sample Size +

+

In any estimate for sample size, you should also consider the +potential for missing data and/or unusable data due to any other +exclusion criteria in your study (i.e., attention checks, speeding, +getting the answer right, etc.). In this study, we likely expect all +participants to see all items and therefore, we could expect to use the +minimum sample size as our final sample size, the point at which all +items reach our SE criterion, or the maximum sample size.

+
+
+
+
+ + + + +
+ + + + + + + diff --git a/docs/articles/batres_vignette_files/tabwid-1.1.3/tabwid.css b/docs/articles/batres_vignette_files/tabwid-1.1.3/tabwid.css new file mode 100644 index 0000000..5e31a86 --- /dev/null +++ b/docs/articles/batres_vignette_files/tabwid-1.1.3/tabwid.css @@ -0,0 +1,42 @@ +.tabwid { + font-size: initial; + padding-bottom: 1em; +} + +.tabwid table{ + border-spacing:0px !important; + border-collapse:collapse; + line-height:1; + margin-left:auto; + margin-right:auto; + border-width: 0; + border-color: transparent; + caption-side: top; +} +.tabwid-caption-bottom table{ + caption-side: bottom; +} +.tabwid_left table{ + margin-left:0; +} +.tabwid_right table{ + margin-right:0; +} +.tabwid td, .tabwid th { + padding: 0; +} +.tabwid a { + text-decoration: none; +} +.tabwid thead { + background-color: transparent; +} +.tabwid tfoot { + background-color: transparent; +} +.tabwid table tr { +background-color: transparent; +} +.katex-display { + margin: 0 0 !important; +} diff --git a/docs/articles/batres_vignette_files/tabwid-1.1.3/tabwid.js b/docs/articles/batres_vignette_files/tabwid-1.1.3/tabwid.js new file mode 100644 index 0000000..47070f7 --- /dev/null +++ b/docs/articles/batres_vignette_files/tabwid-1.1.3/tabwid.js @@ -0,0 +1,20 @@ +document.addEventListener("DOMContentLoaded", function(event) { + var els = document.querySelectorAll(".tabwid"); + var tabwid_link = document.querySelector('link[href*="tabwid.css"]') + if (tabwid_link === null) { + const tabwid_styles = document.evaluate("//style[contains(., 'tabwid')]", document, null, XPathResult.ANY_TYPE, null ); + tabwid_link = tabwid_styles.iterateNext(); + } + + Array.prototype.forEach.call(els, function(template) { + const dest = document.createElement("div"); + template.parentNode.insertBefore(dest, template.nextSibling) + dest.setAttribute("class", "flextable-shadow-host"); + const fantome = dest.attachShadow({mode: 'open'}); + fantome.appendChild(template); + if (tabwid_link !== null) { + fantome.appendChild(tabwid_link.cloneNode(true)); + } + }); +}); + diff --git a/docs/articles/geller_vignette.html b/docs/articles/geller_vignette.html new file mode 100644 index 0000000..a69c9de --- /dev/null +++ b/docs/articles/geller_vignette.html @@ -0,0 +1,512 @@ + + + + + + + + +Power and Sample Size Simulation: Overconfidence for picture cues in foreign language learning • semanticprimeR + + + + + + + + + + Skip to contents + + +
+ + + + +
+
+

Power and Sample Size Simulation: Overconfidence for picture cues in foreign language learning

+

Jason +Geller

+ +

2023-12-27

+ + +
geller_vignette.Rmd
+
+ + + +
+

Vignette Setup: +

+
+knitr::opts_chunk$set(echo = TRUE)
+
+# Set a random seed
+set.seed(3898934)
+
+# Libraries necessary for this vignette
+library(rio)
+library(flextable)
+library(dplyr)
+#> 
+#> Attaching package: 'dplyr'
+#> The following objects are masked from 'package:stats':
+#> 
+#>     filter, lag
+#> The following objects are masked from 'package:base':
+#> 
+#>     intersect, setdiff, setequal, union
+library(tidyr)
+library(psych)
+library(semanticprimeR)
+
+# Function for simulation
+item_power <- function(data, # name of data frame
+                       dv_col, # name of DV column as a character
+                       item_col, # number of items column as a character
+                       nsim = 10, # small for cran 
+                       sample_start = 20, 
+                       sample_stop = 200, 
+                       sample_increase = 5,
+                       decile = .5){
+  
+  DF <- cbind.data.frame(
+    "dv" = data[ , dv_col],
+    "items" = data[ , item_col]
+  )
+  
+  # just in case
+  colnames(DF) <- c("dv", "items")
+  
+  # figure out the "sufficiently narrow" ci value
+  SE <- tapply(DF$dv, DF$items, function (x) { sd(x)/sqrt(length(x)) })
+  cutoff <- quantile(SE, probs = decile)
+  
+  # sequence of sample sizes to try
+  samplesize_values <- seq(sample_start, sample_stop, sample_increase)
+
+  # create a blank table for us to save the values in 
+  sim_table <- matrix(NA, 
+                      nrow = length(samplesize_values)*nsim, 
+                      ncol = length(unique(DF$items)))
+
+  # make it a data frame
+  sim_table <- as.data.frame(sim_table)
+
+  # add a place for sample size values 
+  sim_table$sample_size <- NA
+
+  iterate <- 1
+  
+  for (p in 1:nsim){
+    # loop over sample sizes
+    for (i in 1:length(samplesize_values)){
+        
+      # temp that samples and summarizes
+      temp <- DF %>% 
+        group_by(items) %>% 
+        sample_n(samplesize_values[i], replace = T) %>% 
+        summarize(se = sd(dv)/sqrt(length(dv)))
+      
+      # dv on items
+      colnames(sim_table)[1:length(unique(DF$items))] <- temp$items
+      sim_table[iterate, 1:length(unique(DF$items))] <- temp$se
+      sim_table[iterate, "sample_size"] <- samplesize_values[i]
+      sim_table[iterate, "nsim"] <- p
+      
+      iterate <- iterate + 1
+    }
+  }
+
+  # figure out cut off
+  final_sample <- sim_table %>% 
+    pivot_longer(cols = -c(sample_size, nsim)) %>% 
+    dplyr::rename(item = name, se = value) %>% 
+    group_by(sample_size, nsim) %>% 
+    summarize(percent_below = sum(se <= cutoff)/length(unique(DF$items))) %>% 
+    ungroup() %>% 
+    # then summarize all down averaging percents
+    dplyr::group_by(sample_size) %>% 
+    summarize(percent_below = mean(percent_below)) %>% 
+    dplyr::arrange(percent_below) %>% 
+    ungroup()
+  
+  return(list(
+    SE = SE, 
+    cutoff = cutoff, 
+    DF = DF, 
+    sim_table = sim_table, 
+    final_sample = final_sample
+  ))
+
+}
+
+
+

Project/Data Title: +

+

Overconfidence for picture cues in foreign language learning

+

Data provided by: Jason Geller

+
+
+

Project/Data Description: +

+

Previous research shows that participants are overconfident in their +ability to learn foreign language vocabulary from pictures compared with +English translations. The current study explored whether this tendency +is due to processing fluency or beliefs about learning. Using self-paced +study of Swahili words paired with either picture cues or English +translation cues, 30 participants provided JOLs to each of the 42 +English-Swahili word pairs from Carpenter and Olson’s (2012) Experiment +2.The English words were one-syllable nouns, ranging between three and +six letters, with an average concreteness rating of 4.86 on a 5-point +scale (SD = .16) (Brysbaert, Warriner, & Kuperman, 2014), and an +average frequency of 106.52 per million (SD = 113.40) (Brysbaert & +New, 2009).

+
+
+

Methods Description: +

+

Participants began the experiment with instructions informing them +that they would be learning Swahili words paired with either pictures or +English translations as cues. To illustrate each type of cue, they were +given an example of an item (Train: Reli) that was not included among +the 42 experimental items. They were informed that each pair of items +(English-Swahili pairs or picture-Swahili pairs) would be presented one +at a time, and they would have as much time as they needed to study it. +Participants were encouraged to do their best to learn each pair, and to +encourage full and meaningful processing of each, they were instructed +to press the spacebar once they felt they had fully “digested” it. For +each participant, 21 items were randomly selected to be presented as +English-Swahili pairs, and 21 as picture-Swahili pairs. Participants saw +each stimulus pair one at a time, in a unique random order with +English-Swahili pairs and picture-Swahili pairs intermixed. Each pair +was presented in the center of the computer screen and remained on +screen until participants pressed the spacebar to move on to the next +pair. After each of the 42 pairs was presented for self-paced study in +this way, the same pairs were presented again for JOLs. During a JOL +trial, each cue-target pair was presented on the screen and participants +were asked to estimate—using a scale from 0% (definitely will NOT +recall) to 100% (definitely will recall)—the likelihood of recalling the +Swahili word from its cue (either the picture or English translation) +after about 5 minutes. Participants entered a value between 0 and 100 +and pressed the ENTER key to advance to the next item.

+
+
+

Data Location: +

+

Data can be found here: https://osf.io/2byt9/.

+
+#read in data
+DF <- import("data/geller_data.xlsx") %>% 
+  select(Experiment, Subject, `CueType[1Word,2Pic]`, Stimulus, EncodeJOL)
+#> Warning: Expecting numeric in J2069 / R2069C10: got 'jico'
+  
+str(DF)
+#> 'data.frame':    2898 obs. of  5 variables:
+#>  $ Experiment         : num  1 1 1 1 1 1 1 1 1 1 ...
+#>  $ Subject            : num  1 1 1 1 1 1 1 1 1 1 ...
+#>  $ CueType[1Word,2Pic]: num  1 1 1 1 1 1 1 1 1 1 ...
+#>  $ Stimulus           : chr  "kidoto" "muhindi" "kiti" "jaluba" ...
+#>  $ EncodeJOL          : num  1 1 1 1 1 1 1 1 1 1 ...
+
+
+

Date Published: +

+

No official publication, see citation below.

+
+
+

Dataset Citation: +

+

Carpenter, S. K., & Geller, J. (2020). Is a picture really worth +a thousand words? Evaluating contributions of fluency and analytic +processing in metacognitive judgements for pictures in foreign language +vocabulary learning. Quarterly Journal of Experimental Psychology, +73(2), 211–224. https://doi.org/10.1177/1747021819879416

+
+
+

Citations: +

+

Brysbaert, M., Warriner, A. B., & Kuperman, V. (2014). +Concreteness ratings for 40 thousand generally known English word +lemmas. Behavior Research Methods, 46(3), 904–911. https://doi.org/10.3758/s13428-013-0403-5

+

Brysbaert, M., & New, B. (2009). Moving beyond Kučera and +Francis: A critical evaluation of current word frequency norms and the +introduction of a new and improved word frequency measure for American +English. Behavior Research Methods, 41(4), 977–990. https://doi.org/10.3758/BRM.41.4.977

+

Carpenter, S. K., & Geller, J. (2020). Is a picture really worth +a thousand words? Evaluating contributions of fluency and analytic +processing in metacognitive judgements for pictures in foreign language +vocabulary learning. Quarterly Journal of Experimental Psychology, +73(2), 211–224. https://doi.org/10.1177/1747021819879416

+

Carpenter, S. K., & Olson, K. M. (2012). Are pictures good for +learning new vocabulary in a foreign language? Only if you think they +are not. Journal of Experimental Psychology: Learning, Memory, and +Cognition, 38(1), 92–101. https://doi.org/10.1037/a0024828

+
+
+

Keywords: +

+

Overconfidence, metacognition, processing fluency, analytic +processing, foreign language learning

+
+
+

Use License: +

+

Open access with reference to original paper +(Attribution-NonCommercial-ShareAlike CC BY-NC-SA)

+
+
+

Geographic Description - City/State/Country of Participants: +

+

Ames, Iowa

+
+
+

Column Metadata: +

+
+metadata <- tibble::tribble(
+             ~Variable.Name,                                                                  ~Variable.Description, ~`Type (numeric,.character,.logical,.etc.)`,
+               "Experiment",                                                 "Experiment 1 (1) or 2 (2) ONLY USE 1",                                          NA,
+                  "Subject",                                                                           "Subject ID",                                   "Numeric",
+                  "CueType", "Whether participant was presented with word translation (1) or word with picture (2)",                                   "Numeric",
+                 "Stimulus",                                                "Swahili words presented on each trail",                                 "Character",
+                "EncodeJOL",                         "JOL (1-100) 1=not likely to recall 100=very likely to recall",                                   "Numeric"
+             )
+
+flextable(metadata) %>% autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

Variable.Name

Variable.Description

Type (numeric,.character,.logical,.etc.)

Experiment

Experiment 1 (1) or 2 (2) ONLY USE 1

Subject

Subject ID

Numeric

CueType

Whether participant was presented with word translation (1) or word with picture (2)

Numeric

Stimulus

Swahili words presented on each trail

Character

EncodeJOL

JOL (1-100) 1=not likely to recall 100=very likely to recall

Numeric

+
+
+
+

AIPE Analysis: +

+
+

Stopping Rule +

+
+DF <- DF %>% 
+  filter(Experiment == 1) %>%
+  filter(!is.na(EncodeJOL))
+
+# Function for simulation
+var1 <- item_power(data = DF, # name of data frame
+            dv_col = "EncodeJOL", # name of DV column as a character
+            item_col = "Stimulus", # number of items column as a character
+            nsim = 10,
+            sample_start = 20, 
+            sample_stop = 100, 
+            sample_increase = 5,
+            decile = .4)
+#> `summarise()` has grouped output by 'sample_size'. You can override using the
+#> `.groups` argument.
+

What the usual standard error for the data that could be considered +for our stopping rule using the 40% decile?

+
+# individual SEs
+var1$SE
+#>   andiko      bao  bunduki    chaka   chapeo chimbule   daraja   dawati 
+#> 5.569863 5.421327 6.467708 5.812192 5.232406 5.964306 5.006286 4.295635 
+#>     dubu   duwara   farasi      fia     fupa     gari     geli     jaja 
+#> 6.825573 3.857377 6.126705 5.192728 6.954286 6.092600 5.496488 7.424850 
+#>   jaluba    jicho     jiti    jumba     juya   kanisa     kelb   kidoto 
+#> 4.803243 5.649133 6.229624 5.405121 3.783108 6.245590 6.311649 4.324860 
+#>   kipira  kitanda     kiti   maliki    mapwa    mkono   mlango  muhindi 
+#> 5.895944 5.515605 6.404627 6.614947 6.634286 7.609701 5.745819 5.471669 
+#>   muundi papatiko      pua    rinda     riza   safina   samaki     simu 
+#> 6.108910 6.681585 6.309811 5.378363 6.045881 6.548968 5.384973 5.490716 
+#>  ufunguo    wardi 
+#> 6.229707 5.739385
+
+var1$cutoff
+#>      40% 
+#> 5.601571
+

Using our 40% decile as a guide, we find that 5.602 is our target +standard error for an accurately measured item.

+
+
+

Minimum Sample Size +

+

To estimate minimum sample size, we should figure out what number of +participants it would take to achieve 80%, 85%, 90%, and 95% of the SEs +for items below our critical score of 5.602?

+
+cutoff <- calculate_cutoff(population = DF, 
+                           grouping_items = "Stimulus",
+                           score = "EncodeJOL",
+                           minimum = as.numeric(min(DF$EncodeJOL)),
+                           maximum = as.numeric(max(DF$EncodeJOL)))
+# showing how this is the same as the person calculated version versus semanticprimeR's function
+cutoff$cutoff
+#>      40% 
+#> 5.601571
+
+final_table <- calculate_correction(
+  proportion_summary = var1$final_sample,
+  pilot_sample_size = length(unique(DF$Subject)),
+  proportion_variability = cutoff$prop_var
+  )
+
+flextable(final_table) %>% 
+  autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

percent_below

sample_size

corrected_sample_size

87.85714

35

31.48800

87.85714

35

31.48800

97.38095

40

39.17344

97.38095

40

39.17344

+
+

Our minimum sample size is (n = 31 as the minimum at 80%). +We could consider using 90% (n = 39) or 95% (n = +39).

+
+
+

Maximum Sample Size +

+

While there are many considerations for maximum sample size (time, +effort, resources), if we consider a higher value just for estimation +sake, we could use n = at nearly 100%.

+
+
+

Final Sample Size +

+

In any estimate for sample size, you should also consider the +potential for missing data and/or unusable data due to any other +exclusion criteria in your study (i.e., attention checks, speeding, +getting the answer right, etc.). In this study, these values may be +influenced by the pictures/word split in the study.

+
+
+
+
+ + + + +
+ + + + + + + diff --git a/docs/articles/geller_vignette_files/tabwid-1.1.3/tabwid.css b/docs/articles/geller_vignette_files/tabwid-1.1.3/tabwid.css new file mode 100644 index 0000000..5e31a86 --- /dev/null +++ b/docs/articles/geller_vignette_files/tabwid-1.1.3/tabwid.css @@ -0,0 +1,42 @@ +.tabwid { + font-size: initial; + padding-bottom: 1em; +} + +.tabwid table{ + border-spacing:0px !important; + border-collapse:collapse; + line-height:1; + margin-left:auto; + margin-right:auto; + border-width: 0; + border-color: transparent; + caption-side: top; +} +.tabwid-caption-bottom table{ + caption-side: bottom; +} +.tabwid_left table{ + margin-left:0; +} +.tabwid_right table{ + margin-right:0; +} +.tabwid td, .tabwid th { + padding: 0; +} +.tabwid a { + text-decoration: none; +} +.tabwid thead { + background-color: transparent; +} +.tabwid tfoot { + background-color: transparent; +} +.tabwid table tr { +background-color: transparent; +} +.katex-display { + margin: 0 0 !important; +} diff --git a/docs/articles/geller_vignette_files/tabwid-1.1.3/tabwid.js b/docs/articles/geller_vignette_files/tabwid-1.1.3/tabwid.js new file mode 100644 index 0000000..47070f7 --- /dev/null +++ b/docs/articles/geller_vignette_files/tabwid-1.1.3/tabwid.js @@ -0,0 +1,20 @@ +document.addEventListener("DOMContentLoaded", function(event) { + var els = document.querySelectorAll(".tabwid"); + var tabwid_link = document.querySelector('link[href*="tabwid.css"]') + if (tabwid_link === null) { + const tabwid_styles = document.evaluate("//style[contains(., 'tabwid')]", document, null, XPathResult.ANY_TYPE, null ); + tabwid_link = tabwid_styles.iterateNext(); + } + + Array.prototype.forEach.call(els, function(template) { + const dest = document.createElement("div"); + template.parentNode.insertBefore(dest, template.nextSibling) + dest.setAttribute("class", "flextable-shadow-host"); + const fantome = dest.attachShadow({mode: 'open'}); + fantome.appendChild(template); + if (tabwid_link !== null) { + fantome.appendChild(tabwid_link.cloneNode(true)); + } + }); +}); + diff --git a/docs/articles/heyman_vignette.html b/docs/articles/heyman_vignette.html new file mode 100644 index 0000000..8df177c --- /dev/null +++ b/docs/articles/heyman_vignette.html @@ -0,0 +1,584 @@ + + + + + + + + +Power and Sample Size Simulation: Reaction Time Example (raw RT) • semanticprimeR + + + + + + + + + + Skip to contents + + +
+ + + + +
+
+

Power and Sample Size Simulation: Reaction Time Example (raw RT)

+

Christopher L. +Aberson

+ +

2023-12-27

+ + +
heyman_vignette.Rmd
+
+ + + +
+

Vignette Setup: +

+
+
+

Project/Data Title: +

+

Continuous lexical decision task: classification of Dutch words as +either actual words or nonwords

+

Data provided by: Tom Heyman

+
+
+

Project/Data Description: +

+

Data come from a study reported in Heyman, De Deyne, Hutchison, & +Storms (2015, Behavior Research Methods; henceforth HDHS). More +specifically, the study involved a continuous lexical decision task +intended to measure (item-level) semantic priming effects (i.e., +Experiment 3 of HDHS). It is similar to the SPAML set-up (see https://osf.io/q4fjy/), but +with fewer items and participants. The study had several goals, but +principally we wanted to examine how a different/new paradigm called the +speeded word fragment completion task would compare against a more +common, well-established paradigm like lexical decision in terms of +semantic priming (i.e., magnitude of the effect, reliability of +item-level priming, cross-task correlation of item-level priming +effects, etc.). Experiment 3 only involved a continuous lexical decision +task, so the datafile contains no data from the speeded word fragment +completion task.

+
+
+

Methods Description: +

+

Participants were 40 students from the University of Leuven, Belgium +(10 men, 30 women, mean age 20 years). A total of 576 pairs were used in +a continuous lexical decision task (so participants do not perceive them +as pairs): 144 word–word pairs, 144 word–pseudoword pairs, 144 +pseudoword–word pairs, and 144 pseudoword–pseudoword pairs. Of the 144 +word-word pairs, 72 were fillers and 72 were critical pairs, half of +which were related, the other half unrelated (this was counterbalanced +across participants). The dataset only contains data for the critical +pairs. Participants were informed that they would see a letter string on +each trial and that they had to indicate whether the letter string +formed an existing Dutch word or not by pressing the arrow keys. Half of +the participants had to press the left arrow for word and the right +arrow for nonword, and vice versa for the other half.

+
+
+

Data Location: +

+

https://osf.io/frxpd/

+

The example dataset also includes R scripts at this location +that used Accuracy in Parameter Estimation in a different fashion.

+
+HDHS<- read.csv("data/HDHSAIPE.txt", sep="")
+str(HDHS)
+#> 'data.frame':    2880 obs. of  8 variables:
+#>  $ RT       : num  0.52 0.453 0.467 0.534 0.573 ...
+#>  $ zRT      : num  -0.303 -0.492 -0.453 -0.265 -0.153 ...
+#>  $ Pp       : int  1 1 1 1 1 1 1 1 1 1 ...
+#>  $ Type     : chr  "R" "R" "R" "R" ...
+#>  $ Prime    : chr  "hengst" "matrak" "eland" "erwt" ...
+#>  $ Target   : chr  "veulen" "wapen" "gewei" "wortel" ...
+#>  $ accTarget: int  1 1 1 1 1 1 1 1 1 0 ...
+#>  $ accPrime : int  1 1 1 1 0 1 1 1 1 0 ...
+
+
+

Date Published: +

+

2022-02-04

+
+
+

Dataset Citation: +

+

Heyman, T. (2022, February 4). Dataset AIPE. Retrieved from +osf.io/frxpd [based on Heyman, T., De Deyne, S., Hutchison, K. A., & +Storms, G. (2015). Using the speeded word fragment completion task to +examine semantic priming. Behavior Research Methods, 47(2), +580-606.]

+
+
+

Keywords: +

+

Semantic priming; continuous lexical decision task

+
+
+

Use License: +

+

CC-By Attribution 4.0 International

+
+
+

Geographic Description - City/State/Country of Participants: +

+

Belgium

+
+
+

Column Metadata: +

+
+metadata <- import("data/HDHSMeta.txt")
+
+flextable(metadata) %>% autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

Variable Name

Variable Description

Type (numeric, character, logical, etc.)

RT

Response time to the target in seconds

Numeric

zRT

Z-transformed target response times per participant

Numeric

Pp

Participant identifier (1 to 40)

Integer

Type

Whether target was preceded by a related prime (R) or an unrelated prime (U)

Character

Prime

Prime stimulus (in Dutch)

Character

Target

Target stimulus (in Dutch)

Character

accTarget

Whether response to target was correct (1) or not (0)

Integer

accPrime

Whether response to the preceding prime was correct (1) or not (0)

Integer

+
+
+
+

AIPE Analysis: +

+
+# pick only correct answers
+HDHScorrect <- HDHS[HDHS$accTarget==1,] 
+summary_stats <- HDHScorrect %>% #data frame
+  select(RT, Target) %>% #pick the columns
+  group_by(Target) %>% #put together the stimuli
+  summarize(SES = sd(RT)/sqrt(length(RT)), samplesize = length(RT)) #create SE and the sample size for below
+##give descriptives of the SEs
+describe(summary_stats$SES)
+#>    vars  n mean   sd median trimmed  mad  min  max range skew kurtosis   se
+#> X1    1 72 0.05 0.05   0.03    0.04 0.02 0.02 0.31  0.29 3.63    13.19 0.01
+
+##figure out the original sample sizes (not really necessary as all Targets were seen by 40 participants)
+original_SS <- HDHS %>% #data frame
+  count(Target) #count up the sample size
+##add the original sample size to the data frame
+summary_stats <- merge(summary_stats, original_SS, by = "Target")
+##original sample size average
+describe(summary_stats$n)
+#>    vars  n mean sd median trimmed mad min max range skew kurtosis se
+#> X1    1 72   40  0     40      40   0  40  40     0  NaN      NaN  0
+
+##reduced sample size
+describe(summary_stats$samplesize)
+#>    vars  n  mean   sd median trimmed  mad min max range  skew kurtosis   se
+#> X1    1 72 38.12 3.09     39   38.83 1.48  22  40    18 -3.29    12.08 0.36
+
+##percent retained
+describe(summary_stats$samplesize/summary_stats$n)
+#>    vars  n mean   sd median trimmed  mad  min max range  skew kurtosis   se
+#> X1    1 72 0.95 0.08   0.98    0.97 0.04 0.55   1  0.45 -3.29    12.08 0.01
+
+flextable(head(HDHScorrect)) %>% autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

RT

zRT

Pp

Type

Prime

Target

accTarget

accPrime

0.5202093

-0.3026836

1

R

hengst

veulen

1

1

0.4532606

-0.4918172

1

R

matrak

wapen

1

1

0.4670391

-0.4528923

1

R

eland

gewei

1

1

0.5335296

-0.2650529

1

R

erwt

wortel

1

1

0.5732744

-0.1527717

1

R

ijzel

glad

1

0

0.3870141

-0.6789673

1

R

sauna

warm

1

1

+
+
+

Stopping Rule +

+

What the usual standard error for the data that could be considered +for our stopping rule?

+
+SE <- tapply(HDHScorrect$RT, HDHScorrect$Target, function (x) { sd(x)/sqrt(length(x)) })
+min(SE)
+#> [1] 0.01511263
+max(SE)
+#> [1] 0.3058638
+
+cutoff <- quantile(SE, probs = .4)
+cutoff
+#>        40% 
+#> 0.03113963
+

The items have a range of 0.0151126 to 0.3058638. We could use the +40% decile SE = 0.0311396 as our critical value for our stopping rule, +as suggested by the manuscript analysis. We could also have a set SE to +a specific target if we do not believe we have representative pilot data +in this example. You should also consider the scale when estimating +these values (i.e., millisecond data has more room to vary than other +smaller scales).

+
+
+

Minimum Sample Size +

+

To estimate minimum sample size, we should figure out what number of +participants it would take to achieve 80% of the SEs for items below our +critical score of 0.0311396?

+
+# sequence of sample sizes to try
+nsim <- 10 # small for cran
+samplesize_values <- seq(20, 500, 5)
+
+# create a blank table for us to save the values in 
+sim_table <- matrix(NA, 
+                    nrow = length(samplesize_values)*nsim, 
+                    ncol = length(unique(HDHS$Target)))
+
+# make it a data frame
+sim_table <- as.data.frame(sim_table)
+
+# add a place for sample size values 
+sim_table$sample_size <- NA
+
+iterate <- 1
+
+for (p in 1:nsim){
+  
+  # loop over sample sizes
+  for (i in 1:length(samplesize_values)){
+      
+    # temp dataframe that samples and summarizes
+    temp <- HDHScorrect %>% 
+      group_by(Target) %>% 
+      sample_n(samplesize_values[i], replace = T) %>% 
+      summarize(se = sd(RT)/sqrt(length(RT))) 
+    
+    colnames(sim_table)[1:length(unique(HDHScorrect$Target))] <- temp$Target
+    sim_table[iterate, 1:length(unique(HDHScorrect$Target))] <- temp$se
+    sim_table[iterate, "sample_size"] <- samplesize_values[i]
+    sim_table[iterate, "nsim"] <- p
+    iterate <- 1 + iterate
+  }
+  
+}
+
+final_sample <- 
+  sim_table %>% 
+  pivot_longer(cols = -c(sample_size, nsim)) %>% 
+  group_by(sample_size, nsim) %>% 
+  summarize(percent_below = sum(value <= cutoff)/length(unique(HDHScorrect$Target))) %>% 
+  ungroup() %>% 
+  # then summarize all down averaging percents
+  dplyr::group_by(sample_size) %>% 
+  summarize(percent_below = mean(percent_below)) %>% 
+  dplyr::arrange(percent_below) %>% 
+  ungroup()
+#> `summarise()` has grouped output by 'sample_size'. You can override using the
+#> `.groups` argument.
+
+flextable(final_sample %>% head()) %>% autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

sample_size

percent_below

20

0.3958333

25

0.4416667

30

0.4527778

35

0.4972222

40

0.5430556

45

0.5708333

+
+
+
+

Expected Data Loss +

+

The original data found that 4.6875 percent of the data were +unusable.

+
+
+

Minimum Sample Size +

+
+# use semanticprimer cutoff function for prop variance
+cutoff <- calculate_cutoff(population = HDHScorrect, 
+                           grouping_items = "Target",
+                           score = "RT",
+                           minimum = as.numeric(min(HDHScorrect$RT)),
+                           maximum = as.numeric(max(HDHScorrect$RT)))
+# showing how this is the same as the person calculated version versus semanticprimeR's function
+cutoff$cutoff
+#>        40% 
+#> 0.03113963
+
+final_table <- calculate_correction(
+  proportion_summary = final_sample,
+  pilot_sample_size = HDHScorrect %>% group_by(Target) %>% 
+    summarize(sample_size = n()) %>% 
+    ungroup() %>% summarize(avg_sample = mean(sample_size)) %>% 
+    pull(avg_sample),
+  proportion_variability = cutoff$prop_var
+  )
+
+flextable(final_table) %>% 
+  autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + +

percent_below

sample_size

corrected_sample_size

80.55556

95

84.96635

85.41667

120

103.14554

90.13889

180

141.33833

+
+

Based on these simulations, we can decide our minimum sample size is +likely close to 85 and 88.984375 including information about data +loss.

+
+
+

Maximum Sample Size +

+

In this example, we could set our maximum sample size for 90% power +(as defined as 90% of items below our criterion), which would equate to +141 and 147.609375 with the expected data loss. The final table does not +include 95% of items below our criterion, even after estimating 500 +participants. An investigation of the table indicates that it levels off +at 93-94%.

+
+
+

Final Sample Size +

+

In any estimate of sample size, you should also consider the +potential for missing data and/or unusable data due to any other +exclusion criteria in your study (i.e., attention checks, speeding, +getting the answer right, etc.). In this study, we likely expect all +participants to see all items, and therefore, we could expect to use the +minimum sample size as our final sample size, the point at which all +items reach our SE criterion, or the maximum sample size. Note that +maximum sample sizes can also be defined by time, money, or other +means.

+
+
+
+
+ + + + +
+ + + + + + + diff --git a/docs/articles/heyman_vignette_files/tabwid-1.1.3/tabwid.css b/docs/articles/heyman_vignette_files/tabwid-1.1.3/tabwid.css new file mode 100644 index 0000000..5e31a86 --- /dev/null +++ b/docs/articles/heyman_vignette_files/tabwid-1.1.3/tabwid.css @@ -0,0 +1,42 @@ +.tabwid { + font-size: initial; + padding-bottom: 1em; +} + +.tabwid table{ + border-spacing:0px !important; + border-collapse:collapse; + line-height:1; + margin-left:auto; + margin-right:auto; + border-width: 0; + border-color: transparent; + caption-side: top; +} +.tabwid-caption-bottom table{ + caption-side: bottom; +} +.tabwid_left table{ + margin-left:0; +} +.tabwid_right table{ + margin-right:0; +} +.tabwid td, .tabwid th { + padding: 0; +} +.tabwid a { + text-decoration: none; +} +.tabwid thead { + background-color: transparent; +} +.tabwid tfoot { + background-color: transparent; +} +.tabwid table tr { +background-color: transparent; +} +.katex-display { + margin: 0 0 !important; +} diff --git a/docs/articles/heyman_vignette_files/tabwid-1.1.3/tabwid.js b/docs/articles/heyman_vignette_files/tabwid-1.1.3/tabwid.js new file mode 100644 index 0000000..47070f7 --- /dev/null +++ b/docs/articles/heyman_vignette_files/tabwid-1.1.3/tabwid.js @@ -0,0 +1,20 @@ +document.addEventListener("DOMContentLoaded", function(event) { + var els = document.querySelectorAll(".tabwid"); + var tabwid_link = document.querySelector('link[href*="tabwid.css"]') + if (tabwid_link === null) { + const tabwid_styles = document.evaluate("//style[contains(., 'tabwid')]", document, null, XPathResult.ANY_TYPE, null ); + tabwid_link = tabwid_styles.iterateNext(); + } + + Array.prototype.forEach.call(els, function(template) { + const dest = document.createElement("div"); + template.parentNode.insertBefore(dest, template.nextSibling) + dest.setAttribute("class", "flextable-shadow-host"); + const fantome = dest.attachShadow({mode: 'open'}); + fantome.appendChild(template); + if (tabwid_link !== null) { + fantome.appendChild(tabwid_link.cloneNode(true)); + } + }); +}); + diff --git a/docs/articles/index.html b/docs/articles/index.html new file mode 100644 index 0000000..e0e17d6 --- /dev/null +++ b/docs/articles/index.html @@ -0,0 +1,101 @@ + +Articles • semanticprimeR + Skip to contents + + +
+
+
+

Articles

+
+ +
+

All vignettes

+

+ +
Power and Sample Size Simulation: Italian Age of Acquisition Norms for a Large Set of Words (ItAoA)
+
+
Power and Sample Size Simulation: Cue Word Valence Data Example
+
+
Power and Sample Size Simulation: Attractiveness Ratings Example
+
+
Power and Sample Size Simulation: Overconfidence for picture cues in foreign language learning
+
+
Power and Sample Size Simulation: Reaction Time Example (raw RT)
+
+
Power and Sample Size Simulation: EAMMi2
+
+
Power and Sample Size Simulation: Seeing is Believing
+
+
Power and Sample Size Simulatio: Online search trends and word-related emotional response during COVID-19 lockdown in Italy
+
+
Power and Sample Size Simulation: Survival Processing Usefulness
+
+
Power and Sample Size Simulation: Superficial Face Judgment
+
+
Power and Sample Size Simulation: Liking effect induced by gaze
+
+
Power and Sample Size Simulation: Typicality, goodness, imageability, and familiarity of stimuli across 16 categories
+
+
+
+ + +
+ + + + + + + diff --git a/docs/articles/mcfall_vignette.html b/docs/articles/mcfall_vignette.html new file mode 100644 index 0000000..e77a227 --- /dev/null +++ b/docs/articles/mcfall_vignette.html @@ -0,0 +1,1376 @@ + + + + + + + + +Power and Sample Size Simulation: EAMMi2 • semanticprimeR + + + + + + + + + + Skip to contents + + +
+ + + + +
+
+

Power and Sample Size Simulation: EAMMi2

+

Christopher L. +Aberson

+ +

2023-12-27

+ + +
mcfall_vignette.Rmd
+
+ + + +
+

Vignette Setup: +

+
+
+

Project/Data Title: +

+

Emerging Adulthood Measured at Multiple Institutions 2: The Next +Generation (EAMMi2)

+

Data provided by: Joe McFall

+
+
+

Project/Data Description: +

+

Collaborators from 32 academic institutions primarily in the United +States collected data from emerging adults (Nraw = 4220, Nprocessed = +3134). Participants completed self-report measures assessing markers of +adulthood, IDEA inventory of dimensions of emerging adulthood, +subjective well-being, mindfulness, belonging, self-efficacy, disability +identity, somatic health, perceived stress, perceived social support, +social media use, political affiliation, beliefs about the American +dream, interpersonal transgressions, narcissism, interpersonal +exploitativeness, beliefs about marriage, and demographics.

+
+
+

Methods Description: +

+

Project organizers recruited contributors through social media +(Facebook & Twitter) and listserv invitations (Society of +Personality and Social Psychology, Society of Teaching Psychology).

+
+
+

Data Location: +

+

https://osf.io/qtqpb/

+
+EAMMi2<- import("data/mcfall_data.sav.zip") %>% 
+  select(starts_with("moa1#"), starts_with("moa2#"))
+str(EAMMi2)
+#> 'data.frame':    3134 obs. of  40 variables:
+#>  $ moa1#1_1 : num  3 4 4 4 4 4 3 4 4 1 ...
+#>   ..- attr(*, "label")= chr "imp_financialindependence"
+#>   ..- attr(*, "format.spss")= chr "F12.0"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:2] 1 4
+#>   .. ..- attr(*, "names")= chr [1:2] "not important" "important"
+#>  $ moa1#1_2 : num  4 4 4 3 2 3 2 3 3 2 ...
+#>   ..- attr(*, "label")= chr "imp_nolongerhom"
+#>   ..- attr(*, "format.spss")= chr "F12.0"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:2] 1 4
+#>   .. ..- attr(*, "names")= chr [1:2] "not important" "important"
+#>  $ moa1#1_3 : num  3 4 4 4 4 4 1 2 4 1 ...
+#>   ..- attr(*, "label")= chr "imp_finishededucation"
+#>   ..- attr(*, "format.spss")= chr "F12.0"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:2] 1 4
+#>   .. ..- attr(*, "names")= chr [1:2] "not important" "important"
+#>  $ moa1#1_4 : num  2 1 4 3 3 NA 1 1 4 1 ...
+#>   ..- attr(*, "label")= chr "imp_married"
+#>   ..- attr(*, "format.spss")= chr "F12.0"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:2] 1 4
+#>   .. ..- attr(*, "names")= chr [1:2] "not important" "important"
+#>  $ moa1#1_5 : num  3 1 4 3 3 NA 1 1 4 1 ...
+#>   ..- attr(*, "label")= chr "imp_havechild"
+#>   ..- attr(*, "format.spss")= chr "F12.0"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:2] 1 4
+#>   .. ..- attr(*, "names")= chr [1:2] "not important" "important"
+#>  $ moa1#1_6 : num  4 3 3 4 3 4 1 2 4 1 ...
+#>   ..- attr(*, "label")= chr "imp_settledcareer"
+#>   ..- attr(*, "format.spss")= chr "F12.0"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:2] 1 4
+#>   .. ..- attr(*, "names")= chr [1:2] "not important" "important"
+#>  $ moa1#1_7 : num  4 2 1 4 4 4 1 1 3 4 ...
+#>   ..- attr(*, "label")= chr "imp_avoiddrunk"
+#>   ..- attr(*, "format.spss")= chr "F12.0"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:2] 1 4
+#>   .. ..- attr(*, "names")= chr [1:2] "not important" "important"
+#>  $ moa1#1_8 : num  4 3 4 4 4 4 4 1 3 4 ...
+#>   ..- attr(*, "label")= chr "imp_avoiddrugs"
+#>   ..- attr(*, "format.spss")= chr "F12.0"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:2] 1 4
+#>   .. ..- attr(*, "names")= chr [1:2] "not important" "important"
+#>  $ moa1#1_9 : num  4 4 4 4 2 4 4 1 2 4 ...
+#>   ..- attr(*, "label")= chr "imp_usecontraception"
+#>   ..- attr(*, "format.spss")= chr "F12.0"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:2] 1 4
+#>   .. ..- attr(*, "names")= chr [1:2] "not important" "important"
+#>  $ moa1#1_10: num  2 2 4 3 3 3 1 1 3 1 ...
+#>   ..- attr(*, "label")= chr "imp_committedlongterm"
+#>   ..- attr(*, "format.spss")= chr "F12.0"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:2] 1 4
+#>   .. ..- attr(*, "names")= chr [1:2] "not important" "important"
+#>  $ moa1#2_1 : num  1 2 2 3 2 1 2 1 2 3 ...
+#>   ..- attr(*, "label")= chr "ach_financialindependence"
+#>   ..- attr(*, "format.spss")= chr "F12.1"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:3] 1 2 3
+#>   .. ..- attr(*, "names")= chr [1:3] "no" "somewhat" "yes"
+#>  $ moa1#2_2 : num  3 1 3 1 2 3 2 2 1 3 ...
+#>   ..- attr(*, "label")= chr "ach_nolongerhome"
+#>   ..- attr(*, "format.spss")= chr "F12.1"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:3] 1 2 3
+#>   .. ..- attr(*, "names")= chr [1:3] "no" "somewhat" "achieved"
+#>  $ moa1#2_3 : num  1 2 2 2 1 1 2 1 1 3 ...
+#>   ..- attr(*, "label")= chr "ach_finishededucation"
+#>   ..- attr(*, "format.spss")= chr "F12.1"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:3] 1 2 3
+#>   .. ..- attr(*, "names")= chr [1:3] "no" "somewhat" "achieved"
+#>  $ moa1#2_4 : num  2 1 3 1 1 NA 2 1 1 3 ...
+#>   ..- attr(*, "label")= chr "ach_married"
+#>   ..- attr(*, "format.spss")= chr "F12.1"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:3] 1 2 3
+#>   .. ..- attr(*, "names")= chr [1:3] "no" "somewhat" "achieved"
+#>  $ moa1#2_5 : num  3 1 3 1 1 NA 2 1 1 2 ...
+#>   ..- attr(*, "label")= chr "ach_havechild"
+#>   ..- attr(*, "format.spss")= chr "F12.1"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:3] 1 2 3
+#>   .. ..- attr(*, "names")= chr [1:3] "no" "somewhat" "achieved"
+#>  $ moa1#2_6 : num  2 2 1 1 1 1 2 1 1 3 ...
+#>   ..- attr(*, "label")= chr "ach_settledcareer"
+#>   ..- attr(*, "format.spss")= chr "F12.1"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:3] 1 2 3
+#>   .. ..- attr(*, "names")= chr [1:3] "no" "somewhat" "achieved"
+#>  $ moa1#2_7 : num  3 2 1 3 2 3 2 1 1 3 ...
+#>   ..- attr(*, "label")= chr "ach_avoiddrunk"
+#>   ..- attr(*, "format.spss")= chr "F12.1"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:3] 1 2 3
+#>   .. ..- attr(*, "names")= chr [1:3] "no" "somewhat" "achieved"
+#>  $ moa1#2_8 : num  3 3 3 3 3 3 2 1 1 3 ...
+#>   ..- attr(*, "label")= chr "ach_avoiddrugs"
+#>   ..- attr(*, "format.spss")= chr "F12.1"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:3] 1 2 3
+#>   .. ..- attr(*, "names")= chr [1:3] "no" "somewhat" "achieved"
+#>  $ moa1#2_9 : num  3 3 3 3 3 3 2 3 3 3 ...
+#>   ..- attr(*, "label")= chr "ach_usecontraception"
+#>   ..- attr(*, "format.spss")= chr "F12.1"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:3] 1 2 3
+#>   .. ..- attr(*, "names")= chr [1:3] "no" "somewhat" "yes"
+#>  $ moa1#2_10: num  3 1 3 1 1 1 2 2 1 2 ...
+#>   ..- attr(*, "label")= chr "ach_committedlongterm"
+#>   ..- attr(*, "format.spss")= chr "F12.1"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:3] 1 2 3
+#>   .. ..- attr(*, "names")= chr [1:3] "no" "somewhat" "achieved"
+#>  $ moa2#1_1 : num  4 4 3 4 4 3 1 4 4 4 ...
+#>   ..- attr(*, "label")= chr "imp_indepedentdecisions"
+#>   ..- attr(*, "format.spss")= chr "F12.0"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:2] 1 4
+#>   .. ..- attr(*, "names")= chr [1:2] "not important" "important"
+#>  $ moa2#1_2 : num  4 4 4 4 4 3 1 3 4 4 ...
+#>   ..- attr(*, "label")= chr "imp_supportfamily"
+#>   ..- attr(*, "format.spss")= chr "F12.0"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:2] 1 4
+#>   .. ..- attr(*, "names")= chr [1:2] "not important" "important"
+#>  $ moa2#1_3 : num  3 3 4 3 4 1 1 2 4 4 ...
+#>   ..- attr(*, "label")= chr "imp_carechildren"
+#>   ..- attr(*, "format.spss")= chr "F12.0"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:2] 1 4
+#>   .. ..- attr(*, "names")= chr [1:2] "not important" "important"
+#>  $ moa2#1_4 : num  4 4 4 4 3 4 1 4 3 4 ...
+#>   ..- attr(*, "label")= chr "imp_acceptresponsibility"
+#>   ..- attr(*, "format.spss")= chr "F12.0"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:2] 1 4
+#>   .. ..- attr(*, "names")= chr [1:2] "not important" "important"
+#>  $ moa2#1_5 : num  4 3 4 3 3 4 1 3 4 2 ...
+#>   ..- attr(*, "label")= chr "imp_employfulltime"
+#>   ..- attr(*, "format.spss")= chr "F12.0"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:2] 1 4
+#>   .. ..- attr(*, "names")= chr [1:2] "not important" "important"
+#>  $ moa2#1_6 : num  4 4 4 4 4 4 1 2 3 4 ...
+#>   ..- attr(*, "label")= chr "imp_avoiddrunkdriving"
+#>   ..- attr(*, "format.spss")= chr "F12.0"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:2] 1 4
+#>   .. ..- attr(*, "names")= chr [1:2] "not important" "important"
+#>  $ moa2#1_7 : num  3 4 4 3 2 2 1 3 3 4 ...
+#>   ..- attr(*, "label")= chr "imp_parentasequal"
+#>   ..- attr(*, "format.spss")= chr "F12.0"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:2] 1 4
+#>   .. ..- attr(*, "names")= chr [1:2] "not important" "important"
+#>  $ moa2#1_8 : num  4 3 4 4 4 4 1 4 4 4 ...
+#>   ..- attr(*, "label")= chr "imp_emotionalcontrol"
+#>   ..- attr(*, "format.spss")= chr "F12.0"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:2] 1 4
+#>   .. ..- attr(*, "names")= chr [1:2] "not important" "important"
+#>  $ moa2#1_9 : num  3 3 4 4 3 4 1 3 4 2 ...
+#>   ..- attr(*, "label")= chr "imp_considerothers"
+#>   ..- attr(*, "format.spss")= chr "F12.0"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:2] 1 4
+#>   .. ..- attr(*, "names")= chr [1:2] "not important" "important"
+#>  $ moa2#1_10: num  2 4 2 3 4 1 1 4 4 1 ...
+#>   ..- attr(*, "label")= chr "imp_supportparentsfinance"
+#>   ..- attr(*, "format.spss")= chr "F12.0"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:2] 1 4
+#>   .. ..- attr(*, "names")= chr [1:2] "not important" "important"
+#>  $ moa2#2_1 : num  3 3 2 3 2 3 2 2 3 3 ...
+#>   ..- attr(*, "label")= chr "achi_independentdecisions"
+#>   ..- attr(*, "format.spss")= chr "F12.1"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:3] 1 2 3
+#>   .. ..- attr(*, "names")= chr [1:3] "no" "somewhat" "yes"
+#>  $ moa2#2_2 : num  2 1 2 2 1 1 2 1 1 2 ...
+#>   ..- attr(*, "label")= chr "ach_supportfamily"
+#>   ..- attr(*, "format.spss")= chr "F12.1"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:3] 1 2 3
+#>   .. ..- attr(*, "names")= chr [1:3] "no" "somewhat" "yes"
+#>  $ moa2#2_3 : num  3 1 3 2 2 1 2 1 3 3 ...
+#>   ..- attr(*, "label")= chr "ach_carechildren"
+#>   ..- attr(*, "format.spss")= chr "F12.1"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:3] 1 2 3
+#>   .. ..- attr(*, "names")= chr [1:3] "no" "somewhat" "yes"
+#>  $ moa2#2_4 : num  2 3 2 3 3 3 2 2 2 3 ...
+#>   ..- attr(*, "label")= chr "ach_acceptresponsibility"
+#>   ..- attr(*, "format.spss")= chr "F12.1"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:3] 1 2 3
+#>   .. ..- attr(*, "names")= chr [1:3] "no" "somewhat" "yes"
+#>  $ moa2#2_5 : num  3 1 1 2 2 3 2 1 3 3 ...
+#>   ..- attr(*, "label")= chr "ach_employfulltime"
+#>   ..- attr(*, "format.spss")= chr "F12.1"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:3] 1 2 3
+#>   .. ..- attr(*, "names")= chr [1:3] "no" "somewhat" "yes"
+#>  $ moa2#2_6 : num  3 3 3 3 2 3 2 3 2 3 ...
+#>   ..- attr(*, "label")= chr "ach_avoiddrunkdriving"
+#>   ..- attr(*, "format.spss")= chr "F12.1"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:3] 1 2 3
+#>   .. ..- attr(*, "names")= chr [1:3] "no" "somewhat" "yes"
+#>  $ moa2#2_7 : num  3 3 3 2 2 1 2 1 3 2 ...
+#>   ..- attr(*, "label")= chr "ach_parentasequal"
+#>   ..- attr(*, "format.spss")= chr "F12.1"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:3] 1 2 3
+#>   .. ..- attr(*, "names")= chr [1:3] "no" "somewhat" "yes"
+#>  $ moa2#2_8 : num  2 3 2 3 2 1 2 2 3 2 ...
+#>   ..- attr(*, "label")= chr "ach_emotionalcontrol"
+#>   ..- attr(*, "format.spss")= chr "F12.1"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:3] 1 2 3
+#>   .. ..- attr(*, "names")= chr [1:3] "no" "somewhat" "yes"
+#>  $ moa2#2_9 : num  2 3 2 3 3 3 2 2 3 2 ...
+#>   ..- attr(*, "label")= chr "ach_considerothers"
+#>   ..- attr(*, "format.spss")= chr "F12.1"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:3] 1 2 3
+#>   .. ..- attr(*, "names")= chr [1:3] "no" "somewhat" "yes"
+#>  $ moa2#2_10: num  1 1 1 2 1 1 2 1 3 3 ...
+#>   ..- attr(*, "label")= chr "ach_supportparentsfinances"
+#>   ..- attr(*, "format.spss")= chr "F12.1"
+#>   ..- attr(*, "display_width")= int 12
+#>   ..- attr(*, "labels")= Named num [1:3] 1 2 3
+#>   .. ..- attr(*, "names")= chr [1:3] "no" "somewhat" "yes"
+
+
+

Date Published: +

+

2018-01-09

+
+
+

Dataset Citation: +

+

Grahe, J. E., Chalk, H. M., Cramblet Alvarez, L. D., Faas, C., +Hermann, A., McFall, J. P., & Molyneux, K. (2018, January 10). +EAMMi2 Public Data. Retrieved from: https://osf.io/x7mp2/.

+
+
+

Keywords: +

+

self report, emerging adulthood

+
+
+

Use License: +

+

CC-By Attribution 4.0 International

+
+
+

Geographic Description - City/State/Country of Participants: +

+

Mostly United States but any English speaker could complete.

+
+
+

Column Metadata: +

+
+EAMMi2metadata <- import("data/mcfall_metadata.csv")
+flextable(EAMMi2metadata) %>% autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

Variable

Label

moa1#1_1

imp_financialindependence

moa1#1_2

imp_nolongerhom

moa1#1_3

imp_finishededucation

moa1#1_4

imp_married

moa1#1_5

imp_havechild

moa1#1_6

imp_settledcareer

moa1#1_7

imp_avoiddrunk

moa1#1_8

imp_avoiddrugs

moa1#1_9

imp_usecontraception

moa1#1_10

imp_committedlongterm

moa1#2_1

ach_financialindependence

moa1#2_2

ach_nolongerhome

moa1#2_3

ach_finishededucation

moa1#2_4

ach_married

moa1#2_5

ach_havechild

moa1#2_6

ach_settledcareer

moa1#2_7

ach_avoiddrunk

moa1#2_8

ach_avoiddrugs

moa1#2_9

ach_usecontraception

moa1#2_10

ach_committedlongterm

moa2#1_1

imp_indepedentdecisions

moa2#1_2

imp_supportfamily

moa2#1_3

imp_carechildren

moa2#1_4

imp_acceptresponsibility

moa2#1_5

imp_employfulltime

moa2#1_6

imp_avoiddrunkdriving

moa2#1_7

imp_parentasequal

moa2#1_8

imp_emotionalcontrol

moa2#1_9

imp_considerothers

moa2#1_10

imp_supportparentsfinance

moa2#2_1

achi_independentdecisions

moa2#2_2

ach_supportfamily

moa2#2_3

ach_carechildren

moa2#2_4

ach_acceptresponsibility

moa2#2_5

ach_employfulltime

moa2#2_6

ach_avoiddrunkdriving

moa2#2_7

ach_parentasequal

moa2#2_8

ach_emotionalcontrol

moa2#2_9

ach_considerothers

moa2#2_10

ach_supportparentsfinances

IDEA_1

IDEA-manypossibility

IDEA_2

IDEA-exploration

IDEA_3

IDEA-stressed

IDEA_4

IDEA-highpressure

IDEA_5

IDEA-definingself

IDEA_6

IDEA-beliefsvalues

IDEA_7

IDEA-someways

IDEA_8

IDEA-graduallyadult

swb_1

SWB-ideal

swb_2

SWB-excellent

swb_3

SWB-satisfied

swb_4

SWB-important

swb_5

SWB-changenothing

swb_6

SWB-highselfesteem

mindful_1

MIND-emotnotconscious

mindful_2

MIND-breakspill

mindful_3

MIND-difficultfocus

mindful_4

MIND-walknoattention

mindful_5

MIND-notnoticetension

mindful_6

MIND-forgetnames

mindful_7

MIND-runautomatic

mindful_8

MIND-rushactivities

mindful_9

MIND-goalfocus

mindful_10

MIND-jobautomatically

mindful_11

MIND-listensametime

mindful_12

MIND-driveautomatic

mindful_13

MIND-preoccupied

mindful_14

MIND-withoutpayattention

mindful_15

MIND-snackunaware

belong_1

Belong_nobother

belong_2

Belong_avoidrejection

belong_3

Belong_seldomworry

belong_4

Belong_needpeople

belong_5

Belong_othersacceptme

belong_6

Belong_notalone

belong_7

Belong_OKalone

belong_8

Belong_strongNEED

belong_9

Belong_bothernotinplans

belong_10

Belong_feelingseasilyhurt

belnow

BELONG-feelIbelong

efficacy_1

EFF-solvetryhard

efficacy_2

EFF-getwhatwant

efficacy_3

EFF-stick2goals

efficacy_4

EFF-dealunexpected

efficacy_5

EFF-resourceful

efficacy_6

EFF-solvenecesseffort

efficacy_7

EFF-remaincalm

efficacy_8

EFF-findseveralsolutions

efficacy_9

EFF-thinkofsolution

efficacy_10

EFF-whatevercomesmyway

support_1

SUP-specialforneed

support_2

SUP-specialjoysorry.

support_3

SUP-familyhelp

support_4

SUP-familyemotionalhelp

support_5

SUP-specialcomfort

support_6

SUP-friendshelp

support_7

SUP-countonfriends

support_8

SUP-talkfamily

support_9

SUP-friendsjoysorrow

support_10

SUP-specialcaresfeelings

support_11

SUP-familyhelpdecisions

support_12

SUP-friendstalkproblems

SocMedia_1

SocMed-avoiddrifting

SocMedia_2

SocMed-friendsplanstonight

SocMedia_3

SocMed-friendsintouch

SocMedia_4

SocMed-friendsupto

SocMedia_5

SocMed-Reconnectwithpeople

SocMedia_6

SocMed-Findoutmore

SocMedia_7

SocMed-someonetoknowbetter

SocMedia_8

SocMed-makenewfriends

SocMedia_9

SocMed-getintouch

SocMedia_10

SocMed-getinformation

SocMedia_11

SocMed-shareinformation

usdream_1

AmDreamImport

usdream_2

AmDreamAchieve

usdream_3

attentionchechshould be1

transgres_1

trangress-lietoyou

transgres_2

transgress-rumors

transgres_3

transgress-goteven

transgres_4

transgress-degraded

NPI1

NPI1

NPI2

NPI2

NPI3

NPI3

NPI4

NPI4

NPI5

NPI5

NPI6

NPI6

NPI7

NPI7

NPI8

NPI8

NPI9

NPI9

NPI10

NPI10

NPI11

NPI11

NPI12

NPI12

NPI13

NPI13

exploit_1

EXP-benefitfromothers

exploit_2

EXP-profitfromothers

exploit_3

EXP-usingothers

POQ1

DISID-disabilityinterferes

POQ2

DISID-dontthinkdisabled

POQ3

DISID-lackconfidence

POQ4

DISID-proudtobedisabled

POQ5

DISID-ashamed

POQ6

DISID-notreducedenjoy

POQ7

DISID-limitedfriendships

POQ8

DISID-sourcestrength

POQ9

DISID-accomplishmore

POQ10

DISID-notaproblem

POQ11

DISID-normallife

POQ12

DISID-betterperson

POQ13

DISID-importantpart

POQ14

DISID-proudofdisability

POQ15

DISID-disabilityenriches

physSx_1

Phys_stomach

physSx_2

Phys-back

physSx_3

Phys-appendages

physSx_4

Phys-headaches

physSx_5

Phys-chest

physSx_6

Phys-dizziness

physSx_7

Phys-fainting

physSx_8

Phys-heartpound

physSx_9

Phys-shortness

physSx_10

Phys-constipation

physSx_11

Phys-nausea

physSx_12

Phys-tired

physSx_13

Phys-troublesleeping

stress_1

stress-beenupset

stress_2

stress-unablecontrol

stress_3

stress-nervous

stress_4

stress-confident

stress_5

stress-goingmyway

stress_6

stress-couldnotcope

stress_7

stress-controlirritations

stress_8

stress-ontopofthings

stress_9

stress-beenangered

stress_10

stress-feltdifficulties

Variables in the working file

+
+
+
+EAMMi2 <- EAMMi2[complete.cases(EAMMi2),]
+EAMMi2long <- EAMMi2 %>% pivot_longer(cols = everything()) %>% 
+  dplyr::rename(item = name, score = value) %>% 
+  group_by(item) %>% 
+  sample_n(size = 50)
+
+flextable(head(EAMMi2long)) %>% autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

item

score

moa1#1_1

4

moa1#1_1

3

moa1#1_1

4

moa1#1_1

4

moa1#1_1

4

moa1#1_1

3

+
+
+
+

AIPE Analysis: +

+
+

Stopping Rule +

+

What the usual standard error for the data that could be considered +for our stopping rule?

+
+SE <- tapply(EAMMi2long$score, EAMMi2long$item, function (x) { sd(x)/sqrt(length(x)) })
+min(SE)
+#> [1] 0.04956958
+quantile(SE, probs = .4)
+#>        40% 
+#> 0.09805288
+max(SE)
+#> [1] 0.1781767
+
+cutoff <- quantile(SE, probs = .4)
+
+# we can also use semanticprimer's function
+cutoff_score <- calculate_cutoff(population = EAMMi2long,
+                                 grouping_items = "item",
+                                 score = "score",
+                                 minimum = min(EAMMi2long$score),
+                                 maximum = max(EAMMi2long$score))
+cutoff_score$cutoff
+#>        40% 
+#> 0.09805288
+

The items have a range of 0.0495696 to 0.1781767. We could use the +40% decile SE = 0.0980529 as our critical value for our stopping rule +given the manuscript results. We could also have a set SE to a specific +item if we do not believe we have representative pilot data in this +example. You should also consider the scale when estimating these values +(i.e., 1-7 scales will have smaller estimates than 1-100 scales).

+
+
+

Minimum Sample Size +

+

To estimate minimum sample size, we should figure out what number of +participants it would take to achieve 80% of the SEs for items below our +critical score of 0.0980529?

+
+# sequence of sample sizes to try
+nsim <- 10 # small for cran
+samplesize_values <- seq(20, 200, 5)
+
+# create a blank table for us to save the values in 
+
+sim_table <- matrix(NA, 
+                    nrow = length(samplesize_values)*nsim, 
+                    ncol = length(unique(EAMMi2long$item)))
+
+# make it a data frame
+sim_table <- as.data.frame(sim_table)
+
+# add a place for sample size values 
+sim_table$sample_size <- NA
+
+iterate <- 1
+
+for (p in 1:nsim){
+  # loop over sample sizes
+  for (i in 1:length(samplesize_values)){
+      
+    # temp dataframe that samples and summarizes
+    temp <- EAMMi2long %>% 
+      group_by(item) %>% 
+      sample_n(samplesize_values[i], replace = T) %>% 
+      summarize(se = sd(score)/sqrt(length(score))) 
+    
+    colnames(sim_table)[1:length(unique(EAMMi2long$item))] <- temp$item
+    sim_table[iterate, 1:length(unique(EAMMi2long$item))] <- temp$se
+    sim_table[iterate, "sample_size"] <- samplesize_values[i]
+    sim_table[iterate, "nsim"] <- p
+    
+    iterate <- iterate + 1
+  }
+}
+
+final_sample <- 
+  sim_table %>% 
+  pivot_longer(cols = -c(sample_size, nsim)) %>% 
+  group_by(sample_size, nsim) %>% 
+  summarize(percent_below = sum(value <= cutoff)/length(unique(EAMMi2long$item))) %>% 
+  ungroup() %>% 
+  # then summarize all down averaging percents
+  dplyr::group_by(sample_size) %>% 
+  summarize(percent_below = mean(percent_below)) %>% 
+  dplyr::arrange(percent_below) %>% 
+  ungroup()
+#> `summarise()` has grouped output by 'sample_size'. You can override using the
+#> `.groups` argument.
+
+flextable(final_sample %>% head()) %>% autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

sample_size

percent_below

20

0.1125

25

0.1425

30

0.1950

35

0.2225

40

0.3050

45

0.3475

+
+
+final_table <- calculate_correction(
+  proportion_summary = final_sample,
+  pilot_sample_size = EAMMi2long %>% group_by(item) %>% 
+    summarize(sample_size = n()) %>% ungroup() %>% 
+    summarize(avg_sample = mean(sample_size)) %>% pull(avg_sample),
+  proportion_variability = cutoff_score$prop_var
+  )
+
+flextable(final_table) %>% 
+  autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

percent_below

sample_size

corrected_sample_size

81.00

100

79.10863

85.50

110

86.31167

90.25

125

96.91896

97.25

155

116.99286

+
+

Based on these simulations, we can decide our minimum sample size is +likely close to 79.

+
+
+

Maximum Sample Size +

+

In this example, we could set our maximum sample size for 90% power, +which would equate to 97 participants.

+
+
+

Final Sample Size +

+

In any estimate for sample size, you should also consider the +potential for missing data and/or unusable data due to any other +exclusion criteria in your study (i.e., attention checks, speeding, +getting the answer right, etc.). Another important note is that these +estimates are driven by the number of items. Fewer items would require +smaller sample sizes to achieve minimum power. Note: Several redundant +(e.g., reverse coded items) and/or not useful variables (various checks) +were omitted.

+
+
+
+
+ + + + +
+ + + + + + + diff --git a/docs/articles/mcfall_vignette_files/tabwid-1.1.3/tabwid.css b/docs/articles/mcfall_vignette_files/tabwid-1.1.3/tabwid.css new file mode 100644 index 0000000..5e31a86 --- /dev/null +++ b/docs/articles/mcfall_vignette_files/tabwid-1.1.3/tabwid.css @@ -0,0 +1,42 @@ +.tabwid { + font-size: initial; + padding-bottom: 1em; +} + +.tabwid table{ + border-spacing:0px !important; + border-collapse:collapse; + line-height:1; + margin-left:auto; + margin-right:auto; + border-width: 0; + border-color: transparent; + caption-side: top; +} +.tabwid-caption-bottom table{ + caption-side: bottom; +} +.tabwid_left table{ + margin-left:0; +} +.tabwid_right table{ + margin-right:0; +} +.tabwid td, .tabwid th { + padding: 0; +} +.tabwid a { + text-decoration: none; +} +.tabwid thead { + background-color: transparent; +} +.tabwid tfoot { + background-color: transparent; +} +.tabwid table tr { +background-color: transparent; +} +.katex-display { + margin: 0 0 !important; +} diff --git a/docs/articles/mcfall_vignette_files/tabwid-1.1.3/tabwid.js b/docs/articles/mcfall_vignette_files/tabwid-1.1.3/tabwid.js new file mode 100644 index 0000000..47070f7 --- /dev/null +++ b/docs/articles/mcfall_vignette_files/tabwid-1.1.3/tabwid.js @@ -0,0 +1,20 @@ +document.addEventListener("DOMContentLoaded", function(event) { + var els = document.querySelectorAll(".tabwid"); + var tabwid_link = document.querySelector('link[href*="tabwid.css"]') + if (tabwid_link === null) { + const tabwid_styles = document.evaluate("//style[contains(., 'tabwid')]", document, null, XPathResult.ANY_TYPE, null ); + tabwid_link = tabwid_styles.iterateNext(); + } + + Array.prototype.forEach.call(els, function(template) { + const dest = document.createElement("div"); + template.parentNode.insertBefore(dest, template.nextSibling) + dest.setAttribute("class", "flextable-shadow-host"); + const fantome = dest.attachShadow({mode: 'open'}); + fantome.appendChild(template); + if (tabwid_link !== null) { + fantome.appendChild(tabwid_link.cloneNode(true)); + } + }); +}); + diff --git a/docs/articles/moat_vignette.html b/docs/articles/moat_vignette.html new file mode 100644 index 0000000..58077d6 --- /dev/null +++ b/docs/articles/moat_vignette.html @@ -0,0 +1,540 @@ + + + + + + + + +Power and Sample Size Simulation: Seeing is Believing • semanticprimeR + + + + + + + + + + Skip to contents + + +
+ + + + +
+
+

Power and Sample Size Simulation: Seeing is Believing

+

Jason +Geller

+ +

2023-12-27

+ + +
moat_vignette.Rmd
+
+ + + +
+

Vignette Setup: +

+
+knitr::opts_chunk$set(echo = TRUE)
+
+# Libraries necessary for this vignette
+library(rio)
+library(flextable)
+library(dplyr)
+#> 
+#> Attaching package: 'dplyr'
+#> The following objects are masked from 'package:stats':
+#> 
+#>     filter, lag
+#> The following objects are masked from 'package:base':
+#> 
+#>     intersect, setdiff, setequal, union
+library(tidyr)
+library(semanticprimeR)
+set.seed(92747)
+
+# Function for simulation
+item_power <- function(data, # name of data frame
+                       dv_col, # name of DV column as a character
+                       item_col, # number of items column as a character
+                       nsim = 10, # small for cran
+                       sample_start = 20, 
+                       sample_stop = 200, 
+                       sample_increase = 5,
+                       decile = .5){
+  
+  DF <- cbind.data.frame(
+    dv = data[ , dv_col],
+    items = data[ , item_col]
+  )
+  
+  # just in case
+  colnames(DF) <- c("dv", "items")
+  
+  # figure out the "sufficiently narrow" ci value
+  SE <- tapply(DF$dv, DF$items, function (x) { sd(x)/sqrt(length(x)) })
+  cutoff <- quantile(SE, probs = decile)
+  
+  # sequence of sample sizes to try
+  samplesize_values <- seq(sample_start, sample_stop, sample_increase)
+
+  # create a blank table for us to save the values in 
+  sim_table <- matrix(NA, 
+                      nrow = length(samplesize_values), 
+                      ncol = length(unique(DF$items)))
+
+  # make it a data frame
+  sim_table <- as.data.frame(sim_table)
+
+  # add a place for sample size values 
+  sim_table$sample_size <- NA
+
+  iterate <- 1
+  for (p in 1:nsim){
+    # loop over sample sizes
+    for (i in 1:length(samplesize_values)){
+        
+      # temp that samples and summarizes
+      temp <- DF %>% 
+        group_by(items) %>% 
+        sample_n(samplesize_values[i], replace = T) %>% 
+        summarize(se = sd(dv)/sqrt(length(dv)))
+      
+      # dv on items
+      colnames(sim_table)[1:length(unique(DF$items))] <- temp$items
+      sim_table[iterate, 1:length(unique(DF$items))] <- temp$se
+      sim_table[iterate, "sample_size"] <- samplesize_values[i]
+      sim_table[iterate, "nsim"] <- p
+      
+    }
+  }
+
+  # figure out cut off
+  final_sample <- sim_table %>% 
+    pivot_longer(cols = -c(sample_size, nsim)) %>% 
+    dplyr::rename(item = name, se = value) %>% 
+    group_by(sample_size, nsim) %>% 
+    summarize(percent_below = sum(se <= cutoff)/length(unique(DF$items))) %>% 
+    ungroup() %>% 
+    # then summarize all down averaging percents
+    dplyr::group_by(sample_size) %>% 
+    summarize(percent_below = mean(percent_below)) %>% 
+    dplyr::arrange(percent_below) %>% 
+    ungroup()
+  
+  return(list(
+    SE = SE, 
+    cutoff = cutoff, 
+    DF = DF, 
+    sim_table = sim_table, 
+    final_sample = final_sample
+  ))
+
+}
+
+
+

Project/Data Title: +

+

Seeing Is Believing: How Media Type Effects Truth Judgements

+

Data provided by: Gianni Ribeiro

+
+
+

Project/Data Description: +

+

People have been duly concerned about how fake news influences the +minds of the populous since the rise of propaganda in World War One +(Lasswell, 1927). Experts are increasingly worried about the effects of +false information spreading over the medium of video. Members of the +deep trust alliance, a global network of scholars researching deepfakes +and doctored videos, state that ‘a fundamental erosion of trust is +already underway’ (Harrison, 2020). Newman et al. (2015) discovered that +the media type through which information is presented does indeed affect +how true the information feels. Newman speculated that this truthiness +effect could be because images provide participants with more +information than text alone, thus making the source feel more +informationally rich.

+

In this experiment, our aim is to test the generalizability of +Newman’s truthiness effect in two ways: first, to see if it extends to +other media types in addition to images, and second, to test if it +applies to other domains. In this study, we will present individuals +with true and false claims presented through three different media +types: (1) text, (2) text alongside a photo, and (3) text alongside a +video. This is a direct replication of Newman’s experiment, just with +the addition of the video condition. Similarly, participants will also +be asked to make truth judgements about trivial claims and claims about +COVID-19, to see if the truthiness effect extends to other domains +besides trivia.

+

In this within-subjects design, participants will be presented with +true and false claims about trivia and COVID-19 in counterbalanced +order. These claims will be randomly assigned to appear either as text +alone, text alongside an image, or text alongside a video. Participants +will be asked to rate how true they believe each claim is.

+
+
+

Methods Description: +

+

Participants were largely sourced from the first-year participant +pool at The University of Queensland. Participation was completely +voluntary, and participants can choose to withdraw at any time.

+

Thirty matched trivia claims were generated directly from Newman’s +materials. These claims were selected and a true and false version of +each claim was created. Newman’s original claims are available at the +following link: https://data.mendeley.com/datasets/r68dcdjrpc/1

+

The second set of materials comprising of matched true and false +claims was generated using information resources from the World Health +Organisation, and various conspiracy websites. These claims were then +fact-checked by Kirsty Short, an epidemiologist and senior lecturer in +the School of Chemistry and Molecular Sciences at The University of +Queensland.

+

The claims were also pilot tested to ensure that none of them +performed at floor or ceiling. This pilot test consisted of 56 +participants and subsequently four claims were dropped. The data from +this pilot test was also used to accurately perform a power analysis. +After generating the means of the pilot test, we found that to acquire a +power of 0.8 or greater, there must be a mean difference of 0.4 between +each media type. This mean difference is quite conservative, since we +plan to measure truth ratings on a six-point scale and is easily +achievable with 100 participants.

+

The videos were largely sourced from the stock image website Envato +Elements and Screenflow’s Royalty Free Stock Media Library.

+
+
+

Data Location: +

+

Data can be found here: https://osf.io/zu9pg/

+
+DF <- import("data/moat_data.csv.zip") 
+  
+str(DF)
+#> 'data.frame':    5040 obs. of  11 variables:
+#>  $ id            : int  1 1 1 1 1 1 1 1 1 1 ...
+#>  $ domain        : chr  "covid" "covid" "covid" "covid" ...
+#>  $ gender        : chr  "Female" "Female" "Female" "Female" ...
+#>  $ age           : int  22 22 22 22 22 22 22 22 22 22 ...
+#>  $ filename      : chr  "1_kaitlin_exp_v2b_97832952686.txt" "1_kaitlin_exp_v2b_97832952686.txt" "1_kaitlin_exp_v2b_97832952686.txt" "1_kaitlin_exp_v2b_97832952686.txt" ...
+#>  $ medium        : chr  "claim" "claim" "claim" "claim" ...
+#>  $ question_type : chr  "drinking" "herd" "hydroxychloroquine" "steam" ...
+#>  $ truth         : logi  TRUE TRUE TRUE TRUE TRUE FALSE ...
+#>  $ claim         : chr  "COVID-19 cannot be contracted through drinking water." "Herd immunity against COVID-19 cannot be achieved by letting the virus spread through the population." "Studies show hydroxychloroquine does not have clinical benefits in treating COVID-19." "Steam inhalation cannot help cure COVID-19." ...
+#>  $ filename_other: chr  NA NA NA NA ...
+#>  $ rating        : int  1 5 6 6 6 1 1 1 5 1 ...
+
+
+

Date Published: +

+

No official publication, see citation below.

+
+
+

Dataset Citation: +

+

Moat, K., Tangen, J., & Newman, E. (2021). Seeing Is Believing: +How Media Type Effects Truth Judgements.

+
+
+

Keywords: +

+

covid, trivia games, claims, interpretation

+
+
+

Use License: +

+

Open access with reference to original paper +(Attribution-NonCommercial-ShareAlike CC BY-NC-SA)

+
+
+

Geographic Description - City/State/Country of Participants: +

+

Brisbane, Queensland, Australia

+
+
+

Column Metadata: +

+
+metadata <- tibble::tribble(
+             ~Variable.Name,                                                                                                       ~Variable.Description, ~`Type.(numeric,.character,.logical,.etc.)`,
+                      "Id",                                                                                                            "Participant ID",                                   "numeric",
+                   "Domain",                                                    "Whether the trial is a claim about COVID ('covid') or TRIVIA ('trivia)",                                 "character",
+                   "Medium", "Whether the trial appears as text alone ('claim'), text alongside an image ('photo'), or text alongside a video ('video')",                                 "character",
+               "Trial_type",                                        "Whether the trial presents a claim that is TRUE ('target') or FALSE ('distractor')",                                 "character",
+                   "Rating",                           "Paritcipant’s truth rating of the claim ranging from 1 (definitely false) to 6 (definitely tue)",                                   "numeric"
+             )
+
+flextable(metadata) %>% autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

Variable.Name

Variable.Description

Type.(numeric,.character,.logical,.etc.)

Id

Participant ID

numeric

Domain

Whether the trial is a claim about COVID ('covid') or TRIVIA ('trivia)

character

Medium

Whether the trial appears as text alone ('claim'), text alongside an image ('photo'), or text alongside a video ('video')

character

Trial_type

Whether the trial presents a claim that is TRUE ('target') or FALSE ('distractor')

character

Rating

Paritcipant’s truth rating of the claim ranging from 1 (definitely false) to 6 (definitely tue)

numeric

+
+
+
+

AIPE Analysis: +

+
+# Function for simulation
+var1 <- item_power(data = DF, # name of data frame
+            dv_col = "rating", # name of DV column as a character
+            item_col = "question_type", # number of items column as a character
+            nsim = 10, 
+            sample_start = 20, 
+            sample_stop = 300, 
+            sample_increase = 5,
+            decile = .4)
+#> `summarise()` has grouped output by 'sample_size'. You can override using the
+#> `.groups` argument.
+
+

Stopping Rule +

+

What is the usual standard error for the data that could be +considered for our stopping rule?

+
+var1$SE
+#>             afghan        antibiotics           bacteria          blindness 
+#>          0.1733704          0.2192951          0.2550577          0.1787244 
+#>      breastfeeding           chemical           children            cocaine 
+#>          0.1726203          0.2000046          0.2224147          0.2427085 
+#>        colorvision               corn           couscous            curling 
+#>          0.1284245          0.1064393          0.1337200          0.1500109 
+#>         dartboards            denmark                dna           drinking 
+#>          0.1322563          0.1802086          0.2273651          0.1732374 
+#>            elderly            fishing             forest         foxhunting 
+#>          0.2576951          0.1464690          0.1349403          0.1446861 
+#>             grapes               herd                hiv         houseflies 
+#>          0.1573876          0.1877676          0.2135034          0.1907986 
+#> hydroxychloroquine        infertility          lawnbowls               lime 
+#>          0.1495606          0.2049964          0.1147161          0.1465564 
+#>            longbow           marathon          microwave         mintonette 
+#>          0.1667281          0.1392743          0.1959902          0.1066397 
+#>         mosquitoes          mountains          mouthwash               nile 
+#>          0.1894154          0.0912085          0.2245578          0.1532541 
+#>              otter             oxygen            oysters         penicillin 
+#>          0.1280050          0.2093482          0.1173648          0.1584095 
+#>             poland          prisoners               rate              rigor 
+#>          0.1326624          0.1970849          0.2147593          0.2238266 
+#>             saline              smell              snake       snowboarding 
+#>          0.2132273          0.2432145          0.1899915          0.1359677 
+#>              steam        temperature         triathalon              twice 
+#>          0.2243410          0.2215570          0.1851070          0.2292498 
+#>             urchin                 uv           vesuvius          vitamin-c 
+#>          0.1399591          0.2161739          0.1433344          0.2127463 
+#>          vitamin-d              water          waterfall               zulu 
+#>          0.2251918          0.1817230          0.1411920          0.1264954
+var1$cutoff
+#>       40% 
+#> 0.1580007
+
+cutoff <- var1$cutoff
+
+# we can also use semanticprimer's function
+cutoff_score <- calculate_cutoff(population = DF,
+                                 grouping_items = "question_type",
+                                 score = "rating",
+                                 minimum = min(DF$rating),
+                                 maximum = max(DF$rating))
+cutoff_score$cutoff
+#>       40% 
+#> 0.1580007
+

Using our 40% decile as a guide, we find that 0.158 is our target +standard error for an accurately measured item.

+
+
+

Minimum Sample Size +

+

To estimate minimum sample size, we should figure out what number of +participants it would take to achieve 80%, 85%, 90%, and 95% of the SEs +for items below our critical score of 0.158?

+

How large does the sample have to be for 80% of the items to be below +our stopping SE rule?

+
+flextable(var1$final_sample %>% head()) %>% 
+  autofit()
+
+ + + + + + + + + + + + + + + + +

sample_size

percent_below

300

1

+
+
+
+final_table <- calculate_correction(
+  proportion_summary = var1$final_sample,
+  pilot_sample_size = DF %>% group_by(question_type) %>% 
+    summarize(sample_size = n()) %>% ungroup() %>% 
+    summarize(avg_sample = mean(sample_size)) %>% pull(avg_sample),
+  proportion_variability = cutoff_score$prop_var
+  )
+
+flextable(final_table) %>% 
+  autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

percent_below

sample_size

corrected_sample_size

100

300

173.0834

100

300

173.0834

100

300

173.0834

100

300

173.0834

+
+

Based on these simulations, we can decide our minimum sample size is +likely close to 173.

+
+
+

Maximum Sample Size +

+

In this example, we could set our maximum sample size for 90% of +items, which would equate to 173 participants.

+
+
+

Final Sample Size +

+

You should also consider any potential for missing data and/or +unusable data given the requirements for your study. Given that +participants are likely to see all items in this study, we could use the +minimum, stopping rule, and maximum defined above.

+
+
+
+
+ + + + +
+ + + + + + + diff --git a/docs/articles/moat_vignette_files/tabwid-1.1.3/tabwid.css b/docs/articles/moat_vignette_files/tabwid-1.1.3/tabwid.css new file mode 100644 index 0000000..5e31a86 --- /dev/null +++ b/docs/articles/moat_vignette_files/tabwid-1.1.3/tabwid.css @@ -0,0 +1,42 @@ +.tabwid { + font-size: initial; + padding-bottom: 1em; +} + +.tabwid table{ + border-spacing:0px !important; + border-collapse:collapse; + line-height:1; + margin-left:auto; + margin-right:auto; + border-width: 0; + border-color: transparent; + caption-side: top; +} +.tabwid-caption-bottom table{ + caption-side: bottom; +} +.tabwid_left table{ + margin-left:0; +} +.tabwid_right table{ + margin-right:0; +} +.tabwid td, .tabwid th { + padding: 0; +} +.tabwid a { + text-decoration: none; +} +.tabwid thead { + background-color: transparent; +} +.tabwid tfoot { + background-color: transparent; +} +.tabwid table tr { +background-color: transparent; +} +.katex-display { + margin: 0 0 !important; +} diff --git a/docs/articles/moat_vignette_files/tabwid-1.1.3/tabwid.js b/docs/articles/moat_vignette_files/tabwid-1.1.3/tabwid.js new file mode 100644 index 0000000..47070f7 --- /dev/null +++ b/docs/articles/moat_vignette_files/tabwid-1.1.3/tabwid.js @@ -0,0 +1,20 @@ +document.addEventListener("DOMContentLoaded", function(event) { + var els = document.querySelectorAll(".tabwid"); + var tabwid_link = document.querySelector('link[href*="tabwid.css"]') + if (tabwid_link === null) { + const tabwid_styles = document.evaluate("//style[contains(., 'tabwid')]", document, null, XPathResult.ANY_TYPE, null ); + tabwid_link = tabwid_styles.iterateNext(); + } + + Array.prototype.forEach.call(els, function(template) { + const dest = document.createElement("div"); + template.parentNode.insertBefore(dest, template.nextSibling) + dest.setAttribute("class", "flextable-shadow-host"); + const fantome = dest.attachShadow({mode: 'open'}); + fantome.appendChild(template); + if (tabwid_link !== null) { + fantome.appendChild(tabwid_link.cloneNode(true)); + } + }); +}); + diff --git a/docs/articles/montefinese_vignette.html b/docs/articles/montefinese_vignette.html new file mode 100644 index 0000000..6aca325 --- /dev/null +++ b/docs/articles/montefinese_vignette.html @@ -0,0 +1,829 @@ + + + + + + + + +Power and Sample Size Simulatio: Online search trends and word-related emotional response during COVID-19 lockdown in Italy • semanticprimeR + + + + + + + + + + Skip to contents + + +
+ + + + +
+
+

Power and Sample Size Simulatio: Online search trends and word-related emotional response during COVID-19 lockdown in Italy

+

Mahmoud +M.Elsherif

+ +

2023-12-27

+ + +
montefinese_vignette.Rmd
+
+ + + +
+

Vignette Setup: +

+
+
+

Project/Data Title: +

+

Online search trends and word-related emotional response during +COVID-19 lockdown in Italy

+

Data provided by: Maria Montefinese

+
+
+

Project/Data Description: +

+

The strong and long lockdown adopted by the Italian government to +limit the spread of the COVID-19 represents the first threat-related +mass isolation in history that scientists can study in depth to +understand the emotional response of individuals to a pandemic. +Perception of a pandemic threat through invasive media communication, +such as that related to COVID-19, can induce fear-related emotions (Van +Bavel et al., 2020). The dimension theory of emotions (Osgood & +Suci, 1955) assumes that emotive space is defined along three +dimensions: valence (indicating the way an individual judges a stimulus; +from unpleasant to pleasant), arousal (indicating the degree of +activation an individual feels towards a stimulus; from calm to excited) +and dominance (indicating the degree of control an individual feels over +a given stimulus; from out of control to in control). Fear is +characterized as a negatively valenced emotion, accompanied by a high +level of arousal (Witte, 1992; Witte, 1998) and a low dominance +(Stevenson, Mikel & James, 2007). This is generally in line with +previous results showing that participants judged stimuli related to the +most feared medical conditions as the most negative, the most +anxiety-provoking, and the least controllable (Warriner, Kuperman & +Brysbaert, 2013). Fear is also characterized by extreme levels of +emotional avoidance of specific stimuli (Perin et al., 2015) and may be +considered a unidirectional precursor to psychopathological responses +within the current context (Ahorsu et al., 2020). dealing with fear in a +pandemic situation could be easier for some people than others. Indeed, +individual differences have been associated with behavioral responses to +pandemic status (Carvalho Pianowski & Gonçalves, 2020).

+

To mitigate the effects of the COVID-19 on the mental health of +individuals, it is imperative to evaluate their emotional response to +this emergency. The internet searches are a direct tool to address this +problem. In fact, COVID-19 has been reported to affect the content that +people explore online (Effenberger et al., 2020), and online media and +platforms offer essential channels where people express their feelings +and emotions and seek health-related information (Kalichman et al., +2003; Reeves, 2001). In particular, Google Trends is an available data +source of real-time internet search patterns, which has been shown to be +a valid indicator of people’s desires and intentions (Payne, +Brown-Iannuzzi & Hannay, 2017; Pelham et al., 2018). Therefore, the +amount of searches related to COVID-19 on the internet revealed by +Google Trends are an indicator of how people feel about concepts related +to the COVID-19 pandemic. A change in online search trends reflects a +change in participants’ interests and attitudes towards a specific +topic. Based on the topic, the context (that is, the reasons for this +change), and this mutated interest per se, it is possible to predict +people’s behavior and affective response to the topic in question. In +this study, our aim was to understand how emotional reaction and online +search behavior have changed in response to the COVID-19 lockdown in the +Italian population.

+
+
+

Methods Description: +

+

Data were collected in the period from 4 May to 17 May 2020, the last +day of complete lockdown in Italy, from 71 native adult Italian speakers +(56 females and 13 males; mean age (SD) = 26.2 (7.9) years; mean +education (SD) = 15.3 (3.2) years). There were no other specific +eligibility criteria. An online survey was conducted using Google Forms +to collect affective ratings during the lockdown caused by the COVID-19 +epidemic in Italy. In particular, we asked participants to complete the +Positive and Negative Affect Schedule (PANAS, Terraciano, McCrae & +Costa, 2003) and Fear of COVID-19 Scale (FCV-19S, Ahorsu et al., 2020) +and judged valence, arousal, and dominance (on a 9-point self-assessment +manikin, Montefinese et al., 2014) of words related or unrelated to +COVID-19, as identified by Google search trends. The word stimuli +consisted of 3 groups of 20 words each. The first group (REL+) consisted +of the words showing the largest positive relation between their search +trends and the search trend for COVID-related terms. On the contrary, +the second group (REL-) consisted of the words showing the largest +negative relation between their search trends and the search trend for +COVID-related terms. In other words, the COVID-19 epidemic in Italy and +the consequent increase in interest in terms related to COVID was +related to a similar increase in interest for the REL+ words and a +decrease in interest for the REL- words. The third group (UNREL) +consisted of the words for which the search trend was unrelated to the +search trend for the COVID-related terms.

+
+
+

Data Location: +

+

https://osf.io/we9r4/

+
+DF <- import("data/montefinese_data.csv") 
+
+names(DF) <- make.names(names(DF),unique = TRUE)
+
+names(DF)[names(DF) == 'ITEM..ITA.'] <- "item"
+
+DF <- DF %>%
+  filter(StimType != "") %>% 
+  filter(Measure == "Valence") %>% # only look at valence score 
+  arrange(item) %>% #orders the rows of the data by the target_name column
+  group_by(item) %>% #group by the target name
+  transform(items = as.numeric(factor(item)))%>% #transform target name into a item
+  select(items, item, everything()
+         ) #select all variables from items and target_name 
+
+head(DF)
+#>   items     item ssID Gender Age Education Measure StimType Response
+#> 1     1 affogare    1      F  36        21 Valence    UNREL        2
+#> 2     1 affogare    2      M  40        21 Valence    UNREL        2
+#> 3     1 affogare    3      F  29        21 Valence    UNREL        1
+#> 4     1 affogare    4      M  39        13 Valence    UNREL        1
+#> 5     1 affogare    5      F  27        16 Valence    UNREL        1
+#> 6     1 affogare    6      M  33        18 Valence    UNREL        1
+
+
+

Date Published: +

+

2021-08-10

+
+
+

Dataset Citation: +

+

Montefinese M, Ambrosini E, Angrilli A. 2021. Online search trends +and word-related emotional response during COVID-19 lockdown in Italy: a +cross-sectional online study. PeerJ 9:e11858 https://doi.org/10.7717/peerj.11858

+
+
+

Keywords: +

+

Covid-19; Emotional response; Online search; Lockdown; Coping

+
+
+

Use License: +

+

CC-By Attribution 4.0 International

+
+
+

Geographic Description - City/State/Country of Participants: +

+

Italy

+
+
+

Column Metadata: +

+
+metadata <- import("data/montefinese_metadata.xlsx")
+
+flextable(metadata) %>% autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

Variable Name

Variable Description

Type (numeric, character, logical, etc.)

ssID

Participant code

Numeric

Gender

Participants’ gender

Character

Age

Participants’ age

Numeric

Education

Participants’ years of education

Numeric

Measure

Questionnaires and ratings (PANAS, COVID-19 fear, valence, arousal, dominance)

Character

ITEM (ITA)

Test items and word stimuli

Character

Stim Type

Word condition (REL+, REL-, UNREL)

Character

Response

Participants’ scores to the questionnaires and ratings

Numeric

+
+
+
+

AIPE Analysis: +

+

In this dataset, there are REL+ and REL- variables. In the REL+ +condition, the words show the largest positive relation between their +search trends and the search trend for the COVID-related terms. In the +REL- condition, the words showed the largest negative relation between +their search trends and the search trends for the COVID-related terms. +The third group (UNREL) consisted in the words for which the search +trend was unrelated to the search trend for the COVID-related terms.

+
+

Stopping Rule +

+

What the usual standard error for the data that could be considered +for our stopping rule using the 40% decile? Given potential differences +in conditions, we subset the data to each condition to estimate +separately.

+
+### create  subset for REL+
+DF_RELpos <- subset(DF, StimType == "REL+")
+
+### create  subset for REL-
+DF_RELneg <- subset(DF, StimType == "REL-")
+
+### create  subset for UNREL
+DF_UNREL <- subset(DF, StimType == "UNREL")
+
+
+# individual SEs for REL+ condition 
+cutoff_relpos <- calculate_cutoff(population = DF_RELpos,
+                                  grouping_items = "item", 
+                                  score = "Response", 
+                                  minimum = min(DF_RELpos$Response),
+                                  maximum = max(DF_RELpos$Response))
+
+SE1 <- tapply(DF_RELpos$Response, DF_RELpos$item, function (x) { sd(x)/sqrt(length(x)) })
+SE1
+#>      burro       casa cioccolato   computer     corona   famiglia     febbre 
+#>  0.1557687  0.1766870  0.1537913  0.1998951  0.2176631  0.1481984  0.1481984 
+#>     lavare    libertà      mondo     muffin    notizie      peste     salute 
+#>  0.1860313  0.1916883  0.2017999  0.1846399  0.1636991  0.1621336  0.1569829 
+#>    salvare       sole      tempo termometro      torta     vaiolo 
+#>  0.1431403  0.1483131  0.1952478  0.1441268  0.1393278  0.1585099
+cutoff_relpos$cutoff
+#>       40% 
+#> 0.1564972
+
+# individual SEs for REL- condition
+cutoff_relneg <- calculate_cutoff(population = DF_RELneg,
+                                  grouping_items = "item", 
+                                  score = "Response", 
+                                  minimum = min(DF_RELneg$Response),
+                                  maximum = max(DF_RELneg$Response))
+
+SE2 <- tapply(DF_RELneg$Response, DF_RELneg$item, function (x) { sd(x)/sqrt(length(x)) })
+SE2
+#>    autobus      costa    dormire     giacca      hotel   mangiare matrimonio 
+#> 0.17715152 0.18453238 0.16521553 0.15728951 0.17384120 0.14909443 0.20475544 
+#>     motore    palazzo  pantalone     piazza    profumo ristorante      sposa 
+#> 0.15085177 0.17073238 0.17481656 0.20640961 0.16138025 0.20118108 0.21208427 
+#>       tram     tumore       uomo    vacanza    viaggio  villaggio 
+#> 0.16872880 0.07001896 0.16715951 0.13096103 0.18557374 0.16663313
+cutoff_relneg$cutoff
+#>      40% 
+#> 0.166949
+
+# individual SEs for UNREL condition
+cutoff_unrel <- calculate_cutoff(population = DF_UNREL,
+                                  grouping_items = "item", 
+                                  score = "Response", 
+                                  minimum = min(DF_UNREL$Response),
+                                  maximum = max(DF_UNREL$Response))
+
+SE3 <- tapply(DF_UNREL$Response, DF_UNREL$item, function (x) { sd(x)/sqrt(length(x)) })
+SE3
+#>    affogare        baco     cannone      cappio   corridore  dipendente 
+#>   0.1312204   0.1622734   0.2131240   0.1750919   0.1781088   0.1796297 
+#>  disturbare      fetore  firmamento    funerale       gusto       ladro 
+#>   0.1535516   0.1507766   0.1973986   0.1121214   0.1526631   0.1473738 
+#> malevolenza     mestolo     nettare      oceano  offendersi     orgasmo 
+#>   0.1379994   0.1218824   0.1755445   0.1511708   0.1652155   0.1458857 
+#>  perfezione     tradire 
+#>   0.2210864   0.1158751
+cutoff_unrel$cutoff
+#>       40% 
+#> 0.1510131
+
+# sequence of sample sizes to try
+nsim <- 10 # small for cran
+samplesize_values <- seq(25, 300, 5)
+
+# create a blank table for us to save the values in positive ----
+sim_table <- matrix(NA, 
+                    nrow = length(samplesize_values)*nsim, 
+                    ncol = length(unique(DF_RELpos$item)))
+# make it a data frame
+sim_table <- as.data.frame(sim_table)
+
+# add a place for sample size values 
+sim_table$sample_size <- NA
+sim_table$var <- "Response"
+
+# make a second table for negative -----
+sim_table2 <- matrix(NA, 
+                    nrow = length(samplesize_values)*nsim, 
+                    ncol = length(unique(DF_RELneg$item)))
+
+# make it a data frame
+sim_table2 <- as.data.frame(sim_table2)
+
+# add a place for sample size values 
+sim_table2$sample_size <- NA
+sim_table2$var <- "Response"
+
+# make a second table for unrelated -----
+sim_table3 <- matrix(NA, 
+                    nrow = length(samplesize_values)*nsim, 
+                    ncol = length(unique(DF_UNREL$item)))
+
+# make it a data frame
+sim_table3 <- as.data.frame(sim_table3)
+
+# add a place for sample size values 
+sim_table3$sample_size <- NA
+sim_table3$var <- "Response"
+
+iterate <- 1
+
+for (p in 1:nsim){
+  
+  # loop over sample size
+  for (i in 1:length(samplesize_values)){
+      
+    # related positive temp variables ----
+    temp_RELpos <- DF_RELpos %>% 
+      dplyr::group_by(item) %>% 
+      dplyr::sample_n(samplesize_values[i], replace = T) %>% 
+      dplyr::summarize(se1 = sd(Response)/sqrt(length(Response))) 
+    
+    # put in table 
+    colnames(sim_table)[1:length(unique(DF_RELpos$item))] <- temp_RELpos$item
+    sim_table[iterate, 1:length(unique(DF_RELpos$item))] <- temp_RELpos$se1
+    sim_table[iterate, "sample_size"] <- samplesize_values[i]
+    sim_table[iterate, "nsim"] <- p
+    
+    # related negative temp variables ----
+    temp_RELneg <-DF_RELneg %>% 
+      dplyr::group_by(item) %>% 
+      dplyr::sample_n(samplesize_values[i], replace = T) %>% 
+      dplyr::summarize(se2 = sd(Response)/sqrt(length(Response))) 
+  
+    # put in table 
+    colnames(sim_table2)[1:length(unique(DF_RELneg$item))] <- temp_RELneg$item
+    sim_table2[iterate, 1:length(unique(DF_RELneg$item))] <- temp_RELneg$se2
+    sim_table2[iterate, "sample_size"] <- samplesize_values[i]
+    sim_table2[iterate, "nsim"] <- p
+    
+    # unrelated temp variables ----
+    temp_UNREL <-DF_UNREL %>% 
+      dplyr::group_by(item) %>% 
+      dplyr::sample_n(samplesize_values[i], replace = T) %>% 
+      dplyr::summarize(se3 = sd(Response)/sqrt(length(Response))) 
+  
+    # put in table 
+    colnames(sim_table3)[1:length(unique(DF_UNREL$item))] <- temp_UNREL$item
+    sim_table3[iterate, 1:length(unique(DF_UNREL$item))] <- temp_UNREL$se3
+    sim_table3[iterate, "sample_size"] <- samplesize_values[i]
+    sim_table3[iterate, "nsim"] <- p
+    
+    iterate <- iterate + 1
+    
+  }
+}
+
+
+

Minimum Sample Size +

+

Suggestions for REL+ Condition:

+
+# multiply by correction 
+cutoff <- quantile(SE1, probs = .4)
+
+final_sample <- 
+  sim_table %>%
+  pivot_longer(cols = -c(sample_size, var, nsim)) %>% 
+  dplyr::rename(item = name, se = value) %>% 
+  dplyr::group_by(sample_size, var, nsim) %>% 
+  dplyr::summarize(percent_below = sum(se <= cutoff)/length(unique(DF_RELpos$item))) %>% 
+  ungroup() %>% 
+  # then summarize all down averaging percents
+  dplyr::group_by(sample_size, var) %>% 
+  summarize(percent_below = mean(percent_below)) %>% 
+  dplyr::arrange(percent_below) %>% 
+  ungroup()
+#> `summarise()` has grouped output by 'sample_size', 'var'. You can override
+#> using the `.groups` argument.
+#> `summarise()` has grouped output by 'sample_size'. You can override using the
+#> `.groups` argument.
+
+flextable(final_sample %>% head()) %>% autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

sample_size

var

percent_below

35

Response

0.000

25

Response

0.005

30

Response

0.010

40

Response

0.015

50

Response

0.050

45

Response

0.055

+
+
+final_table_pos <- calculate_correction(
+  proportion_summary = final_sample,
+  pilot_sample_size = length(unique(DF_RELpos$ssID)),
+  proportion_variability = cutoff_relpos$prop_var
+  )
+
+flextable(final_table_pos) %>% 
+  autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

percent_below

sample_size

corrected_sample_size

81.0

105

70.33792

88.5

115

77.34137

91.0

125

84.39584

95.5

130

88.08384

+
+

Suggestions for REL- Condition:

+
+cutoff <- quantile(SE2, probs = .4)
+
+final_sample2 <- 
+  sim_table2 %>%
+  pivot_longer(cols = -c(sample_size, var, nsim)) %>% 
+  dplyr::rename(item = name, se = value)  %>% 
+  dplyr::group_by(sample_size, var, nsim) %>% 
+  dplyr::summarize(percent_below = sum(se <= cutoff)/length(unique(DF_RELneg$item))) %>% 
+  ungroup() %>% 
+  # then summarize all down averaging percents
+  dplyr::group_by(sample_size, var) %>% 
+  summarize(percent_below = mean(percent_below)) %>% 
+  dplyr::arrange(percent_below) %>% 
+  ungroup()
+#> `summarise()` has grouped output by 'sample_size', 'var'. You can override
+#> using the `.groups` argument.
+#> `summarise()` has grouped output by 'sample_size'. You can override using the
+#> `.groups` argument.
+
+flextable(final_sample2 %>% head()) %>% autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

sample_size

var

percent_below

25

Response

0.065

30

Response

0.065

35

Response

0.075

45

Response

0.105

40

Response

0.110

50

Response

0.130

+
+
+final_table_neg <- calculate_correction(
+  proportion_summary = final_sample2,
+  pilot_sample_size = length(unique(DF_RELneg$ssID)),
+  proportion_variability = cutoff_relneg$prop_var
+  )
+
+flextable(final_table_neg) %>% 
+  autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

percent_below

sample_size

corrected_sample_size

82.5

95

62.03046

86.0

105

69.52984

90.0

110

73.23150

98.0

120

80.94565

+
+

Suggestions for UNREL Condition:

+
+cutoff <- quantile(SE3, probs = .4)
+
+final_sample3 <- 
+  sim_table3 %>%
+  pivot_longer(cols = -c(sample_size, var, nsim)) %>% 
+  dplyr::rename(item = name, se = value) %>% 
+  dplyr::group_by(sample_size, var, nsim) %>% 
+  dplyr::summarize(percent_below = sum(se <= cutoff)/length(unique(DF_UNREL$item))) %>% 
+  ungroup() %>% 
+  # then summarize all down averaging percents
+  dplyr::group_by(sample_size, var) %>% 
+  summarize(percent_below = mean(percent_below)) %>% 
+  dplyr::arrange(percent_below) %>% 
+  ungroup()
+#> `summarise()` has grouped output by 'sample_size', 'var'. You can override
+#> using the `.groups` argument.
+#> `summarise()` has grouped output by 'sample_size'. You can override using the
+#> `.groups` argument.
+
+flextable(final_sample3 %>% head()) %>% autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

sample_size

var

percent_below

25

Response

0.030

35

Response

0.055

30

Response

0.060

40

Response

0.120

45

Response

0.125

50

Response

0.200

+
+
+final_table_unrel <- calculate_correction(
+  proportion_summary = final_sample3,
+  pilot_sample_size = length(unique(DF_UNREL$ssID)),
+  proportion_variability = cutoff_unrel$prop_var
+  )
+
+flextable(final_table_unrel) %>% 
+  autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

percent_below

sample_size

corrected_sample_size

81.0

105

69.89133

86.5

115

76.90026

90.0

125

83.91580

96.5

150

100.77698

+
+

Based on these simulations, we can decide our minimum sample size by +examining all three potential scores at 80% of items below the +criterion, \(n_{positive}\) = 70, \(n_{negative}\) = 62, or \(n_{unrelated}\) = 70. These scores are all +very similar, and we should select the largest one.

+
+
+

Maximum Sample Size +

+

In this example, we could set our maximum sample size for 90% power +which would equate to: \(n_{positive}\) += 84, \(n_{negative}\) = 73, or \(n_{unrelated}\) = 84.

+
+
+

Final Sample Size +

+

The final sample size should be selected from the largest suggested +sample size based on condition to ensure that all conditions are +adequately measured.

+
+
+
+
+ + + + +
+ + + + + + + diff --git a/docs/articles/montefinese_vignette_files/tabwid-1.1.3/tabwid.css b/docs/articles/montefinese_vignette_files/tabwid-1.1.3/tabwid.css new file mode 100644 index 0000000..5e31a86 --- /dev/null +++ b/docs/articles/montefinese_vignette_files/tabwid-1.1.3/tabwid.css @@ -0,0 +1,42 @@ +.tabwid { + font-size: initial; + padding-bottom: 1em; +} + +.tabwid table{ + border-spacing:0px !important; + border-collapse:collapse; + line-height:1; + margin-left:auto; + margin-right:auto; + border-width: 0; + border-color: transparent; + caption-side: top; +} +.tabwid-caption-bottom table{ + caption-side: bottom; +} +.tabwid_left table{ + margin-left:0; +} +.tabwid_right table{ + margin-right:0; +} +.tabwid td, .tabwid th { + padding: 0; +} +.tabwid a { + text-decoration: none; +} +.tabwid thead { + background-color: transparent; +} +.tabwid tfoot { + background-color: transparent; +} +.tabwid table tr { +background-color: transparent; +} +.katex-display { + margin: 0 0 !important; +} diff --git a/docs/articles/montefinese_vignette_files/tabwid-1.1.3/tabwid.js b/docs/articles/montefinese_vignette_files/tabwid-1.1.3/tabwid.js new file mode 100644 index 0000000..47070f7 --- /dev/null +++ b/docs/articles/montefinese_vignette_files/tabwid-1.1.3/tabwid.js @@ -0,0 +1,20 @@ +document.addEventListener("DOMContentLoaded", function(event) { + var els = document.querySelectorAll(".tabwid"); + var tabwid_link = document.querySelector('link[href*="tabwid.css"]') + if (tabwid_link === null) { + const tabwid_styles = document.evaluate("//style[contains(., 'tabwid')]", document, null, XPathResult.ANY_TYPE, null ); + tabwid_link = tabwid_styles.iterateNext(); + } + + Array.prototype.forEach.call(els, function(template) { + const dest = document.createElement("div"); + template.parentNode.insertBefore(dest, template.nextSibling) + dest.setAttribute("class", "flextable-shadow-host"); + const fantome = dest.attachShadow({mode: 'open'}); + fantome.appendChild(template); + if (tabwid_link !== null) { + fantome.appendChild(tabwid_link.cloneNode(true)); + } + }); +}); + diff --git a/docs/articles/roer_vignette.html b/docs/articles/roer_vignette.html new file mode 100644 index 0000000..44ba92e --- /dev/null +++ b/docs/articles/roer_vignette.html @@ -0,0 +1,491 @@ + + + + + + + + +Power and Sample Size Simulation: Survival Processing Usefulness • semanticprimeR + + + + + + + + + + Skip to contents + + +
+ + + + +
+
+

Power and Sample Size Simulation: Survival Processing Usefulness

+

Necdet Gürkan +& Yangyang Yu

+ +

2023-12-27

+ + +
roer_vignette.Rmd
+
+ + + +
+

Vignette Setup: +

+
+
+

Project/Data Title: +

+

The survival processing effect

+

Data provided by: Röer, Bell & Buchner (2013)

+
+
+

Project/Data Description: +

+

The data come from a conceptual replication study on the survival +processing effect. The survival processing effect refers to the finding +that rating words according to their relevance in a survival-related +scenario leads to better retention than processing words in a number of +other fictional scenarios. Participants were randomly assigned to one of +the rating scenarios (survival, afterlife, moving). The to-be-rated +words were presented individually in a random order on the computer +screen. Each word remained on the screen for five seconds. Participants +rated the words by clicking on a 5-point scale that ranged from +completely useless (1) to very useful (5), which was displayed right +below the word.

+
+
+

Methods Description: +

+

Participants were students at Heinrich Heine University Düsseldorf, +Germany that were paid for participating or received course credit. +Their ages ranged from 18 to 55 years. The words to-be-rated consisted +of 30 typical members of 30 categories drawn from the updated Battig and +Montague norms (Van Overschelde, Rawson, & Dunlosky, 2004).

+
+
+

Data Location: +

+

Data included within this vignette. We drop the scenario column +because the standard deviation and mean of item ratings across the +scenarios were identical. We also add a participant column to keep this +script similar to other ones.

+
+DF <- import("data/roer_data.xlsx")
+drops <- c("Scenario")
+DF <- DF[ , !(names(DF) %in% drops)]
+DF <- cbind(Participant_Number = 1:nrow(DF) , DF)
+
+str(DF)
+#> 'data.frame':    218 obs. of  31 variables:
+#>  $ Participant_Number: int  1 2 3 4 5 6 7 8 9 10 ...
+#>  $ Item_1            : num  1 3 3 2 3 3 3 1 4 1 ...
+#>  $ Item_2            : num  2 5 4 1 4 5 4 3 5 3 ...
+#>  $ Item_3            : num  5 3 1 5 2 2 5 2 3 4 ...
+#>  $ Item_4            : num  1 4 2 0 3 2 2 1 4 2 ...
+#>  $ Item_5            : num  3 5 1 5 1 3 5 2 0 4 ...
+#>  $ Item_6            : num  1 3 2 1 4 1 5 2 2 1 ...
+#>  $ Item_7            : num  4 2 4 1 4 4 4 1 5 3 ...
+#>  $ Item_8            : num  3 5 5 4 4 2 5 5 2 3 ...
+#>  $ Item_9            : num  1 5 4 5 4 2 4 1 3 3 ...
+#>  $ Item_10           : num  0 5 5 5 0 5 5 4 0 4 ...
+#>  $ Item_11           : num  3 5 4 5 3 1 5 5 2 1 ...
+#>  $ Item_12           : num  3 5 5 5 5 1 3 5 1 1 ...
+#>  $ Item_13           : num  1 1 3 1 2 1 1 4 1 1 ...
+#>  $ Item_14           : num  1 2 1 4 1 2 2 1 2 5 ...
+#>  $ Item_15           : num  1 4 2 1 5 1 3 2 2 1 ...
+#>  $ Item_16           : num  4 5 4 2 3 3 4 3 3 4 ...
+#>  $ Item_17           : num  3 5 0 1 3 1 4 3 3 3 ...
+#>  $ Item_18           : num  2 5 4 1 5 5 5 2 5 4 ...
+#>  $ Item_19           : num  2 1 1 4 1 3 4 2 4 3 ...
+#>  $ Item_20           : num  5 3 4 5 2 4 5 3 3 2 ...
+#>  $ Item_21           : num  3 0 4 5 3 4 1 1 4 2 ...
+#>  $ Item_22           : num  3 5 1 1 2 3 5 4 3 4 ...
+#>  $ Item_23           : num  1 1 2 1 1 4 3 1 5 2 ...
+#>  $ Item_24           : num  1 4 4 2 3 2 4 5 2 0 ...
+#>  $ Item_25           : num  2 5 5 3 5 1 5 4 3 4 ...
+#>  $ Item_26           : num  1 4 3 1 3 1 2 1 2 3 ...
+#>  $ Item_27           : num  1 5 1 1 5 2 4 4 3 4 ...
+#>  $ Item_28           : num  1 5 1 1 4 2 3 5 2 3 ...
+#>  $ Item_29           : num  1 5 2 3 2 1 4 3 1 3 ...
+#>  $ Item_30           : num  3 5 4 1 1 2 5 4 4 5 ...
+
+
+

Date Published: +

+

No official publication, see citation below.

+
+
+

Dataset Citation: +

+

Röer, J. P., Bell, R., & Buchner, A. (2013). Is the +survival-processing memory advantage due to richness of encoding? +Journal of Experimental Psychology: Learning, Memory, and Cognition, 39, +1294-1302.

+
+
+

Keywords: +

+

usefulness; survival processing; adaptive memory; richness of +encoding

+
+
+

Use License: +

+

CC BY-NC

+
+
+

Geographic Description - City/State/Country of Participants: +

+

Düsseldorf, Germany

+
+
+

Column Metadata: +

+
+metadata <- import("data/roer_metadata.xlsx")
+
+flextable(metadata) %>% autofit()
+
+ + + + + + + + + + + + + + + + + + + +

Variable Name

Variable Description

Type (numeric, character, logical, etc.)

Items

Item ratings for item_1 to item_30

Numeric

Scenario

Categorical scenarios- 1,2,3

Numeric

+
+
+
+

AIPE Analysis: +

+
+DF_long <- pivot_longer(DF, cols = -c(Participant_Number)) %>% 
+  dplyr:: rename(item = name, score = value)
+
+flextable(head(DF_long)) %>% autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

Participant_Number

item

score

1

Item_1

1

1

Item_2

2

1

Item_3

5

1

Item_4

1

1

Item_5

3

1

Item_6

1

+
+
+

Stopping Rule +

+

What is the usual standard error for the data that could be +considered for our stopping rule using the 40% decile?

+
+# individual SEs
+SE <- tapply(DF_long$score, DF_long$item, function (x) { sd(x)/sqrt(length(x)) })
+SE
+#>     Item_1    Item_10    Item_11    Item_12    Item_13    Item_14    Item_15 
+#> 0.08860091 0.09743922 0.10419876 0.10725788 0.07167329 0.11502337 0.09746261 
+#>    Item_16    Item_17    Item_18    Item_19     Item_2    Item_20    Item_21 
+#> 0.09425595 0.08981453 0.08968434 0.09817041 0.10421504 0.10768420 0.10195369 
+#>    Item_22    Item_23    Item_24    Item_25    Item_26    Item_27    Item_28 
+#> 0.09891678 0.11403914 0.08751293 0.10279479 0.08015419 0.09612067 0.09697587 
+#>    Item_29     Item_3    Item_30     Item_4     Item_5     Item_6     Item_7 
+#> 0.08758437 0.10963101 0.11319421 0.07944272 0.11514133 0.08852481 0.10163361 
+#>     Item_8     Item_9 
+#> 0.09615698 0.09118122
+
+cutoff <- quantile(SE, probs = .40)
+cutoff
+#>        40% 
+#> 0.09614246
+
+# we could also use the cutoff score function in semanticprimeR
+cutoff_score <- calculate_cutoff(population = DF_long,
+                                 grouping_items = "item",
+                                 score = "score",
+                                 minimum = min(DF_long$score),
+                                 maximum = max(DF_long$score))
+
+cutoff_score$cutoff
+#>        40% 
+#> 0.09614246
+

Using our 40% decile as a guide, we find that 0.096 is our target +standard error for an accurately measured item.

+
+
+

Minimum Sample Size +

+

To estimate the minimum sample size, we should figure out what number +of participants it would take to achieve 80%, 85%, 90%, and 95% of the +SEs for items below our critical score of 0.096.

+
+# sequence of sample sizes to try
+nsim <- 10 # small for cran
+samplesize_values <- seq(20, 500, 5)
+
+# create a blank table for us to save the values in 
+sim_table <- matrix(NA, 
+                    nrow = length(samplesize_values)*nsim, 
+                    ncol = length(unique(DF_long$item)))
+
+# make it a data frame
+sim_table <- as.data.frame(sim_table)
+
+# add a place for sample size values 
+sim_table$sample_size <- NA
+
+iterate <- 1
+for (p in 1:nsim){
+  # loop over sample sizes
+  for (i in 1:length(samplesize_values)){
+      
+    # temp dataframe that samples and summarizes
+    temp <- DF_long %>% 
+      group_by(item) %>% 
+      sample_n(samplesize_values[i], replace = T) %>% 
+      summarize(se = sd(score)/sqrt(length(score))) 
+    
+    colnames(sim_table)[1:length(unique(DF_long$item))] <- temp$item
+    sim_table[iterate, 1:length(unique(DF_long$item))] <- temp$se
+    sim_table[iterate, "sample_size"] <- samplesize_values[i]
+    sim_table[iterate, "nsim"] <- p
+    
+    iterate <- iterate + 1
+  }
+}
+
+final_sample <- 
+  sim_table %>% 
+  pivot_longer(cols = -c(sample_size, nsim)) %>% 
+  dplyr::rename(item = name, se = value) %>% 
+  group_by(sample_size, nsim) %>% 
+  summarize(percent_below = sum(se <= cutoff)/length(unique(DF_long$item))) %>% 
+  ungroup() %>% 
+  # then summarize all down averaging percents
+  dplyr::group_by(sample_size) %>% 
+  summarize(percent_below = mean(percent_below)) %>% 
+  dplyr::arrange(percent_below) %>% 
+  ungroup()
+#> `summarise()` has grouped output by 'sample_size'. You can override using the
+#> `.groups` argument.
+
+flextable(final_sample %>% head()) %>% autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

sample_size

percent_below

20

0

25

0

30

0

35

0

40

0

45

0

+
+
+final_table <- calculate_correction(
+  proportion_summary = final_sample,
+  pilot_sample_size = DF_long %>% group_by(item) %>% 
+    summarize(sample_size = n()) %>% ungroup() %>% 
+    summarize(avg_sample = mean(sample_size)) %>% pull(avg_sample),
+  proportion_variability = cutoff_score$prop_var
+  )
+
+flextable(final_table) %>% 
+  autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

percent_below

sample_size

corrected_sample_size

80.33333

270

60.18641

85.00000

285

67.54308

92.33333

300

75.18211

95.33333

315

82.85322

+
+

Based on these simulations, we can decide our minimum sample size is +likely close to 60.

+
+
+

Maximum Sample Size +

+

In this example, we could set our maximum sample size for 90% of +items, which would equate to 75 participants.

+
+
+

Final Sample Size +

+

We should consider any data loss or other issues related to survival +processing when thinking about the final sample size requirements.

+
+
+
+
+ + + + +
+ + + + + + + diff --git a/docs/articles/roer_vignette_files/tabwid-1.1.3/tabwid.css b/docs/articles/roer_vignette_files/tabwid-1.1.3/tabwid.css new file mode 100644 index 0000000..5e31a86 --- /dev/null +++ b/docs/articles/roer_vignette_files/tabwid-1.1.3/tabwid.css @@ -0,0 +1,42 @@ +.tabwid { + font-size: initial; + padding-bottom: 1em; +} + +.tabwid table{ + border-spacing:0px !important; + border-collapse:collapse; + line-height:1; + margin-left:auto; + margin-right:auto; + border-width: 0; + border-color: transparent; + caption-side: top; +} +.tabwid-caption-bottom table{ + caption-side: bottom; +} +.tabwid_left table{ + margin-left:0; +} +.tabwid_right table{ + margin-right:0; +} +.tabwid td, .tabwid th { + padding: 0; +} +.tabwid a { + text-decoration: none; +} +.tabwid thead { + background-color: transparent; +} +.tabwid tfoot { + background-color: transparent; +} +.tabwid table tr { +background-color: transparent; +} +.katex-display { + margin: 0 0 !important; +} diff --git a/docs/articles/roer_vignette_files/tabwid-1.1.3/tabwid.js b/docs/articles/roer_vignette_files/tabwid-1.1.3/tabwid.js new file mode 100644 index 0000000..47070f7 --- /dev/null +++ b/docs/articles/roer_vignette_files/tabwid-1.1.3/tabwid.js @@ -0,0 +1,20 @@ +document.addEventListener("DOMContentLoaded", function(event) { + var els = document.querySelectorAll(".tabwid"); + var tabwid_link = document.querySelector('link[href*="tabwid.css"]') + if (tabwid_link === null) { + const tabwid_styles = document.evaluate("//style[contains(., 'tabwid')]", document, null, XPathResult.ANY_TYPE, null ); + tabwid_link = tabwid_styles.iterateNext(); + } + + Array.prototype.forEach.call(els, function(template) { + const dest = document.createElement("div"); + template.parentNode.insertBefore(dest, template.nextSibling) + dest.setAttribute("class", "flextable-shadow-host"); + const fantome = dest.attachShadow({mode: 'open'}); + fantome.appendChild(template); + if (tabwid_link !== null) { + fantome.appendChild(tabwid_link.cloneNode(true)); + } + }); +}); + diff --git a/docs/articles/suchow_vignette.html b/docs/articles/suchow_vignette.html new file mode 100644 index 0000000..26e7002 --- /dev/null +++ b/docs/articles/suchow_vignette.html @@ -0,0 +1,645 @@ + + + + + + + + +Power and Sample Size Simulation: Superficial Face Judgment • semanticprimeR + + + + + + + + + + Skip to contents + + +
+ + + + +
+
+

Power and Sample Size Simulation: Superficial Face Judgment

+

Necdet Gürkan +& Yangyang Yu

+ +

2023-12-27

+ + +
suchow_vignette.Rmd
+
+ + + +
+

Vignette Setup: +

+
+
+

Project/Data Title: +

+

Deep models of superficial trait inferences

+

Data provided by: Jordan W. Suchow

+
+
+

Project/Data Description: +

+

The diversity of human faces and the contexts in which they appear +gives rise to an expansive stimulus space over which people infer +psychological traits (e.g., trustworthiness or alertness) and other +attributes (e.g., age or adiposity). Machine learning methods, in +particular deep neural networks, provide expressive feature +representations of face stimuli, but the correspondence between these +representations and various human attribute inferences is difficult to +determine because the former are high-dimensional vectors produced via +black box optimization algorithms. In this paper, we combined deep +generative image models with over 1 million judgments to model +inferences of more than 30 attributes over a comprehensive latent face +space. The predictive accuracy of the model approached human interrater +reliability, which simulations suggest would not have been possible with +fewer faces, fewer judgments, or lower-dimensional feature +representations. The model can be used to predict and manipulate +inferences with respect to arbitrary face photographs or to generate +synthetic photorealistic face stimuli that evoke impressions tuned along +the modeled attributes.

+

In sum, the dataset contains 1.14 million ratings across 1000 items +and 34 traits by 5,000 participants. NOTE: The trait trustworthy in the +dataset was collected twice, so the trait column has 35 traits.

+
+
+

Methods Description: +

+

For the attribute model studies, we used a between-subjects design +where participants evaluated faces with respect to each attribute. +Participants first consented. Then they completed a preinstruction +agreement to answer open-ended questions at the end of the study. In the +instructions, participants were given 25 examples of face images in +order to provide a sense of the diversity they would encounter during +the experiment. Participants were instructed to rate a series of faces +on a continuous slider scale where extremes were bipolar descriptors +such as “trustworthy” to “not trustworthy.” We did not supply +definitions of each attribute to participants and instead relied on +participants’ intuitive notions for each.

+

Each participant then completed 120 trials with the single attribute +to which they were assigned. One hundred of these trials displayed +images randomly selected (without replacement) from the full set; the +remaining 20 trials were repeats of earlier trials, selected randomly +from the 100 unique trials, which we used to assess intrarater +reliability. Each stimulus in the full set was judged by at least 30 +unique participants.

+

At the end of the experiment, participants were given a survey that +queried what participants believed we were assessing and asked for a +self-assessment of their performance and feedback on any potential +points of confusion, as well as demographic information such as age, +race, and gender. Participants were given 30 min to complete the entire +experiment, but most completed it in under 20 min. Each participant was +paid $1.50.

+
+
+

Data Location: +

+

https://github.com/jcpeterson/omi

+
+## Please set the work directory to the folder containing the scripts and data
+face_data <- import("data/suchow_data.csv.zip")
+str(face_data)
+#> 'data.frame':    1139300 obs. of  5 variables:
+#>  $ participant: int  1256 1256 1256 1256 1256 1256 1256 1256 1256 1256 ...
+#>  $ stimulus   : int  63 75 73 64 54 46 23 18 74 49 ...
+#>  $ trait      : int  1 1 1 1 1 1 1 1 1 1 ...
+#>  $ response   : int  77 99 0 58 69 58 54 47 24 71 ...
+#>  $ rt         : int  4413 3518 5248 4167 3703 6304 4774 4480 2974 3359 ...
+
+
+

Date Published: +

+

2022-04-15

+
+
+

Dataset Citation: +

+

Peterson, J. C., Uddenberg, S., Griffiths, T., Todorov, A., & +Suchow, J. W. (2022). Deep models of superficial face judgments. +Proceedings of the National Academy of Sciences (PNAS).

+
+
+

Keywords: +

+

first impressions, social perception, face perception

+
+
+

Use License: +

+

https://creativecommons.org/licenses/by-nc-sa/4.0/

+
+
+

Geographic Description - City/State/Country of Participants: +

+

For the attribute model studies, we used Amazon Mechanical Turk to +recruit a total of 4,157 participants across 10,974 sessions, of which +10,633 (≈ 97%) met our criteria for inclusion. Participants identified +their gender as female (2,065) or male (2,053), preferred not to say +(21), or did not have their gender listed as an option (18). The mean +age was ∼39 y old. Participants identified their race/ethnicity as +either White (2,935), Black/African American (458), Latinx/a/o or +Hispanic (158), East Asian (174), Southeast Asian (71), South Asian +(70), Native American/American Indian (31), Middle Eastern (12), Native +Hawaiian or Other Pacific Islander (3), or some combination of two or +more races/ethnicities (215). The remaining participants either +preferred not to say (22) or did not have their race/ethnicity listed as +an option (8). Participants were recruited from the United States.

+
+
+

Column Metadata: +

+
+metadata <- import("data/suchow_metadata.xlsx")
+
+flextable(metadata) %>% autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

Variable Name

Variable Description

Type (numeric, character, logical, etc.)

Participant

Unique number assigned to each participant

Numeric

Stimulus

Face 1 to 1004

Numeric

Trait

Trait 1 to 35

Numeric

Response

Rating for corresponding rating

Numeric

+
+
+
+

AIPE Analysis: +

+
+

Stopping Rule +

+

When pilot data is this large, it is important to sample a smaller +subset based on what the participant might actually do in the study. We +will pick 50 faces rated on 10 traits - and then select the highest and +lowest variance to estimate from. This choice is somewhat arbitrary - in +a real study, you could choose to use only the variables you were +interested in and pick the most conservative values or simply average +together estimates from all variables.

+
+# pick random faces
+faces <- unique(face_data$stimulus)[sample(unique(face_data$stimulus), size = 50)]
+# pick random traits
+traits <- unique(face_data$trait)[sample(unique(face_data$trait), size = 10)]
+
+face_data <- face_data %>% 
+  filter(trait %in% traits) %>% 
+  filter(stimulus %in% faces)
+
+# all SEs 
+SE_full <- tapply(face_data$response, face_data$trait, function (x) { sd(x)/sqrt(length(x)) })
+SE_full
+#>         3        11        15        17        18        20        25        26 
+#> 0.5302480 0.6052025 0.6057533 0.7151215 0.5899025 0.5936983 0.8063501 0.8173728 
+#>        29        33 
+#> 0.7510497 0.6380199
+
+## smallest variance is trait 4
+face_data_trait4_sub <- subset(face_data, trait == names(which.min(SE_full)))
+
+## largest is trait 30
+face_data_trait30_sub <- subset(face_data, trait == names(which.max(SE_full)))
+
+# individual SEs for 4 trait 
+SE1 <- tapply(face_data_trait4_sub$response, face_data_trait4_sub$stimulus, function (x) { sd(x)/sqrt(length(x)) })
+quantile(SE1, probs = .4)
+#>      40% 
+#> 3.230473
+
+# individual SEs for 30 trait
+SE2 <- tapply(face_data_trait30_sub$response, face_data_trait30_sub$stimulus, function (x) { sd(x)/sqrt(length(x)) })
+
+quantile(SE2, probs = .4)
+#>      40% 
+#> 4.120649
+
+
+

Minimum Sample Size +

+

How large does the sample have to be for 80% and 95% of the items to +be below our stopping SE rule?

+
+# sequence of sample sizes to try
+nsim <- 10 # small for cran 
+samplesize_values <- seq(25, 100, 5)
+
+# create a blank table for us to save the values in 
+sim_table <- matrix(NA, 
+                    nrow = length(samplesize_values)*nsim, 
+                    ncol = length(unique(face_data_trait4_sub$stimulus)))
+# make it a data frame
+sim_table <- as.data.frame(sim_table)
+
+# add a place for sample size values 
+sim_table$sample_size <- NA
+sim_table$var <- "response"
+
+# make a second table for the second variable
+sim_table2 <- matrix(NA, 
+                    nrow = length(samplesize_values)*nsim, 
+                    ncol = length(unique(face_data_trait30_sub$stimulus)))
+
+# make it a data frame
+sim_table2 <- as.data.frame(sim_table2)
+
+# add a place for sample size values 
+sim_table2$sample_size <- NA
+sim_table2$var <- "response"
+
+iterate <- 1
+for (p in 1:nsim){
+  # loop over sample sizes for age and outdoor trait
+  for (i in 1:length(samplesize_values)){
+      
+    # temp dataframe for age trait that samples and summarizes
+    temp7 <- face_data_trait4_sub %>% 
+      dplyr::group_by(stimulus) %>% 
+      dplyr::sample_n(samplesize_values[i], replace = T) %>% 
+      dplyr::summarize(se1 = sd(response)/sqrt(length(response))) 
+    
+    # 
+    colnames(sim_table)[1:length(unique(face_data_trait4_sub$stimulus))] <- temp7$stimulus
+    sim_table[iterate, 1:length(unique(face_data_trait4_sub$stimulus))] <- temp7$se1
+    sim_table[iterate, "sample_size"] <- samplesize_values[i]
+    sim_table[iterate, "nsim"] <- p
+    
+    # temp dataframe for outdoor trait that samples and summarizes
+    temp35 <-face_data_trait30_sub %>% 
+      dplyr::group_by(stimulus) %>% 
+      dplyr::sample_n(samplesize_values[i], replace = T) %>% 
+      dplyr::summarize(se2 = sd(response)/sqrt(length(response))) 
+    
+    # 
+    colnames(sim_table2)[1:length(unique(face_data_trait30_sub$stimulus))] <- temp35$stimulus
+    sim_table2[iterate, 1:length(unique(face_data_trait30_sub$stimulus))] <- temp35$se2
+    sim_table2[iterate, "sample_size"] <- samplesize_values[i]
+    sim_table2[iterate, "nsim"] <- p
+    
+    iterate <- 1 + iterate
+  
+  }
+  
+}
+

Calculate the cutoff score with information necessary for +correction.

+
+cutoff_trait4 <- calculate_cutoff(population = face_data_trait4_sub, 
+                 grouping_items = "stimulus",
+                 score = "response", 
+                 minimum = min(face_data_trait4_sub$response),
+                 maximum = max(face_data_trait4_sub$response))
+
+# same as above
+cutoff_trait4$cutoff
+#>      40% 
+#> 3.230473
+
+cutoff_trait30 <- calculate_cutoff(population = face_data_trait30_sub, 
+                 grouping_items = "stimulus",
+                 score = "response", 
+                 minimum = min(face_data_trait30_sub$response),
+                 maximum = max(face_data_trait30_sub$response))
+
+cutoff_trait30$cutoff
+#>      40% 
+#> 4.120649
+

Trait 4 Results:

+
+cutoff <- quantile(SE1, probs = .4)
+final_sample <- 
+  sim_table %>%
+  pivot_longer(cols = -c(sample_size, var, nsim)) %>% 
+  dplyr::rename(item = name, se = value) %>% 
+  dplyr::group_by(sample_size, var, nsim) %>% 
+  dplyr::summarize(percent_below = sum(se <= cutoff)/length(unique(face_data_trait4_sub$stimulus))) %>% 
+  ungroup() %>% 
+  # then summarize all down averaging percents
+  dplyr::group_by(sample_size, var) %>% 
+  summarize(percent_below = mean(percent_below)) %>% 
+  dplyr::arrange(percent_below) %>% 
+  ungroup()
+#> `summarise()` has grouped output by 'sample_size', 'var'. You can override
+#> using the `.groups` argument.
+#> `summarise()` has grouped output by 'sample_size'. You can override using the
+#> `.groups` argument.
+
+flextable(final_sample %>% head()) %>% autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

sample_size

var

percent_below

25

response

0.110

30

response

0.176

35

response

0.288

40

response

0.442

45

response

0.604

50

response

0.720

+
+

Calculate the final corrected scores:

+
+final_scores <- calculate_correction(proportion_summary = final_sample,
+                     pilot_sample_size = face_data_trait4_sub %>% 
+                       group_by(stimulus) %>% 
+                       summarize(sample_size = n()) %>% 
+                       ungroup() %>% 
+                       summarize(avg_sample = mean(sample_size)) %>% 
+                       pull(avg_sample),
+                     proportion_variability = cutoff_trait4$prop_var)
+
+flextable(final_scores) %>% autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

percent_below

sample_size

corrected_sample_size

82.6

55

45.47975

88.6

60

50.61284

93.4

65

55.82046

97.2

70

60.93349

+
+

Trait 30 Results:

+
+cutoff <- quantile(SE2, probs = .4) 
+final_sample2 <- 
+  sim_table2 %>%
+  pivot_longer(cols = -c(sample_size, var, nsim)) %>% 
+  dplyr::rename(item = name, se = value)  %>% 
+  dplyr::group_by(sample_size, var, nsim) %>% 
+  dplyr::summarize(percent_below = sum(se <= cutoff)/length(unique(face_data_trait30_sub$stimulus))) %>% 
+  ungroup() %>% 
+  # then summarize all down averaging percents
+  dplyr::group_by(sample_size, var) %>% 
+  summarize(percent_below = mean(percent_below)) %>% 
+  dplyr::arrange(percent_below) %>% 
+  ungroup()
+#> `summarise()` has grouped output by 'sample_size', 'var'. You can override
+#> using the `.groups` argument.
+#> `summarise()` has grouped output by 'sample_size'. You can override using the
+#> `.groups` argument.
+
+flextable(final_sample2 %>% head()) %>% autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

sample_size

var

percent_below

25

response

0.336

30

response

0.408

35

response

0.506

40

response

0.626

45

response

0.712

50

response

0.822

+
+

Calculate the final corrected scores:

+
+final_scores2 <- calculate_correction(proportion_summary = final_sample2,
+                     pilot_sample_size = face_data_trait30_sub %>% 
+                       group_by(stimulus) %>% 
+                       summarize(sample_size = n()) %>% 
+                       ungroup() %>% 
+                       summarize(avg_sample = mean(sample_size)) %>% 
+                       pull(avg_sample),
+                     proportion_variability = cutoff_trait30$prop_var)
+
+flextable(final_scores2) %>% autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

percent_below

sample_size

corrected_sample_size

82.2

50

46.04663

89.8

55

51.50307

93.8

60

56.99324

98.0

65

62.40286

+
+

Based on these simulations, we can decide our minimum sample size for +80% is likely close to 45 for the trait 4 trials or 46 for the trait 30 +trials, depending on rounding. We can consider only the most variant +trait for power analysis since it would satisfy other traits in the +dataset as well.

+
+
+

Maximum Sample Size +

+

In this example, we could set our maximum sample size for 95% items +below the criterion, which would equate to 61 for the trait 4 trials or +62 for trait 30 trials.

+
+
+

Final Sample Size +

+

Considering both estimated traits and a smaller proportion of things +to rate, we found that we could likely use samples from 40 to 60 people. +Other considerations could include fatigue on the number of ratings each +person has to complete.

+
+
+
+
+ + + + +
+ + + + + + + diff --git a/docs/articles/suchow_vignette_files/tabwid-1.1.3/tabwid.css b/docs/articles/suchow_vignette_files/tabwid-1.1.3/tabwid.css new file mode 100644 index 0000000..5e31a86 --- /dev/null +++ b/docs/articles/suchow_vignette_files/tabwid-1.1.3/tabwid.css @@ -0,0 +1,42 @@ +.tabwid { + font-size: initial; + padding-bottom: 1em; +} + +.tabwid table{ + border-spacing:0px !important; + border-collapse:collapse; + line-height:1; + margin-left:auto; + margin-right:auto; + border-width: 0; + border-color: transparent; + caption-side: top; +} +.tabwid-caption-bottom table{ + caption-side: bottom; +} +.tabwid_left table{ + margin-left:0; +} +.tabwid_right table{ + margin-right:0; +} +.tabwid td, .tabwid th { + padding: 0; +} +.tabwid a { + text-decoration: none; +} +.tabwid thead { + background-color: transparent; +} +.tabwid tfoot { + background-color: transparent; +} +.tabwid table tr { +background-color: transparent; +} +.katex-display { + margin: 0 0 !important; +} diff --git a/docs/articles/suchow_vignette_files/tabwid-1.1.3/tabwid.js b/docs/articles/suchow_vignette_files/tabwid-1.1.3/tabwid.js new file mode 100644 index 0000000..47070f7 --- /dev/null +++ b/docs/articles/suchow_vignette_files/tabwid-1.1.3/tabwid.js @@ -0,0 +1,20 @@ +document.addEventListener("DOMContentLoaded", function(event) { + var els = document.querySelectorAll(".tabwid"); + var tabwid_link = document.querySelector('link[href*="tabwid.css"]') + if (tabwid_link === null) { + const tabwid_styles = document.evaluate("//style[contains(., 'tabwid')]", document, null, XPathResult.ANY_TYPE, null ); + tabwid_link = tabwid_styles.iterateNext(); + } + + Array.prototype.forEach.call(els, function(template) { + const dest = document.createElement("div"); + template.parentNode.insertBefore(dest, template.nextSibling) + dest.setAttribute("class", "flextable-shadow-host"); + const fantome = dest.attachShadow({mode: 'open'}); + fantome.appendChild(template); + if (tabwid_link !== null) { + fantome.appendChild(tabwid_link.cloneNode(true)); + } + }); +}); + diff --git a/docs/articles/ulloa_vignette.html b/docs/articles/ulloa_vignette.html new file mode 100644 index 0000000..2519619 --- /dev/null +++ b/docs/articles/ulloa_vignette.html @@ -0,0 +1,603 @@ + + + + + + + + +Power and Sample Size Simulation: Liking effect induced by gaze • semanticprimeR + + + + + + + + + + Skip to contents + + +
+ + + + +
+
+

Power and Sample Size Simulation: Liking effect induced by gaze

+

Necdet Gürkan +& Yangyang Yu

+ +

2023-12-27

+ + +
ulloa_vignette.Rmd
+
+ + + +
+

Vignette Setup: +

+
+
+

Project/Data Title: +

+

Liking effect induced by gaze

+

Data provided by: José Luis Ulloa, Clara Marchetti, Marine Taffou +& Nathalie George

+
+
+

Project/Data Description: +

+

This dataset resulted from a study aiming at investigating how gaze +perception can influence preferences. Previous studies suggest that we +like more the objects that are looked-at by others than non-looked-at +objects (a so-called liking effect). We extended previous studies to +investigate both abstract and manipulable objects. Participants +performed a categorization task (for items that were cued or not by +gaze). Next, participants evaluated how much they liked the items. We +tested if the liking effect could be observed for non-manipulable +(alphanumeric characters) as well as for manipulable items (common +tools).

+
+
+

Methods Description: +

+

Participants were students at Heinrich-Heine-Universität Düsseldorf, +Germany that were paid for participating or received course credit. +Their ages ranged from 18 to 55 years. The words to-be-rated consisted +of 30 typical members of 30 categories drawn from the updated Battig and +Montague norms (Van Overschelde, Rawson, & Dunlosky, 2004).

+
+
+

Data Location: +

+

Data included within this vignette.

+
+DF <- import("data/ulloa_data.csv")
+drops <- c("RT", "side", "aff-ness")
+DF <- DF[ , !(names(DF) %in% drops)]
+head(DF)
+#>   suj congr item liking
+#> 1   1 valid    G      4
+#> 2   1 valid    G      3
+#> 3   1 valid    G      1
+#> 4   1 valid    G      3
+#> 5   1 valid    K      8
+#> 6   1 valid    K      6
+
+
+

Date Published: +

+

No official publication, see citation below.

+
+
+

Dataset Citation: +

+

José Luis Ulloa, Clara Marchetti, Marine Taffou & Nathalie George +(2014): Only your eyes tell me what you like: Exploring the liking +effect induced by other’s gaze, Cognition & Emotion, DOI: +10.1080/02699931.2014.919899

+
+
+

Keywords: +

+

Social attention; Gaze; Pointing gesture; Liking; Cueing.

+
+
+

Use License: +

+

CC-BY

+
+
+

Geographic Description - City/State/Country of Participants: +

+

Paris, France

+
+
+

Column Metadata: +

+
+metadata <- import("data/ulloa_metadata.xlsx")
+
+flextable(metadata) %>% autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

Variable Name

Variable Description

Type (numeric, character, logical, etc.)

suj

Unique number assigned to each participant

Numeric

congr

valid vs invalid

Character

item

G, K, S, L

Character

liking

rating response

Numeric

+
+
+
+

AIPE Analysis +

+

In this dataset, there are valid and invalid cue-targeting variable. +In valid cue-targeting condition, stimulus is on the same side of the +gaze. In invalid cue-targeting condition, stimulus was on the opposite +side of the gaze. We consider these two different conditions +separately.

+
+

Stopping Rule +

+

What the usual standard error for the data that could be considered +for our stopping rule using the 40% decile?

+
+### create  subset for valid cue-targeting
+DF_valid <- subset(DF, congr == "valid") %>% 
+  group_by(suj, item) %>% 
+  summarize(liking = mean(liking, na.rm = T)) %>% 
+  as.data.frame()
+#> `summarise()` has grouped output by 'suj'. You can override using the `.groups`
+#> argument.
+
+### create  subset for invalid cue-targeting
+DF_invalid <- subset(DF, congr == "invalid") %>% 
+  group_by(suj, item) %>% 
+  summarize(liking = mean(liking, na.rm = T)) %>% 
+  as.data.frame()
+#> `summarise()` has grouped output by 'suj'. You can override using the `.groups`
+#> argument.
+
+# individual SEs for valid cue-targeting condition 
+SE1 <- tapply(DF_valid$liking, DF_valid$item, function (x) { sd(x)/sqrt(length(x)) })
+
+SE1
+#>         G         K         L         S 
+#> 0.2013228 0.1779694 0.1801060 0.2286006
+cutoff1 <- quantile(SE1, probs = .4)
+cutoff1
+#>       40% 
+#> 0.1843494
+
+# individual SEs for invalid cue-targeting condition
+SE2 <- tapply(DF_invalid$liking, DF_invalid$item, function (x) { sd(x)/sqrt(length(x)) })
+
+SE2
+#>         G         K         L         S 
+#> 0.1982333 0.1749820 0.1724613 0.2132725
+cutoff2 <- quantile(SE2, probs = .4)
+cutoff2
+#>       40% 
+#> 0.1796323
+
+# sequence of sample sizes to try
+nsim <- 10 # small for cran
+samplesize_values <- seq(25, 200, 5)
+
+# create a blank table for us to save the values in 
+sim_table <- matrix(NA, 
+                    nrow = length(samplesize_values)*nsim, 
+                    ncol = length(unique(DF_valid$item)))
+# make it a data frame
+sim_table <- as.data.frame(sim_table)
+
+# add a place for sample size values 
+sim_table$sample_size <- NA
+sim_table$var <- "liking"
+
+# make a second table for the second variable
+sim_table2 <- matrix(NA, 
+                    nrow = length(samplesize_values)*nsim, 
+                    ncol = length(unique(DF_valid$item)))
+
+# make it a data frame
+sim_table2 <- as.data.frame(sim_table2)
+
+# add a place for sample size values 
+sim_table2$sample_size <- NA
+sim_table2$var <- "liking"
+
+iterate <- 1
+for (p in 1:nsim){
+  
+  # loop over sample sizes for age and outdoor trait
+  for (i in 1:length(samplesize_values)){
+      
+    # temp dataframe for age trait that samples and summarizes
+    temp_valid <- DF_valid %>% 
+      dplyr::group_by(item) %>% 
+      dplyr::sample_n(samplesize_values[i], replace = T) %>% 
+      dplyr::summarize(se1 = sd(liking)/sqrt(length(liking))) 
+    
+    # 
+    colnames(sim_table)[1:length(unique(DF_valid$item))] <- temp_valid$item
+    sim_table[iterate, 1:length(unique(DF_valid$item))] <- temp_valid$se1
+    sim_table[iterate, "sample_size"] <- samplesize_values[i]
+    sim_table[iterate, "nsim"] <- p
+    
+    # temp dataframe for outdoor trait that samples and summarizes
+    
+    temp_invalid <-DF_invalid %>% 
+      dplyr::group_by(item) %>% 
+      dplyr::sample_n(samplesize_values[i], replace = T) %>% 
+      dplyr::summarize(se2 = sd(liking)/sqrt(length(liking))) 
+  
+    # 
+    colnames(sim_table)[1:length(unique(DF_invalid$item))] <- temp_invalid$item
+    sim_table2[iterate, 1:length(unique(DF_invalid$item))] <- temp_invalid$se2
+    sim_table2[iterate, "sample_size"] <- samplesize_values[i]
+    sim_table2[iterate, "nsim"] <- p
+    
+    iterate <- 1 + iterate
+  }
+  
+}
+

Calculate the cutoff score with information necessary for +correction.

+
+cutoff_valid <- calculate_cutoff(population = DF_valid, 
+                 grouping_items = "item",
+                 score = "liking", 
+                 minimum = min(DF_valid$liking),
+                 maximum = max(DF_valid$liking))
+
+# same as above
+cutoff_valid$cutoff
+#>       40% 
+#> 0.1843494
+
+cutoff_invalid <- calculate_cutoff(population = DF_invalid, 
+                 grouping_items = "item",
+                 score = "liking", 
+                 minimum = min(DF_valid$liking),
+                 maximum = max(DF_valid$liking))
+
+cutoff_invalid$cutoff
+#>       40% 
+#> 0.1796323
+
+### for valid cue-targeting condition
+final_sample_valid <- 
+  sim_table %>%
+  pivot_longer(cols = -c(sample_size, var, nsim)) %>%
+  dplyr::rename(item = name, se = value) %>% 
+  dplyr::group_by(sample_size, var, nsim) %>% 
+  dplyr::summarize(percent_below = sum(se <= cutoff1)/length(unique(DF_valid$item))) %>% 
+  ungroup() %>% 
+  # then summarize all down averaging percents
+  dplyr::group_by(sample_size, var) %>% 
+  summarize(percent_below = mean(percent_below)) %>% 
+  dplyr::arrange(percent_below) %>% 
+  ungroup()
+#> `summarise()` has grouped output by 'sample_size', 'var'. You can override
+#> using the `.groups` argument.
+#> `summarise()` has grouped output by 'sample_size'. You can override using the
+#> `.groups` argument.
+
+flextable(final_sample_valid %>% head()) %>% 
+  autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

sample_size

var

percent_below

25

liking

0.150

30

liking

0.250

35

liking

0.300

40

liking

0.425

45

liking

0.625

50

liking

0.825

+
+

Calculate the final corrected scores:

+
+final_scores <- calculate_correction(proportion_summary = final_sample_valid,
+                     pilot_sample_size = length(unique(DF$suj)),
+                     proportion_variability = cutoff_valid$prop_var)
+
+# only show first four rows since all 100
+flextable(final_scores %>% 
+            ungroup() %>% 
+            slice_head(n = 4)) %>% autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

percent_below

sample_size

corrected_sample_size

82.5

50

44.43666

92.5

55

50.02481

92.5

55

50.02481

95.0

60

55.49695

+
+
+### for valid cue-targeting condition
+final_sample_invalid <- 
+  sim_table2 %>%
+  pivot_longer(cols = -c(sample_size, var, nsim)) %>%
+  dplyr::rename(item = name, se = value) %>% 
+  dplyr::group_by(sample_size, var, nsim) %>% 
+  dplyr::summarize(percent_below = sum(se <= cutoff2)/length(unique(DF_invalid$item))) %>% 
+  ungroup() %>% 
+  # then summarize all down averaging percents
+  dplyr::group_by(sample_size, var) %>% 
+  summarize(percent_below = mean(percent_below)) %>% 
+  dplyr::arrange(percent_below) %>% 
+  ungroup()
+#> `summarise()` has grouped output by 'sample_size', 'var'. You can override
+#> using the `.groups` argument.
+#> `summarise()` has grouped output by 'sample_size'. You can override using the
+#> `.groups` argument.
+
+flextable(final_sample_invalid %>% head()) %>% 
+  autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

sample_size

var

percent_below

25

liking

0.075

30

liking

0.250

35

liking

0.400

40

liking

0.600

45

liking

0.675

50

liking

0.825

+
+

Calculate the final corrected scores:

+
+final_scores2 <- calculate_correction(proportion_summary = final_sample_invalid,
+                     pilot_sample_size = length(unique(DF$suj)),
+                     proportion_variability = cutoff_invalid$prop_var)
+
+# only show first four rows since all 100
+flextable(final_scores2 %>% 
+            ungroup() %>% 
+            slice_head(n = 4)) %>% autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

percent_below

sample_size

corrected_sample_size

82.5

50

44.78681

87.5

55

50.23831

92.5

60

55.67221

100.0

65

61.41225

+
+
+
+

Minimum Sample Size +

+

Based on these simulations, we can decide our minimum sample size for +80% is likely close to 44 for the valid trials or 45 for the invalid +trials, depending on rounding.

+
+
+

Maximum Sample Size +

+

In this example, we could set our maximum sample size for 95% items +below the criterion, which would equate to 55 for the valid trials or 61 +for invalid trials. In this case, values are equal because the percent +below jumps from 75% to 100%.

+
+
+

Final Sample Size +

+

In any estimate for sample size for this study, the dataset has a +large variance in ratings. This dataset need to more sample for items in +each conditions. In fact, we experimented combining two conditions +(valid & invalid cue-targeting) which did not result in any +difference.

+
+
+
+
+ + + + +
+ + + + + + + diff --git a/docs/articles/ulloa_vignette_files/tabwid-1.1.3/tabwid.css b/docs/articles/ulloa_vignette_files/tabwid-1.1.3/tabwid.css new file mode 100644 index 0000000..5e31a86 --- /dev/null +++ b/docs/articles/ulloa_vignette_files/tabwid-1.1.3/tabwid.css @@ -0,0 +1,42 @@ +.tabwid { + font-size: initial; + padding-bottom: 1em; +} + +.tabwid table{ + border-spacing:0px !important; + border-collapse:collapse; + line-height:1; + margin-left:auto; + margin-right:auto; + border-width: 0; + border-color: transparent; + caption-side: top; +} +.tabwid-caption-bottom table{ + caption-side: bottom; +} +.tabwid_left table{ + margin-left:0; +} +.tabwid_right table{ + margin-right:0; +} +.tabwid td, .tabwid th { + padding: 0; +} +.tabwid a { + text-decoration: none; +} +.tabwid thead { + background-color: transparent; +} +.tabwid tfoot { + background-color: transparent; +} +.tabwid table tr { +background-color: transparent; +} +.katex-display { + margin: 0 0 !important; +} diff --git a/docs/articles/ulloa_vignette_files/tabwid-1.1.3/tabwid.js b/docs/articles/ulloa_vignette_files/tabwid-1.1.3/tabwid.js new file mode 100644 index 0000000..47070f7 --- /dev/null +++ b/docs/articles/ulloa_vignette_files/tabwid-1.1.3/tabwid.js @@ -0,0 +1,20 @@ +document.addEventListener("DOMContentLoaded", function(event) { + var els = document.querySelectorAll(".tabwid"); + var tabwid_link = document.querySelector('link[href*="tabwid.css"]') + if (tabwid_link === null) { + const tabwid_styles = document.evaluate("//style[contains(., 'tabwid')]", document, null, XPathResult.ANY_TYPE, null ); + tabwid_link = tabwid_styles.iterateNext(); + } + + Array.prototype.forEach.call(els, function(template) { + const dest = document.createElement("div"); + template.parentNode.insertBefore(dest, template.nextSibling) + dest.setAttribute("class", "flextable-shadow-host"); + const fantome = dest.attachShadow({mode: 'open'}); + fantome.appendChild(template); + if (tabwid_link !== null) { + fantome.appendChild(tabwid_link.cloneNode(true)); + } + }); +}); + diff --git a/docs/articles/vanpaemel_vignette.html b/docs/articles/vanpaemel_vignette.html new file mode 100644 index 0000000..fead87e --- /dev/null +++ b/docs/articles/vanpaemel_vignette.html @@ -0,0 +1,637 @@ + + + + + + + + +Power and Sample Size Simulation: Typicality, goodness, imageability, and familiarity of stimuli across 16 categories • semanticprimeR + + + + + + + + + + Skip to contents + + +
+ + + + +
+
+

Power and Sample Size Simulation: Typicality, goodness, imageability, and familiarity of stimuli across 16 categories

+

Necdet Gürkan +& Yangyang Yu

+ +

2023-12-27

+ + +
vanpaemel_vignette.Rmd
+
+ + + +
+

Vignette Setup: +

+
+
+

Project/Data Title: +

+

Exemplar by feature applicability matrices and other Dutch normative +data for semantic concepts

+

Data provided by: Wolf Vanpaemel

+
+
+

Project/Data Description: +

+

This data provides extensive exemplar by feature applicability +matrices covering 15 or 16 different categories (birds, fish, insects, +mammals, amphibians/reptiles, clothing, kitchen utensils, musical +instruments, tools, vehicles, weapons, fruit, vegetables, professions, +and sports), as well as two large semantic domains (animals and +artifacts). For all exemplars of the semantic categories, typicality +ratings, goodness ratings, goodness rank order, generation frequency, +exemplar associative strength, category associative strength, estimated +age of acquisition, word frequency, familiarity ratings, imageability +ratings, and pairwise similarity ratings are described as well. The +structure of the dataset is not programming language friendly. Here, we +only consider typicality.

+
+
+

Methods Description: +

+

The typicality data were collected as part of a larger data +collection. Here we describe the typicality data collection only. The +data collection took place in a large classroom where all the +participants were present at the same time. The participants received a +booklet with instructions on the first page, followed by four sheets +with a semantic category label printed in bold on top. Each of the +category labels was followed by a list of 5–33 items belonging to that +category, referring to exemplars. The participants were asked to +indicate, for every item in the list, how typical it was for the +category printed on top of the page. They used a Likert-type rating +scale, ranging from 1 for very atypical items to 20 for very typical +items. If they encountered an exemplar they did not know, they were +asked to circle it. Every participant completed typicality ratings for +four different categories. The assignment of categories to participants +was randomized. For every category, four different random permutations +of the exemplars were used, and each of these permutations was +distributed with an equal frequency among the participants. All the +exemplars of a category were rated by 28 different participants.

+
+
+

Data Location: +

+

https://static-content.springer.com/esm/art%3A10.3758%2FBRM.40.4.1030/MediaObjects/DeDeyne-BRM-2008b.zip +and included here.

+
+### for typicality data -- cleaning and processing
+typicality_fnames <- list.files(path = "data/vanpaemel_data",
+                                full.names = TRUE)
+
+typicality_dfs <- lapply(typicality_fnames, read.csv)
+
+ID <- c(1:16)
+typicality_dfs <- mapply(cbind, typicality_dfs, "SampleID" = ID, SIMPLIFY = F)
+
+typicality_all_df <- bind_rows(typicality_dfs)
+typicality_all_df_v2 <- typicality_all_df %>% 
+                        unite("comp_group", X:X.1, remove = TRUE) %>% 
+                        select(-c(30,31,32,33,34)) %>% 
+                        drop_na(c(2:29)) %>%
+                        filter_all(any_vars(!is.na(.))) %>%
+                        dplyr::rename(compType = SampleID)
+# typicality_all_df_v2
+typicality_all_df_v3 <- typicality_all_df_v2 %>% 
+  select(starts_with("X"), compType, comp_group) %>% 
+  pivot_longer(cols = starts_with("X"), 
+               names_to = "participant", 
+               values_to = "score")
+                    
+head(typicality_all_df_v3)
+#> # A tibble: 6 × 4
+#>   compType comp_group  participant score
+#>      <int> <chr>       <chr>       <int>
+#> 1        1 kikker_frog X.2            18
+#> 2        1 kikker_frog X.3            20
+#> 3        1 kikker_frog X.4            19
+#> 4        1 kikker_frog X.5            12
+#> 5        1 kikker_frog X.6            20
+#> 6        1 kikker_frog X.7            15
+
+
+

Date Published: +

+

2008-11-01

+
+
+

Dataset Citation: +

+

De Deyne, S., Verheyen, S., Ameel, E. et al. Exemplar by feature +applicability matrices and other Dutch normative data for semantic +concepts. Behavior Research Methods 40, 1030–1048 (2008). https://doi.org/10.3758/BRM.40.4.1030

+
+
+

Keywords: +

+

Typicality, goodness, imageability, familiarity

+
+
+

Use License: +

+

CC-By Attribution 4.0 International

+
+
+

Geographic Description - City/State/Country of Participants: +

+

University of Leuven, Belgium

+
+
+

Column Metadata: +

+
+metadata <- import("data/vanpaemel_metadata.xlsx")
+
+flextable(metadata) %>% autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

Variable Name

Variable Description

Type (numeric, character, logical, etc.)

compType

Comparison type for typicality rating

Character

comp_group

Individual items within compType

Character

participant

Participant number

Character

score

Typicality: how typical is the item for the category?

Numeric

+
+
+
+

AIPE Analysis: +

+
+

Stopping Rule +

+

In this example, we will pick one comparison type and use the items +within that to estimate sample size. This choice is arbitrary!

+
+# individual SEs among different comparison group
+SE <- tapply(typicality_all_df_v3$score, typicality_all_df_v3$compType, function (x) { sd(x)/sqrt(length(x)) })
+SE
+#>         1         2         3         4         5         6         7         8 
+#> 0.4847915 0.1868793 0.1894860 0.2326625 0.1862387 0.2310363 0.1433243 0.1751163 
+#>         9        10        11        12        14        16 
+#> 0.1888044 0.1563060 0.2512611 0.1945454 0.2042343 0.2520606
+
+min(SE)
+#> [1] 0.1433243
+max(SE)
+#> [1] 0.4847915
+
+# comparison type 1: amphibians
+
+typicality_data_gp1_sub <- subset(typicality_all_df_v3, compType == 1)
+
+# individual SEs for  comparison type 1
+SE1 <- tapply(typicality_data_gp1_sub$score, typicality_data_gp1_sub$comp_group, function (x) { sd(x)/sqrt(length(x)) })
+
+SE1
+#>           kikker_frog    krokodil_crocodile              pad_toad 
+#>             0.4836714             1.1085074             0.7368140 
+#> salamander_salamander    schildpad_tortoise 
+#>             0.7531742             1.6330366
+
+# sequence of sample sizes to try
+nsim <- 10 # small for cran 
+samplesize_values <- seq(5, 200, 5)
+
+# create a blank table for us to save the values in 
+sim_table <- matrix(NA, 
+                    nrow = length(samplesize_values)*nsim, 
+                    ncol = length(unique(typicality_data_gp1_sub$comp_group)))
+# make it a data frame
+sim_table <- as.data.frame(sim_table)
+
+# add a place for sample size values 
+sim_table$sample_size <- NA
+sim_table$var <- "score"
+
+iterate <- 1
+for (p in 1:nsim){
+  
+    # loop over sample sizes for comparison type 
+  for (i in 1:length(samplesize_values)){
+      
+    # temp dataframe for comparison type 1 that samples and summarizes
+    temp1 <- typicality_data_gp1_sub %>% 
+      dplyr::group_by(comp_group) %>% 
+      dplyr::sample_n(samplesize_values[i], replace = T) %>% 
+      dplyr::summarize(se2 = sd(score)/sqrt(length(score))) 
+    
+    # add to table
+    colnames(sim_table)[1:length(unique(typicality_data_gp1_sub$comp_group))] <- temp1$comp_group
+    sim_table[iterate, 1:length(unique(typicality_data_gp1_sub$comp_group))] <- temp1$se2
+    sim_table[iterate, "sample_size"] <- samplesize_values[i]
+    sim_table[iterate, "nsim"] <- p
+    
+    iterate <- 1 + iterate 
+  }
+  
+}
+

Calculate the cutoff score with information necessary for +correction.

+
+cutoff <- calculate_cutoff(population = typicality_data_gp1_sub, 
+                 grouping_items = "comp_group",
+                 score = "score", 
+                 minimum = min(typicality_data_gp1_sub$score),
+                 maximum = max(typicality_data_gp1_sub$score))
+
+cutoff$cutoff
+#>       40% 
+#> 0.7466301
+
+### for response outputs 
+# figure out cut off
+final_sample <- 
+  sim_table %>%
+  pivot_longer(cols = -c(sample_size, var, nsim)) %>% 
+  dplyr::rename(item = name, se = value) %>% 
+  dplyr::group_by(sample_size, var, nsim) %>% 
+  dplyr::summarize(percent_below = sum(se <= cutoff$cutoff)/length(unique(typicality_data_gp1_sub$comp_group))) %>% 
+  ungroup() %>% 
+  # then summarize all down averaging percents
+  dplyr::group_by(sample_size, var) %>% 
+  summarize(percent_below = mean(percent_below)) %>% 
+  dplyr::arrange(percent_below) %>% 
+  ungroup()
+#> `summarise()` has grouped output by 'sample_size', 'var'. You can override
+#> using the `.groups` argument.
+#> `summarise()` has grouped output by 'sample_size'. You can override using the
+#> `.groups` argument.
+
+flextable(final_sample) %>% autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

sample_size

var

percent_below

10

score

0.12

5

score

0.16

15

score

0.18

20

score

0.30

25

score

0.38

30

score

0.52

35

score

0.56

40

score

0.56

45

score

0.62

50

score

0.62

55

score

0.66

60

score

0.68

65

score

0.78

70

score

0.80

75

score

0.82

80

score

0.82

85

score

0.82

95

score

0.82

110

score

0.84

115

score

0.84

100

score

0.86

90

score

0.88

105

score

0.88

125

score

0.88

135

score

0.88

130

score

0.90

150

score

0.92

120

score

0.94

140

score

0.94

155

score

0.94

195

score

0.96

160

score

0.98

170

score

0.98

175

score

0.98

145

score

1.00

165

score

1.00

180

score

1.00

185

score

1.00

190

score

1.00

200

score

1.00

+
+

Calculate the final corrected scores:

+
+final_scores <- calculate_correction(proportion_summary = final_sample,
+                     pilot_sample_size = length(unique(typicality_data_gp1_sub$participant)),
+                     proportion_variability = cutoff$prop_var)
+
+flextable(final_scores) %>% autofit()
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

percent_below

sample_size

corrected_sample_size

80

70

69.05319

88

90

86.00674

94

120

108.71054

100

145

126.05262

+
+
+
+

Minimum Sample Size +

+

Based on these simulations, we can decide our minimum sample size is +likely close to 69.

+
+
+

Maximum Sample Size +

+

In this example, we could set our maximum sample size for 90% power, +which would equate to 109 participants.

+
+
+
+
+ + + + +
+ + + + + + + diff --git a/docs/articles/vanpaemel_vignette_files/tabwid-1.1.3/tabwid.css b/docs/articles/vanpaemel_vignette_files/tabwid-1.1.3/tabwid.css new file mode 100644 index 0000000..5e31a86 --- /dev/null +++ b/docs/articles/vanpaemel_vignette_files/tabwid-1.1.3/tabwid.css @@ -0,0 +1,42 @@ +.tabwid { + font-size: initial; + padding-bottom: 1em; +} + +.tabwid table{ + border-spacing:0px !important; + border-collapse:collapse; + line-height:1; + margin-left:auto; + margin-right:auto; + border-width: 0; + border-color: transparent; + caption-side: top; +} +.tabwid-caption-bottom table{ + caption-side: bottom; +} +.tabwid_left table{ + margin-left:0; +} +.tabwid_right table{ + margin-right:0; +} +.tabwid td, .tabwid th { + padding: 0; +} +.tabwid a { + text-decoration: none; +} +.tabwid thead { + background-color: transparent; +} +.tabwid tfoot { + background-color: transparent; +} +.tabwid table tr { +background-color: transparent; +} +.katex-display { + margin: 0 0 !important; +} diff --git a/docs/articles/vanpaemel_vignette_files/tabwid-1.1.3/tabwid.js b/docs/articles/vanpaemel_vignette_files/tabwid-1.1.3/tabwid.js new file mode 100644 index 0000000..47070f7 --- /dev/null +++ b/docs/articles/vanpaemel_vignette_files/tabwid-1.1.3/tabwid.js @@ -0,0 +1,20 @@ +document.addEventListener("DOMContentLoaded", function(event) { + var els = document.querySelectorAll(".tabwid"); + var tabwid_link = document.querySelector('link[href*="tabwid.css"]') + if (tabwid_link === null) { + const tabwid_styles = document.evaluate("//style[contains(., 'tabwid')]", document, null, XPathResult.ANY_TYPE, null ); + tabwid_link = tabwid_styles.iterateNext(); + } + + Array.prototype.forEach.call(els, function(template) { + const dest = document.createElement("div"); + template.parentNode.insertBefore(dest, template.nextSibling) + dest.setAttribute("class", "flextable-shadow-host"); + const fantome = dest.attachShadow({mode: 'open'}); + fantome.appendChild(template); + if (tabwid_link !== null) { + fantome.appendChild(tabwid_link.cloneNode(true)); + } + }); +}); + diff --git a/docs/authors.html b/docs/authors.html new file mode 100644 index 0000000..d5ae871 --- /dev/null +++ b/docs/authors.html @@ -0,0 +1,98 @@ + +Authors and Citation • semanticprimeR + Skip to contents + + +
+
+
+

Authors and Citation

+
+ +
+

Authors

+ +
  • +

    Erin M. Buchanan. Author, maintainer. +

    +
    • +
+ +
+

Citation

+

+ +

Buchanan E (2023). +semanticprimeR: Semantic Priming Across Many Languages and Related Projects. +R package version 0.1.0, https://semanticpriming.github.io/semanticprimeR/. +

+ 
@Manual{,
+  title = {semanticprimeR: Semantic Priming Across Many Languages and Related Projects},
+  author = {Erin M. Buchanan},
+  year = {2023},
+  note = {R package version 0.1.0},
+  url = {https://semanticpriming.github.io/semanticprimeR/},
+}
+
+
+ + +
+ + + + + + + diff --git a/docs/deps/bootstrap-5.3.1/bootstrap.bundle.min.js b/docs/deps/bootstrap-5.3.1/bootstrap.bundle.min.js new file mode 100644 index 0000000..e8f21f7 --- /dev/null +++ b/docs/deps/bootstrap-5.3.1/bootstrap.bundle.min.js @@ -0,0 +1,7 @@ +/*! + * Bootstrap v5.3.1 (https://getbootstrap.com/) + * Copyright 2011-2023 The Bootstrap Authors (https://github.com/twbs/bootstrap/graphs/contributors) + * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE) + */ +!function(t,e){"object"==typeof exports&&"undefined"!=typeof module?module.exports=e():"function"==typeof define&&define.amd?define(e):(t="undefined"!=typeof globalThis?globalThis:t||self).bootstrap=e()}(this,(function(){"use strict";const t=new Map,e={set(e,i,n){t.has(e)||t.set(e,new Map);const s=t.get(e);s.has(i)||0===s.size?s.set(i,n):console.error(`Bootstrap doesn't allow more than one instance per element. 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this._getItems().indexOf(t)}_setActiveIndicatorElement(t){if(!this._indicatorsElement)return;const e=z.findOne(wt,this._indicatorsElement);e.classList.remove(yt),e.removeAttribute("aria-current");const i=z.findOne(`[data-bs-slide-to="${t}"]`,this._indicatorsElement);i&&(i.classList.add(yt),i.setAttribute("aria-current","true"))}_updateInterval(){const t=this._activeElement||this._getActive();if(!t)return;const e=Number.parseInt(t.getAttribute("data-bs-interval"),10);this._config.interval=e||this._config.defaultInterval}_slide(t,e=null){if(this._isSliding)return;const i=this._getActive(),n=t===at,s=e||b(this._getItems(),i,n,this._config.wrap);if(s===i)return;const o=this._getItemIndex(s),r=e=>N.trigger(this._element,e,{relatedTarget:s,direction:this._orderToDirection(t),from:this._getItemIndex(i),to:o});if(r(dt).defaultPrevented)return;if(!i||!s)return;const a=Boolean(this._interval);this.pause(),this._isSliding=!0,this._setActiveIndicatorElement(o),this._activeElement=s;const l=n?"carousel-item-start":"carousel-item-end",c=n?"carousel-item-next":"carousel-item-prev";s.classList.add(c),d(s),i.classList.add(l),s.classList.add(l),this._queueCallback((()=>{s.classList.remove(l,c),s.classList.add(yt),i.classList.remove(yt,c,l),this._isSliding=!1,r(ut)}),i,this._isAnimated()),a&&this.cycle()}_isAnimated(){return this._element.classList.contains("slide")}_getActive(){return z.findOne(Et,this._element)}_getItems(){return z.find(At,this._element)}_clearInterval(){this._interval&&(clearInterval(this._interval),this._interval=null)}_directionToOrder(t){return p()?t===ct?lt:at:t===ct?at:lt}_orderToDirection(t){return p()?t===lt?ct:ht:t===lt?ht:ct}static jQueryInterface(t){return this.each((function(){const e=xt.getOrCreateInstance(this,t);if("number"!=typeof t){if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t]()}}else e.to(t)}))}}N.on(document,bt,"[data-bs-slide], 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i=`scroll${e[0].toUpperCase()+e.slice(1)}`;this._queueCallback((()=>{this._isTransitioning=!1,this._element.classList.remove(Mt),this._element.classList.add(Pt,Nt),this._element.style[e]="",N.trigger(this._element,St)}),this._element,!0),this._element.style[e]=`${this._element[i]}px`}hide(){if(this._isTransitioning||!this._isShown())return;if(N.trigger(this._element,Dt).defaultPrevented)return;const t=this._getDimension();this._element.style[t]=`${this._element.getBoundingClientRect()[t]}px`,d(this._element),this._element.classList.add(Mt),this._element.classList.remove(Pt,Nt);for(const t of this._triggerArray){const e=z.getElementFromSelector(t);e&&!this._isShown(e)&&this._addAriaAndCollapsedClass([t],!1)}this._isTransitioning=!0,this._element.style[t]="",this._queueCallback((()=>{this._isTransitioning=!1,this._element.classList.remove(Mt),this._element.classList.add(Pt),N.trigger(this._element,$t)}),this._element,!0)}_isShown(t=this._element){return 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e=t.state,i=t.name,n=e.rects.reference,s=e.rects.popper,o=e.modifiersData.preventOverflow,r=ii(e,{elementContext:"reference"}),a=ii(e,{altBoundary:!0}),l=oi(r,n),c=oi(a,s,o),h=ri(l),d=ri(c);e.modifiersData[i]={referenceClippingOffsets:l,popperEscapeOffsets:c,isReferenceHidden:h,hasPopperEscaped:d},e.attributes.popper=Object.assign({},e.attributes.popper,{"data-popper-reference-hidden":h,"data-popper-escaped":d})}},li={name:"offset",enabled:!0,phase:"main",requires:["popperOffsets"],fn:function(t){var e=t.state,i=t.options,n=t.name,s=i.offset,o=void 0===s?[0,0]:s,r=ee.reduce((function(t,i){return t[i]=function(t,e,i){var n=be(t),s=[Vt,zt].indexOf(n)>=0?-1:1,o="function"==typeof i?i(Object.assign({},e,{placement:t})):i,r=o[0],a=o[1];return 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J,Z="x"===y?zt:Vt,tt="x"===y?Rt:qt,et=A[w],it="y"===w?"height":"width",nt=et+g[Z],st=et-g[tt],ot=-1!==[zt,Vt].indexOf(_),rt=null!=(J=null==x?void 0:x[w])?J:0,at=ot?nt:et-E[it]-T[it]-rt+O.altAxis,lt=ot?et+E[it]+T[it]-rt-O.altAxis:st,ct=f&&ot?function(t,e,i){var n=Ne(t,e,i);return n>i?i:n}(at,et,lt):Ne(f?at:nt,et,f?lt:st);A[w]=ct,k[w]=ct-et}e.modifiersData[n]=k}},requiresIfExists:["offset"]};function di(t,e,i){void 0===i&&(i=!1);var n,s,o=me(e),r=me(e)&&function(t){var e=t.getBoundingClientRect(),i=we(e.width)/t.offsetWidth||1,n=we(e.height)/t.offsetHeight||1;return 1!==i||1!==n}(e),a=Le(e),l=Te(t,r,i),c={scrollLeft:0,scrollTop:0},h={x:0,y:0};return(o||!o&&!i)&&(("body"!==ue(e)||Ue(a))&&(c=(n=e)!==fe(n)&&me(n)?{scrollLeft:(s=n).scrollLeft,scrollTop:s.scrollTop}:Xe(n)),me(e)?((h=Te(e,!0)).x+=e.clientLeft,h.y+=e.clientTop):a&&(h.x=Ye(a))),{x:l.left+c.scrollLeft-h.x,y:l.top+c.scrollTop-h.y,width:l.width,height:l.height}}function ui(t){var e=new Map,i=new Set,n=[];function s(t){i.add(t.name),[].concat(t.requires||[],t.requiresIfExists||[]).forEach((function(t){if(!i.has(t)){var n=e.get(t);n&&s(n)}})),n.push(t)}return t.forEach((function(t){e.set(t.name,t)})),t.forEach((function(t){i.has(t.name)||s(t)})),n}var fi={placement:"bottom",modifiers:[],strategy:"absolute"};function pi(){for(var t=arguments.length,e=new Array(t),i=0;iNumber.parseInt(t,10))):"function"==typeof t?e=>t(e,this._element):t}_getPopperConfig(){const t={placement:this._getPlacement(),modifiers:[{name:"preventOverflow",options:{boundary:this._config.boundary}},{name:"offset",options:{offset:this._getOffset()}}]};return(this._inNavbar||"static"===this._config.display)&&(F.setDataAttribute(this._menu,"popper","static"),t.modifiers=[{name:"applyStyles",enabled:!1}]),{...t,...g(this._config.popperConfig,[t])}}_selectMenuItem({key:t,target:e}){const i=z.find(".dropdown-menu 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e=/input|textarea/i.test(t.target.tagName),i="Escape"===t.key,n=[Ei,Ti].includes(t.key);if(!n&&!i)return;if(e&&!i)return;t.preventDefault();const s=this.matches(Ii)?this:z.prev(this,Ii)[0]||z.next(this,Ii)[0]||z.findOne(Ii,t.delegateTarget.parentNode),o=qi.getOrCreateInstance(s);if(n)return t.stopPropagation(),o.show(),void o._selectMenuItem(t);o._isShown()&&(t.stopPropagation(),o.hide(),s.focus())}}N.on(document,Si,Ii,qi.dataApiKeydownHandler),N.on(document,Si,Pi,qi.dataApiKeydownHandler),N.on(document,Li,qi.clearMenus),N.on(document,Di,qi.clearMenus),N.on(document,Li,Ii,(function(t){t.preventDefault(),qi.getOrCreateInstance(this).toggle()})),m(qi);const Vi="backdrop",Ki="show",Qi=`mousedown.bs.${Vi}`,Xi={className:"modal-backdrop",clickCallback:null,isAnimated:!1,isVisible:!0,rootElement:"body"},Yi={className:"string",clickCallback:"(function|null)",isAnimated:"boolean",isVisible:"boolean",rootElement:"(element|string)"};class Ui extends H{constructor(t){super(),this._config=this._getConfig(t),this._isAppended=!1,this._element=null}static get Default(){return Xi}static get DefaultType(){return Yi}static get NAME(){return Vi}show(t){if(!this._config.isVisible)return void g(t);this._append();const e=this._getElement();this._config.isAnimated&&d(e),e.classList.add(Ki),this._emulateAnimation((()=>{g(t)}))}hide(t){this._config.isVisible?(this._getElement().classList.remove(Ki),this._emulateAnimation((()=>{this.dispose(),g(t)}))):g(t)}dispose(){this._isAppended&&(N.off(this._element,Qi),this._element.remove(),this._isAppended=!1)}_getElement(){if(!this._element){const t=document.createElement("div");t.className=this._config.className,this._config.isAnimated&&t.classList.add("fade"),this._element=t}return this._element}_configAfterMerge(t){return t.rootElement=r(t.rootElement),t}_append(){if(this._isAppended)return;const t=this._getElement();this._config.rootElement.append(t),N.on(t,Qi,(()=>{g(this._config.clickCallback)})),this._isAppended=!0}_emulateAnimation(t){_(t,this._getElement(),this._config.isAnimated)}}const Gi=".bs.focustrap",Ji=`focusin${Gi}`,Zi=`keydown.tab${Gi}`,tn="backward",en={autofocus:!0,trapElement:null},nn={autofocus:"boolean",trapElement:"element"};class sn extends H{constructor(t){super(),this._config=this._getConfig(t),this._isActive=!1,this._lastTabNavDirection=null}static get Default(){return en}static get DefaultType(){return nn}static get NAME(){return"focustrap"}activate(){this._isActive||(this._config.autofocus&&this._config.trapElement.focus(),N.off(document,Gi),N.on(document,Ji,(t=>this._handleFocusin(t))),N.on(document,Zi,(t=>this._handleKeydown(t))),this._isActive=!0)}deactivate(){this._isActive&&(this._isActive=!1,N.off(document,Gi))}_handleFocusin(t){const{trapElement:e}=this._config;if(t.target===document||t.target===e||e.contains(t.target))return;const i=z.focusableChildren(e);0===i.length?e.focus():this._lastTabNavDirection===tn?i[i.length-1].focus():i[0].focus()}_handleKeydown(t){"Tab"===t.key&&(this._lastTabNavDirection=t.shiftKey?tn:"forward")}}const on=".fixed-top, .fixed-bottom, .is-fixed, .sticky-top",rn=".sticky-top",an="padding-right",ln="margin-right";class cn{constructor(){this._element=document.body}getWidth(){const t=document.documentElement.clientWidth;return Math.abs(window.innerWidth-t)}hide(){const t=this.getWidth();this._disableOverFlow(),this._setElementAttributes(this._element,an,(e=>e+t)),this._setElementAttributes(on,an,(e=>e+t)),this._setElementAttributes(rn,ln,(e=>e-t))}reset(){this._resetElementAttributes(this._element,"overflow"),this._resetElementAttributes(this._element,an),this._resetElementAttributes(on,an),this._resetElementAttributes(rn,ln)}isOverflowing(){return this.getWidth()>0}_disableOverFlow(){this._saveInitialAttribute(this._element,"overflow"),this._element.style.overflow="hidden"}_setElementAttributes(t,e,i){const n=this.getWidth();this._applyManipulationCallback(t,(t=>{if(t!==this._element&&window.innerWidth>t.clientWidth+n)return;this._saveInitialAttribute(t,e);const s=window.getComputedStyle(t).getPropertyValue(e);t.style.setProperty(e,`${i(Number.parseFloat(s))}px`)}))}_saveInitialAttribute(t,e){const i=t.style.getPropertyValue(e);i&&F.setDataAttribute(t,e,i)}_resetElementAttributes(t,e){this._applyManipulationCallback(t,(t=>{const i=F.getDataAttribute(t,e);null!==i?(F.removeDataAttribute(t,e),t.style.setProperty(e,i)):t.style.removeProperty(e)}))}_applyManipulationCallback(t,e){if(o(t))e(t);else for(const i of z.find(t,this._element))e(i)}}const hn=".bs.modal",dn=`hide${hn}`,un=`hidePrevented${hn}`,fn=`hidden${hn}`,pn=`show${hn}`,mn=`shown${hn}`,gn=`resize${hn}`,_n=`click.dismiss${hn}`,bn=`mousedown.dismiss${hn}`,vn=`keydown.dismiss${hn}`,yn=`click${hn}.data-api`,wn="modal-open",An="show",En="modal-static",Tn={backdrop:!0,focus:!0,keyboard:!0},Cn={backdrop:"(boolean|string)",focus:"boolean",keyboard:"boolean"};class On extends W{constructor(t,e){super(t,e),this._dialog=z.findOne(".modal-dialog",this._element),this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._isShown=!1,this._isTransitioning=!1,this._scrollBar=new cn,this._addEventListeners()}static get Default(){return Tn}static get DefaultType(){return Cn}static get NAME(){return"modal"}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||this._isTransitioning||N.trigger(this._element,pn,{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._isTransitioning=!0,this._scrollBar.hide(),document.body.classList.add(wn),this._adjustDialog(),this._backdrop.show((()=>this._showElement(t))))}hide(){this._isShown&&!this._isTransitioning&&(N.trigger(this._element,dn).defaultPrevented||(this._isShown=!1,this._isTransitioning=!0,this._focustrap.deactivate(),this._element.classList.remove(An),this._queueCallback((()=>this._hideModal()),this._element,this._isAnimated())))}dispose(){N.off(window,hn),N.off(this._dialog,hn),this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}handleUpdate(){this._adjustDialog()}_initializeBackDrop(){return new Ui({isVisible:Boolean(this._config.backdrop),isAnimated:this._isAnimated()})}_initializeFocusTrap(){return new sn({trapElement:this._element})}_showElement(t){document.body.contains(this._element)||document.body.append(this._element),this._element.style.display="block",this._element.removeAttribute("aria-hidden"),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.scrollTop=0;const e=z.findOne(".modal-body",this._dialog);e&&(e.scrollTop=0),d(this._element),this._element.classList.add(An),this._queueCallback((()=>{this._config.focus&&this._focustrap.activate(),this._isTransitioning=!1,N.trigger(this._element,mn,{relatedTarget:t})}),this._dialog,this._isAnimated())}_addEventListeners(){N.on(this._element,vn,(t=>{"Escape"===t.key&&(this._config.keyboard?this.hide():this._triggerBackdropTransition())})),N.on(window,gn,(()=>{this._isShown&&!this._isTransitioning&&this._adjustDialog()})),N.on(this._element,bn,(t=>{N.one(this._element,_n,(e=>{this._element===t.target&&this._element===e.target&&("static"!==this._config.backdrop?this._config.backdrop&&this.hide():this._triggerBackdropTransition())}))}))}_hideModal(){this._element.style.display="none",this._element.setAttribute("aria-hidden",!0),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._isTransitioning=!1,this._backdrop.hide((()=>{document.body.classList.remove(wn),this._resetAdjustments(),this._scrollBar.reset(),N.trigger(this._element,fn)}))}_isAnimated(){return this._element.classList.contains("fade")}_triggerBackdropTransition(){if(N.trigger(this._element,un).defaultPrevented)return;const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._element.style.overflowY;"hidden"===e||this._element.classList.contains(En)||(t||(this._element.style.overflowY="hidden"),this._element.classList.add(En),this._queueCallback((()=>{this._element.classList.remove(En),this._queueCallback((()=>{this._element.style.overflowY=e}),this._dialog)}),this._dialog),this._element.focus())}_adjustDialog(){const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._scrollBar.getWidth(),i=e>0;if(i&&!t){const t=p()?"paddingLeft":"paddingRight";this._element.style[t]=`${e}px`}if(!i&&t){const t=p()?"paddingRight":"paddingLeft";this._element.style[t]=`${e}px`}}_resetAdjustments(){this._element.style.paddingLeft="",this._element.style.paddingRight=""}static jQueryInterface(t,e){return this.each((function(){const i=On.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===i[t])throw new TypeError(`No method named "${t}"`);i[t](e)}}))}}N.on(document,yn,'[data-bs-toggle="modal"]',(function(t){const e=z.getElementFromSelector(this);["A","AREA"].includes(this.tagName)&&t.preventDefault(),N.one(e,pn,(t=>{t.defaultPrevented||N.one(e,fn,(()=>{a(this)&&this.focus()}))}));const i=z.findOne(".modal.show");i&&On.getInstance(i).hide(),On.getOrCreateInstance(e).toggle(this)})),R(On),m(On);const xn=".bs.offcanvas",kn=".data-api",Ln=`load${xn}${kn}`,Sn="show",Dn="showing",$n="hiding",In=".offcanvas.show",Nn=`show${xn}`,Pn=`shown${xn}`,Mn=`hide${xn}`,jn=`hidePrevented${xn}`,Fn=`hidden${xn}`,Hn=`resize${xn}`,Wn=`click${xn}${kn}`,Bn=`keydown.dismiss${xn}`,zn={backdrop:!0,keyboard:!0,scroll:!1},Rn={backdrop:"(boolean|string)",keyboard:"boolean",scroll:"boolean"};class qn extends W{constructor(t,e){super(t,e),this._isShown=!1,this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._addEventListeners()}static get Default(){return zn}static get DefaultType(){return Rn}static get NAME(){return"offcanvas"}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||N.trigger(this._element,Nn,{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._backdrop.show(),this._config.scroll||(new cn).hide(),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.classList.add(Dn),this._queueCallback((()=>{this._config.scroll&&!this._config.backdrop||this._focustrap.activate(),this._element.classList.add(Sn),this._element.classList.remove(Dn),N.trigger(this._element,Pn,{relatedTarget:t})}),this._element,!0))}hide(){this._isShown&&(N.trigger(this._element,Mn).defaultPrevented||(this._focustrap.deactivate(),this._element.blur(),this._isShown=!1,this._element.classList.add($n),this._backdrop.hide(),this._queueCallback((()=>{this._element.classList.remove(Sn,$n),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._config.scroll||(new cn).reset(),N.trigger(this._element,Fn)}),this._element,!0)))}dispose(){this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}_initializeBackDrop(){const t=Boolean(this._config.backdrop);return new Ui({className:"offcanvas-backdrop",isVisible:t,isAnimated:!0,rootElement:this._element.parentNode,clickCallback:t?()=>{"static"!==this._config.backdrop?this.hide():N.trigger(this._element,jn)}:null})}_initializeFocusTrap(){return new sn({trapElement:this._element})}_addEventListeners(){N.on(this._element,Bn,(t=>{"Escape"===t.key&&(this._config.keyboard?this.hide():N.trigger(this._element,jn))}))}static jQueryInterface(t){return this.each((function(){const e=qn.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t](this)}}))}}N.on(document,Wn,'[data-bs-toggle="offcanvas"]',(function(t){const e=z.getElementFromSelector(this);if(["A","AREA"].includes(this.tagName)&&t.preventDefault(),l(this))return;N.one(e,Fn,(()=>{a(this)&&this.focus()}));const i=z.findOne(In);i&&i!==e&&qn.getInstance(i).hide(),qn.getOrCreateInstance(e).toggle(this)})),N.on(window,Ln,(()=>{for(const t of z.find(In))qn.getOrCreateInstance(t).show()})),N.on(window,Hn,(()=>{for(const t of z.find("[aria-modal][class*=show][class*=offcanvas-]"))"fixed"!==getComputedStyle(t).position&&qn.getOrCreateInstance(t).hide()})),R(qn),m(qn);const Vn={"*":["class","dir","id","lang","role",/^aria-[\w-]*$/i],a:["target","href","title","rel"],area:[],b:[],br:[],col:[],code:[],div:[],em:[],hr:[],h1:[],h2:[],h3:[],h4:[],h5:[],h6:[],i:[],img:["src","srcset","alt","title","width","height"],li:[],ol:[],p:[],pre:[],s:[],small:[],span:[],sub:[],sup:[],strong:[],u:[],ul:[]},Kn=new Set(["background","cite","href","itemtype","longdesc","poster","src","xlink:href"]),Qn=/^(?!javascript:)(?:[a-z0-9+.-]+:|[^&:/?#]*(?:[/?#]|$))/i,Xn=(t,e)=>{const i=t.nodeName.toLowerCase();return e.includes(i)?!Kn.has(i)||Boolean(Qn.test(t.nodeValue)):e.filter((t=>t instanceof RegExp)).some((t=>t.test(i)))},Yn={allowList:Vn,content:{},extraClass:"",html:!1,sanitize:!0,sanitizeFn:null,template:"
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")),e}_typeCheckConfig(t){super._typeCheckConfig(t),this._checkContent(t.content)}_checkContent(t){for(const[e,i]of Object.entries(t))super._typeCheckConfig({selector:e,entry:i},Gn)}_setContent(t,e,i){const n=z.findOne(i,t);n&&((e=this._resolvePossibleFunction(e))?o(e)?this._putElementInTemplate(r(e),n):this._config.html?n.innerHTML=this._maybeSanitize(e):n.textContent=e:n.remove())}_maybeSanitize(t){return this._config.sanitize?function(t,e,i){if(!t.length)return t;if(i&&"function"==typeof i)return i(t);const n=(new window.DOMParser).parseFromString(t,"text/html"),s=[].concat(...n.body.querySelectorAll("*"));for(const t of s){const i=t.nodeName.toLowerCase();if(!Object.keys(e).includes(i)){t.remove();continue}const n=[].concat(...t.attributes),s=[].concat(e["*"]||[],e[i]||[]);for(const e of n)Xn(e,s)||t.removeAttribute(e.nodeName)}return n.body.innerHTML}(t,this._config.allowList,this._config.sanitizeFn):t}_resolvePossibleFunction(t){return g(t,[this])}_putElementInTemplate(t,e){if(this._config.html)return e.innerHTML="",void e.append(t);e.textContent=t.textContent}}const Zn=new Set(["sanitize","allowList","sanitizeFn"]),ts="fade",es="show",is=".modal",ns="hide.bs.modal",ss="hover",os="focus",rs={AUTO:"auto",TOP:"top",RIGHT:p()?"left":"right",BOTTOM:"bottom",LEFT:p()?"right":"left"},as={allowList:Vn,animation:!0,boundary:"clippingParents",container:!1,customClass:"",delay:0,fallbackPlacements:["top","right","bottom","left"],html:!1,offset:[0,6],placement:"top",popperConfig:null,sanitize:!0,sanitizeFn:null,selector:!1,template:'',title:"",trigger:"hover focus"},ls={allowList:"object",animation:"boolean",boundary:"(string|element)",container:"(string|element|boolean)",customClass:"(string|function)",delay:"(number|object)",fallbackPlacements:"array",html:"boolean",offset:"(array|string|function)",placement:"(string|function)",popperConfig:"(null|object|function)",sanitize:"boolean",sanitizeFn:"(null|function)",selector:"(string|boolean)",template:"string",title:"(string|element|function)",trigger:"string"};class cs extends W{constructor(t,e){if(void 0===vi)throw new TypeError("Bootstrap's tooltips require Popper (https://popper.js.org)");super(t,e),this._isEnabled=!0,this._timeout=0,this._isHovered=null,this._activeTrigger={},this._popper=null,this._templateFactory=null,this._newContent=null,this.tip=null,this._setListeners(),this._config.selector||this._fixTitle()}static get Default(){return as}static get DefaultType(){return ls}static get NAME(){return"tooltip"}enable(){this._isEnabled=!0}disable(){this._isEnabled=!1}toggleEnabled(){this._isEnabled=!this._isEnabled}toggle(){this._isEnabled&&(this._activeTrigger.click=!this._activeTrigger.click,this._isShown()?this._leave():this._enter())}dispose(){clearTimeout(this._timeout),N.off(this._element.closest(is),ns,this._hideModalHandler),this._element.getAttribute("data-bs-original-title")&&this._element.setAttribute("title",this._element.getAttribute("data-bs-original-title")),this._disposePopper(),super.dispose()}show(){if("none"===this._element.style.display)throw new Error("Please use show on visible elements");if(!this._isWithContent()||!this._isEnabled)return;const t=N.trigger(this._element,this.constructor.eventName("show")),e=(c(this._element)||this._element.ownerDocument.documentElement).contains(this._element);if(t.defaultPrevented||!e)return;this._disposePopper();const i=this._getTipElement();this._element.setAttribute("aria-describedby",i.getAttribute("id"));const{container:n}=this._config;if(this._element.ownerDocument.documentElement.contains(this.tip)||(n.append(i),N.trigger(this._element,this.constructor.eventName("inserted"))),this._popper=this._createPopper(i),i.classList.add(es),"ontouchstart"in document.documentElement)for(const t of[].concat(...document.body.children))N.on(t,"mouseover",h);this._queueCallback((()=>{N.trigger(this._element,this.constructor.eventName("shown")),!1===this._isHovered&&this._leave(),this._isHovered=!1}),this.tip,this._isAnimated())}hide(){if(this._isShown()&&!N.trigger(this._element,this.constructor.eventName("hide")).defaultPrevented){if(this._getTipElement().classList.remove(es),"ontouchstart"in document.documentElement)for(const t of[].concat(...document.body.children))N.off(t,"mouseover",h);this._activeTrigger.click=!1,this._activeTrigger[os]=!1,this._activeTrigger[ss]=!1,this._isHovered=null,this._queueCallback((()=>{this._isWithActiveTrigger()||(this._isHovered||this._disposePopper(),this._element.removeAttribute("aria-describedby"),N.trigger(this._element,this.constructor.eventName("hidden")))}),this.tip,this._isAnimated())}}update(){this._popper&&this._popper.update()}_isWithContent(){return Boolean(this._getTitle())}_getTipElement(){return this.tip||(this.tip=this._createTipElement(this._newContent||this._getContentForTemplate())),this.tip}_createTipElement(t){const e=this._getTemplateFactory(t).toHtml();if(!e)return null;e.classList.remove(ts,es),e.classList.add(`bs-${this.constructor.NAME}-auto`);const i=(t=>{do{t+=Math.floor(1e6*Math.random())}while(document.getElementById(t));return t})(this.constructor.NAME).toString();return e.setAttribute("id",i),this._isAnimated()&&e.classList.add(ts),e}setContent(t){this._newContent=t,this._isShown()&&(this._disposePopper(),this.show())}_getTemplateFactory(t){return this._templateFactory?this._templateFactory.changeContent(t):this._templateFactory=new Jn({...this._config,content:t,extraClass:this._resolvePossibleFunction(this._config.customClass)}),this._templateFactory}_getContentForTemplate(){return{".tooltip-inner":this._getTitle()}}_getTitle(){return this._resolvePossibleFunction(this._config.title)||this._element.getAttribute("data-bs-original-title")}_initializeOnDelegatedTarget(t){return this.constructor.getOrCreateInstance(t.delegateTarget,this._getDelegateConfig())}_isAnimated(){return this._config.animation||this.tip&&this.tip.classList.contains(ts)}_isShown(){return this.tip&&this.tip.classList.contains(es)}_createPopper(t){const e=g(this._config.placement,[this,t,this._element]),i=rs[e.toUpperCase()];return bi(this._element,t,this._getPopperConfig(i))}_getOffset(){const{offset:t}=this._config;return"string"==typeof t?t.split(",").map((t=>Number.parseInt(t,10))):"function"==typeof t?e=>t(e,this._element):t}_resolvePossibleFunction(t){return g(t,[this._element])}_getPopperConfig(t){const e={placement:t,modifiers:[{name:"flip",options:{fallbackPlacements:this._config.fallbackPlacements}},{name:"offset",options:{offset:this._getOffset()}},{name:"preventOverflow",options:{boundary:this._config.boundary}},{name:"arrow",options:{element:`.${this.constructor.NAME}-arrow`}},{name:"preSetPlacement",enabled:!0,phase:"beforeMain",fn:t=>{this._getTipElement().setAttribute("data-popper-placement",t.state.placement)}}]};return{...e,...g(this._config.popperConfig,[e])}}_setListeners(){const t=this._config.trigger.split(" ");for(const e of t)if("click"===e)N.on(this._element,this.constructor.eventName("click"),this._config.selector,(t=>{this._initializeOnDelegatedTarget(t).toggle()}));else if("manual"!==e){const t=e===ss?this.constructor.eventName("mouseenter"):this.constructor.eventName("focusin"),i=e===ss?this.constructor.eventName("mouseleave"):this.constructor.eventName("focusout");N.on(this._element,t,this._config.selector,(t=>{const e=this._initializeOnDelegatedTarget(t);e._activeTrigger["focusin"===t.type?os:ss]=!0,e._enter()})),N.on(this._element,i,this._config.selector,(t=>{const e=this._initializeOnDelegatedTarget(t);e._activeTrigger["focusout"===t.type?os:ss]=e._element.contains(t.relatedTarget),e._leave()}))}this._hideModalHandler=()=>{this._element&&this.hide()},N.on(this._element.closest(is),ns,this._hideModalHandler)}_fixTitle(){const t=this._element.getAttribute("title");t&&(this._element.getAttribute("aria-label")||this._element.textContent.trim()||this._element.setAttribute("aria-label",t),this._element.setAttribute("data-bs-original-title",t),this._element.removeAttribute("title"))}_enter(){this._isShown()||this._isHovered?this._isHovered=!0:(this._isHovered=!0,this._setTimeout((()=>{this._isHovered&&this.show()}),this._config.delay.show))}_leave(){this._isWithActiveTrigger()||(this._isHovered=!1,this._setTimeout((()=>{this._isHovered||this.hide()}),this._config.delay.hide))}_setTimeout(t,e){clearTimeout(this._timeout),this._timeout=setTimeout(t,e)}_isWithActiveTrigger(){return Object.values(this._activeTrigger).includes(!0)}_getConfig(t){const e=F.getDataAttributes(this._element);for(const t of Object.keys(e))Zn.has(t)&&delete e[t];return t={...e,..."object"==typeof t&&t?t:{}},t=this._mergeConfigObj(t),t=this._configAfterMerge(t),this._typeCheckConfig(t),t}_configAfterMerge(t){return t.container=!1===t.container?document.body:r(t.container),"number"==typeof t.delay&&(t.delay={show:t.delay,hide:t.delay}),"number"==typeof t.title&&(t.title=t.title.toString()),"number"==typeof t.content&&(t.content=t.content.toString()),t}_getDelegateConfig(){const t={};for(const[e,i]of Object.entries(this._config))this.constructor.Default[e]!==i&&(t[e]=i);return t.selector=!1,t.trigger="manual",t}_disposePopper(){this._popper&&(this._popper.destroy(),this._popper=null),this.tip&&(this.tip.remove(),this.tip=null)}static jQueryInterface(t){return this.each((function(){const e=cs.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}}m(cs);const hs={...cs.Default,content:"",offset:[0,8],placement:"right",template:'',trigger:"click"},ds={...cs.DefaultType,content:"(null|string|element|function)"};class us extends cs{static get Default(){return hs}static get DefaultType(){return ds}static get NAME(){return"popover"}_isWithContent(){return this._getTitle()||this._getContent()}_getContentForTemplate(){return{".popover-header":this._getTitle(),".popover-body":this._getContent()}}_getContent(){return this._resolvePossibleFunction(this._config.content)}static jQueryInterface(t){return this.each((function(){const e=us.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}}m(us);const fs=".bs.scrollspy",ps=`activate${fs}`,ms=`click${fs}`,gs=`load${fs}.data-api`,_s="active",bs="[href]",vs=".nav-link",ys=`${vs}, .nav-item > ${vs}, .list-group-item`,ws={offset:null,rootMargin:"0px 0px -25%",smoothScroll:!1,target:null,threshold:[.1,.5,1]},As={offset:"(number|null)",rootMargin:"string",smoothScroll:"boolean",target:"element",threshold:"array"};class Es extends W{constructor(t,e){super(t,e),this._targetLinks=new Map,this._observableSections=new 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e=this._observableSections.get(t.target.hash);if(e){t.preventDefault();const i=this._rootElement||window,n=e.offsetTop-this._element.offsetTop;if(i.scrollTo)return void i.scrollTo({top:n,behavior:"smooth"});i.scrollTop=n}})))}_getNewObserver(){const t={root:this._rootElement,threshold:this._config.threshold,rootMargin:this._config.rootMargin};return new IntersectionObserver((t=>this._observerCallback(t)),t)}_observerCallback(t){const e=t=>this._targetLinks.get(`#${t.target.id}`),i=t=>{this._previousScrollData.visibleEntryTop=t.target.offsetTop,this._process(e(t))},n=(this._rootElement||document.documentElement).scrollTop,s=n>=this._previousScrollData.parentScrollTop;this._previousScrollData.parentScrollTop=n;for(const o of t){if(!o.isIntersecting){this._activeTarget=null,this._clearActiveClass(e(o));continue}const t=o.target.offsetTop>=this._previousScrollData.visibleEntryTop;if(s&&t){if(i(o),!n)return}else s||t||i(o)}}_initializeTargetsAndObservables(){this._targetLinks=new Map,this._observableSections=new Map;const t=z.find(bs,this._config.target);for(const e of t){if(!e.hash||l(e))continue;const t=z.findOne(decodeURI(e.hash),this._element);a(t)&&(this._targetLinks.set(decodeURI(e.hash),e),this._observableSections.set(e.hash,t))}}_process(t){this._activeTarget!==t&&(this._clearActiveClass(this._config.target),this._activeTarget=t,t.classList.add(_s),this._activateParents(t),N.trigger(this._element,ps,{relatedTarget:t}))}_activateParents(t){if(t.classList.contains("dropdown-item"))z.findOne(".dropdown-toggle",t.closest(".dropdown")).classList.add(_s);else for(const e of z.parents(t,".nav, .list-group"))for(const t of z.prev(e,ys))t.classList.add(_s)}_clearActiveClass(t){t.classList.remove(_s);const e=z.find(`${bs}.${_s}`,t);for(const t of e)t.classList.remove(_s)}static jQueryInterface(t){return this.each((function(){const e=Es.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No 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* --------------------------------------------------------------------------\n * Bootstrap dom/data.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n/**\n * Constants\n */\n\nconst elementMap = new Map()\n\nexport default {\n set(element, key, instance) {\n if (!elementMap.has(element)) {\n elementMap.set(element, new Map())\n }\n\n const instanceMap = elementMap.get(element)\n\n // make it clear we only want one instance per element\n // can be removed later when multiple key/instances are fine to be used\n if (!instanceMap.has(key) && instanceMap.size !== 0) {\n // eslint-disable-next-line no-console\n console.error(`Bootstrap doesn't allow more than one instance per element. Bound instance: ${Array.from(instanceMap.keys())[0]}.`)\n return\n }\n\n instanceMap.set(key, instance)\n },\n\n get(element, key) {\n if (elementMap.has(element)) {\n return elementMap.get(element).get(key) || null\n }\n\n return null\n },\n\n remove(element, key) {\n if (!elementMap.has(element)) {\n return\n }\n\n const instanceMap = elementMap.get(element)\n\n instanceMap.delete(key)\n\n // free up element references if there are no instances left for an element\n if (instanceMap.size === 0) {\n elementMap.delete(element)\n }\n }\n}\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap util/index.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nconst MAX_UID = 1_000_000\nconst MILLISECONDS_MULTIPLIER = 1000\nconst TRANSITION_END = 'transitionend'\n\n/**\n * Properly escape IDs selectors to handle weird IDs\n * @param {string} selector\n * @returns {string}\n */\nconst parseSelector = selector => {\n if (selector && window.CSS && window.CSS.escape) {\n // document.querySelector needs escaping to handle IDs (html5+) containing for instance /\n selector = selector.replace(/#([^\\s\"#']+)/g, (match, id) => `#${CSS.escape(id)}`)\n }\n\n return selector\n}\n\n// Shout-out Angus Croll (https://goo.gl/pxwQGp)\nconst toType = object => {\n if (object === null || object === undefined) {\n return `${object}`\n }\n\n return Object.prototype.toString.call(object).match(/\\s([a-z]+)/i)[1].toLowerCase()\n}\n\n/**\n * Public Util API\n */\n\nconst getUID = prefix => {\n do {\n prefix += Math.floor(Math.random() * MAX_UID)\n } while (document.getElementById(prefix))\n\n return prefix\n}\n\nconst getTransitionDurationFromElement = element => {\n if (!element) {\n return 0\n }\n\n // Get transition-duration of the element\n let { transitionDuration, transitionDelay } = window.getComputedStyle(element)\n\n const floatTransitionDuration = Number.parseFloat(transitionDuration)\n const floatTransitionDelay = Number.parseFloat(transitionDelay)\n\n // Return 0 if element or transition duration is not found\n if (!floatTransitionDuration && !floatTransitionDelay) {\n return 0\n }\n\n // If multiple durations are defined, take the first\n transitionDuration = transitionDuration.split(',')[0]\n transitionDelay = transitionDelay.split(',')[0]\n\n return (Number.parseFloat(transitionDuration) + Number.parseFloat(transitionDelay)) * MILLISECONDS_MULTIPLIER\n}\n\nconst triggerTransitionEnd = element => {\n element.dispatchEvent(new Event(TRANSITION_END))\n}\n\nconst isElement = object => {\n if (!object || typeof object !== 'object') {\n return false\n }\n\n if (typeof object.jquery !== 'undefined') {\n object = object[0]\n }\n\n return typeof object.nodeType !== 'undefined'\n}\n\nconst getElement = object => {\n // it's a jQuery object or a node element\n if (isElement(object)) {\n return object.jquery ? object[0] : object\n }\n\n if (typeof object === 'string' && object.length > 0) {\n return document.querySelector(parseSelector(object))\n }\n\n return null\n}\n\nconst isVisible = element => {\n if (!isElement(element) || element.getClientRects().length === 0) {\n return false\n }\n\n const elementIsVisible = getComputedStyle(element).getPropertyValue('visibility') === 'visible'\n // Handle `details` element as its content may falsie appear visible when it is closed\n const closedDetails = element.closest('details:not([open])')\n\n if (!closedDetails) {\n return elementIsVisible\n }\n\n if (closedDetails !== element) {\n const summary = element.closest('summary')\n if (summary && summary.parentNode !== closedDetails) {\n return false\n }\n\n if (summary === null) {\n return false\n }\n }\n\n return elementIsVisible\n}\n\nconst isDisabled = element => {\n if (!element || element.nodeType !== Node.ELEMENT_NODE) {\n return true\n }\n\n if (element.classList.contains('disabled')) {\n return true\n }\n\n if (typeof element.disabled !== 'undefined') {\n return element.disabled\n }\n\n return element.hasAttribute('disabled') && element.getAttribute('disabled') !== 'false'\n}\n\nconst findShadowRoot = element => {\n if (!document.documentElement.attachShadow) {\n return null\n }\n\n // Can find the shadow root otherwise it'll return the document\n if (typeof element.getRootNode === 'function') {\n const root = element.getRootNode()\n return root instanceof ShadowRoot ? root : null\n }\n\n if (element instanceof ShadowRoot) {\n return element\n }\n\n // when we don't find a shadow root\n if (!element.parentNode) {\n return null\n }\n\n return findShadowRoot(element.parentNode)\n}\n\nconst noop = () => {}\n\n/**\n * Trick to restart an element's animation\n *\n * @param {HTMLElement} element\n * @return void\n *\n * @see https://www.charistheo.io/blog/2021/02/restart-a-css-animation-with-javascript/#restarting-a-css-animation\n */\nconst reflow = element => {\n element.offsetHeight // eslint-disable-line no-unused-expressions\n}\n\nconst getjQuery = () => {\n if (window.jQuery && !document.body.hasAttribute('data-bs-no-jquery')) {\n return window.jQuery\n }\n\n return null\n}\n\nconst DOMContentLoadedCallbacks = []\n\nconst onDOMContentLoaded = callback => {\n if (document.readyState === 'loading') {\n // add listener on the first call when the document is in loading state\n if (!DOMContentLoadedCallbacks.length) {\n document.addEventListener('DOMContentLoaded', () => {\n for (const callback of DOMContentLoadedCallbacks) {\n callback()\n }\n })\n }\n\n DOMContentLoadedCallbacks.push(callback)\n } else {\n callback()\n }\n}\n\nconst isRTL = () => document.documentElement.dir === 'rtl'\n\nconst defineJQueryPlugin = plugin => {\n onDOMContentLoaded(() => {\n const $ = getjQuery()\n /* istanbul ignore if */\n if ($) {\n const name = plugin.NAME\n const JQUERY_NO_CONFLICT = $.fn[name]\n $.fn[name] = plugin.jQueryInterface\n $.fn[name].Constructor = plugin\n $.fn[name].noConflict = () => {\n $.fn[name] = JQUERY_NO_CONFLICT\n return plugin.jQueryInterface\n }\n }\n })\n}\n\nconst execute = (possibleCallback, args = [], defaultValue = possibleCallback) => {\n return typeof possibleCallback === 'function' ? possibleCallback(...args) : defaultValue\n}\n\nconst executeAfterTransition = (callback, transitionElement, waitForTransition = true) => {\n if (!waitForTransition) {\n execute(callback)\n return\n }\n\n const durationPadding = 5\n const emulatedDuration = getTransitionDurationFromElement(transitionElement) + durationPadding\n\n let called = false\n\n const handler = ({ target }) => {\n if (target !== transitionElement) {\n return\n }\n\n called = true\n transitionElement.removeEventListener(TRANSITION_END, handler)\n execute(callback)\n }\n\n transitionElement.addEventListener(TRANSITION_END, handler)\n setTimeout(() => {\n if (!called) {\n triggerTransitionEnd(transitionElement)\n }\n }, emulatedDuration)\n}\n\n/**\n * Return the previous/next element of a list.\n *\n * @param {array} list The list of elements\n * @param activeElement The active element\n * @param shouldGetNext Choose to get next or previous element\n * @param isCycleAllowed\n * @return {Element|elem} The proper element\n */\nconst getNextActiveElement = (list, activeElement, shouldGetNext, isCycleAllowed) => {\n const listLength = list.length\n let index = list.indexOf(activeElement)\n\n // if the element does not exist in the list return an element\n // depending on the direction and if cycle is allowed\n if (index === -1) {\n return !shouldGetNext && isCycleAllowed ? list[listLength - 1] : list[0]\n }\n\n index += shouldGetNext ? 1 : -1\n\n if (isCycleAllowed) {\n index = (index + listLength) % listLength\n }\n\n return list[Math.max(0, Math.min(index, listLength - 1))]\n}\n\nexport {\n defineJQueryPlugin,\n execute,\n executeAfterTransition,\n findShadowRoot,\n getElement,\n getjQuery,\n getNextActiveElement,\n getTransitionDurationFromElement,\n getUID,\n isDisabled,\n isElement,\n isRTL,\n isVisible,\n noop,\n onDOMContentLoaded,\n parseSelector,\n reflow,\n triggerTransitionEnd,\n toType\n}\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap dom/event-handler.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport { getjQuery } from '../util/index.js'\n\n/**\n * Constants\n */\n\nconst namespaceRegex = /[^.]*(?=\\..*)\\.|.*/\nconst stripNameRegex = /\\..*/\nconst stripUidRegex = /::\\d+$/\nconst eventRegistry = {} // Events storage\nlet uidEvent = 1\nconst customEvents = {\n mouseenter: 'mouseover',\n mouseleave: 'mouseout'\n}\n\nconst nativeEvents = new Set([\n 'click',\n 'dblclick',\n 'mouseup',\n 'mousedown',\n 'contextmenu',\n 'mousewheel',\n 'DOMMouseScroll',\n 'mouseover',\n 'mouseout',\n 'mousemove',\n 'selectstart',\n 'selectend',\n 'keydown',\n 'keypress',\n 'keyup',\n 'orientationchange',\n 'touchstart',\n 'touchmove',\n 'touchend',\n 'touchcancel',\n 'pointerdown',\n 'pointermove',\n 'pointerup',\n 'pointerleave',\n 'pointercancel',\n 'gesturestart',\n 'gesturechange',\n 'gestureend',\n 'focus',\n 'blur',\n 'change',\n 'reset',\n 'select',\n 'submit',\n 'focusin',\n 'focusout',\n 'load',\n 'unload',\n 'beforeunload',\n 'resize',\n 'move',\n 'DOMContentLoaded',\n 'readystatechange',\n 'error',\n 'abort',\n 'scroll'\n])\n\n/**\n * Private methods\n */\n\nfunction makeEventUid(element, uid) {\n return (uid && `${uid}::${uidEvent++}`) || element.uidEvent || uidEvent++\n}\n\nfunction getElementEvents(element) {\n const uid = makeEventUid(element)\n\n element.uidEvent = uid\n eventRegistry[uid] = eventRegistry[uid] || {}\n\n return eventRegistry[uid]\n}\n\nfunction bootstrapHandler(element, fn) {\n return function handler(event) {\n hydrateObj(event, { delegateTarget: element })\n\n if (handler.oneOff) {\n EventHandler.off(element, event.type, fn)\n }\n\n return fn.apply(element, [event])\n }\n}\n\nfunction bootstrapDelegationHandler(element, selector, fn) {\n return function handler(event) {\n const domElements = element.querySelectorAll(selector)\n\n for (let { target } = event; target && target !== this; target = target.parentNode) {\n for (const domElement of domElements) {\n if (domElement !== target) {\n continue\n }\n\n hydrateObj(event, { delegateTarget: target })\n\n if (handler.oneOff) {\n EventHandler.off(element, event.type, selector, fn)\n }\n\n return fn.apply(target, [event])\n }\n }\n }\n}\n\nfunction findHandler(events, callable, delegationSelector = null) {\n return Object.values(events)\n .find(event => event.callable === callable && event.delegationSelector === delegationSelector)\n}\n\nfunction normalizeParameters(originalTypeEvent, handler, delegationFunction) {\n const isDelegated = typeof handler === 'string'\n // TODO: tooltip passes `false` instead of selector, so we need to check\n const callable = isDelegated ? delegationFunction : (handler || delegationFunction)\n let typeEvent = getTypeEvent(originalTypeEvent)\n\n if (!nativeEvents.has(typeEvent)) {\n typeEvent = originalTypeEvent\n }\n\n return [isDelegated, callable, typeEvent]\n}\n\nfunction addHandler(element, originalTypeEvent, handler, delegationFunction, oneOff) {\n if (typeof originalTypeEvent !== 'string' || !element) {\n return\n }\n\n let [isDelegated, callable, typeEvent] = normalizeParameters(originalTypeEvent, handler, delegationFunction)\n\n // in case of mouseenter or mouseleave wrap the handler within a function that checks for its DOM position\n // this prevents the handler from being dispatched the same way as mouseover or mouseout does\n if (originalTypeEvent in customEvents) {\n const wrapFunction = fn => {\n return function (event) {\n if (!event.relatedTarget || (event.relatedTarget !== event.delegateTarget && !event.delegateTarget.contains(event.relatedTarget))) {\n return fn.call(this, event)\n }\n }\n }\n\n callable = wrapFunction(callable)\n }\n\n const events = getElementEvents(element)\n const handlers = events[typeEvent] || (events[typeEvent] = {})\n const previousFunction = findHandler(handlers, callable, isDelegated ? handler : null)\n\n if (previousFunction) {\n previousFunction.oneOff = previousFunction.oneOff && oneOff\n\n return\n }\n\n const uid = makeEventUid(callable, originalTypeEvent.replace(namespaceRegex, ''))\n const fn = isDelegated ?\n bootstrapDelegationHandler(element, handler, callable) :\n bootstrapHandler(element, callable)\n\n fn.delegationSelector = isDelegated ? handler : null\n fn.callable = callable\n fn.oneOff = oneOff\n fn.uidEvent = uid\n handlers[uid] = fn\n\n element.addEventListener(typeEvent, fn, isDelegated)\n}\n\nfunction removeHandler(element, events, typeEvent, handler, delegationSelector) {\n const fn = findHandler(events[typeEvent], handler, delegationSelector)\n\n if (!fn) {\n return\n }\n\n element.removeEventListener(typeEvent, fn, Boolean(delegationSelector))\n delete events[typeEvent][fn.uidEvent]\n}\n\nfunction removeNamespacedHandlers(element, events, typeEvent, namespace) {\n const storeElementEvent = events[typeEvent] || {}\n\n for (const [handlerKey, event] of Object.entries(storeElementEvent)) {\n if (handlerKey.includes(namespace)) {\n removeHandler(element, events, typeEvent, event.callable, event.delegationSelector)\n }\n }\n}\n\nfunction getTypeEvent(event) {\n // allow to get the native events from namespaced events ('click.bs.button' --> 'click')\n event = event.replace(stripNameRegex, '')\n return customEvents[event] || event\n}\n\nconst EventHandler = {\n on(element, event, handler, delegationFunction) {\n addHandler(element, event, handler, delegationFunction, false)\n },\n\n one(element, event, handler, delegationFunction) {\n addHandler(element, event, handler, delegationFunction, true)\n },\n\n off(element, originalTypeEvent, handler, delegationFunction) {\n if (typeof originalTypeEvent !== 'string' || !element) {\n return\n }\n\n const [isDelegated, callable, typeEvent] = normalizeParameters(originalTypeEvent, handler, delegationFunction)\n const inNamespace = typeEvent !== originalTypeEvent\n const events = getElementEvents(element)\n const storeElementEvent = events[typeEvent] || {}\n const isNamespace = originalTypeEvent.startsWith('.')\n\n if (typeof callable !== 'undefined') {\n // Simplest case: handler is passed, remove that listener ONLY.\n if (!Object.keys(storeElementEvent).length) {\n return\n }\n\n removeHandler(element, events, typeEvent, callable, isDelegated ? handler : null)\n return\n }\n\n if (isNamespace) {\n for (const elementEvent of Object.keys(events)) {\n removeNamespacedHandlers(element, events, elementEvent, originalTypeEvent.slice(1))\n }\n }\n\n for (const [keyHandlers, event] of Object.entries(storeElementEvent)) {\n const handlerKey = keyHandlers.replace(stripUidRegex, '')\n\n if (!inNamespace || originalTypeEvent.includes(handlerKey)) {\n removeHandler(element, events, typeEvent, event.callable, event.delegationSelector)\n }\n }\n },\n\n trigger(element, event, args) {\n if (typeof event !== 'string' || !element) {\n return null\n }\n\n const $ = getjQuery()\n const typeEvent = getTypeEvent(event)\n const inNamespace = event !== typeEvent\n\n let jQueryEvent = null\n let bubbles = true\n let nativeDispatch = true\n let defaultPrevented = false\n\n if (inNamespace && $) {\n jQueryEvent = $.Event(event, args)\n\n $(element).trigger(jQueryEvent)\n bubbles = !jQueryEvent.isPropagationStopped()\n nativeDispatch = !jQueryEvent.isImmediatePropagationStopped()\n defaultPrevented = jQueryEvent.isDefaultPrevented()\n }\n\n const evt = hydrateObj(new Event(event, { bubbles, cancelable: true }), args)\n\n if (defaultPrevented) {\n evt.preventDefault()\n }\n\n if (nativeDispatch) {\n element.dispatchEvent(evt)\n }\n\n if (evt.defaultPrevented && jQueryEvent) {\n jQueryEvent.preventDefault()\n }\n\n return evt\n }\n}\n\nfunction hydrateObj(obj, meta = {}) {\n for (const [key, value] of Object.entries(meta)) {\n try {\n obj[key] = value\n } catch {\n Object.defineProperty(obj, key, {\n configurable: true,\n get() {\n return value\n }\n })\n }\n }\n\n return obj\n}\n\nexport default EventHandler\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap dom/manipulator.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nfunction normalizeData(value) {\n if (value === 'true') {\n return true\n }\n\n if (value === 'false') {\n return false\n }\n\n if (value === Number(value).toString()) {\n return Number(value)\n }\n\n if (value === '' || value === 'null') {\n return null\n }\n\n if (typeof value !== 'string') {\n return value\n }\n\n try {\n return JSON.parse(decodeURIComponent(value))\n } catch {\n return value\n }\n}\n\nfunction normalizeDataKey(key) {\n return key.replace(/[A-Z]/g, chr => `-${chr.toLowerCase()}`)\n}\n\nconst Manipulator = {\n setDataAttribute(element, key, value) {\n element.setAttribute(`data-bs-${normalizeDataKey(key)}`, value)\n },\n\n removeDataAttribute(element, key) {\n element.removeAttribute(`data-bs-${normalizeDataKey(key)}`)\n },\n\n getDataAttributes(element) {\n if (!element) {\n return {}\n }\n\n const attributes = {}\n const bsKeys = Object.keys(element.dataset).filter(key => key.startsWith('bs') && !key.startsWith('bsConfig'))\n\n for (const key of bsKeys) {\n let pureKey = key.replace(/^bs/, '')\n pureKey = pureKey.charAt(0).toLowerCase() + pureKey.slice(1, pureKey.length)\n attributes[pureKey] = normalizeData(element.dataset[key])\n }\n\n return attributes\n },\n\n getDataAttribute(element, key) {\n return normalizeData(element.getAttribute(`data-bs-${normalizeDataKey(key)}`))\n }\n}\n\nexport default Manipulator\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap util/config.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport Manipulator from '../dom/manipulator.js'\nimport { isElement, toType } from './index.js'\n\n/**\n * Class definition\n */\n\nclass Config {\n // Getters\n static get Default() {\n return {}\n }\n\n static get DefaultType() {\n return {}\n }\n\n static get NAME() {\n throw new Error('You have to implement the static method \"NAME\", for each component!')\n }\n\n _getConfig(config) {\n config = this._mergeConfigObj(config)\n config = this._configAfterMerge(config)\n this._typeCheckConfig(config)\n return config\n }\n\n _configAfterMerge(config) {\n return config\n }\n\n _mergeConfigObj(config, element) {\n const jsonConfig = isElement(element) ? Manipulator.getDataAttribute(element, 'config') : {} // try to parse\n\n return {\n ...this.constructor.Default,\n ...(typeof jsonConfig === 'object' ? jsonConfig : {}),\n ...(isElement(element) ? Manipulator.getDataAttributes(element) : {}),\n ...(typeof config === 'object' ? config : {})\n }\n }\n\n _typeCheckConfig(config, configTypes = this.constructor.DefaultType) {\n for (const [property, expectedTypes] of Object.entries(configTypes)) {\n const value = config[property]\n const valueType = isElement(value) ? 'element' : toType(value)\n\n if (!new RegExp(expectedTypes).test(valueType)) {\n throw new TypeError(\n `${this.constructor.NAME.toUpperCase()}: Option \"${property}\" provided type \"${valueType}\" but expected type \"${expectedTypes}\".`\n )\n }\n }\n }\n}\n\nexport default Config\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap base-component.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport Data from './dom/data.js'\nimport EventHandler from './dom/event-handler.js'\nimport Config from './util/config.js'\nimport { executeAfterTransition, getElement } from './util/index.js'\n\n/**\n * Constants\n */\n\nconst VERSION = '5.3.1'\n\n/**\n * Class definition\n */\n\nclass BaseComponent extends Config {\n constructor(element, config) {\n super()\n\n element = getElement(element)\n if (!element) {\n return\n }\n\n this._element = element\n this._config = this._getConfig(config)\n\n Data.set(this._element, this.constructor.DATA_KEY, this)\n }\n\n // Public\n dispose() {\n Data.remove(this._element, this.constructor.DATA_KEY)\n EventHandler.off(this._element, this.constructor.EVENT_KEY)\n\n for (const propertyName of Object.getOwnPropertyNames(this)) {\n this[propertyName] = null\n }\n }\n\n _queueCallback(callback, element, isAnimated = true) {\n executeAfterTransition(callback, element, isAnimated)\n }\n\n _getConfig(config) {\n config = this._mergeConfigObj(config, this._element)\n config = this._configAfterMerge(config)\n this._typeCheckConfig(config)\n return config\n }\n\n // Static\n static getInstance(element) {\n return Data.get(getElement(element), this.DATA_KEY)\n }\n\n static getOrCreateInstance(element, config = {}) {\n return this.getInstance(element) || new this(element, typeof config === 'object' ? config : null)\n }\n\n static get VERSION() {\n return VERSION\n }\n\n static get DATA_KEY() {\n return `bs.${this.NAME}`\n }\n\n static get EVENT_KEY() {\n return `.${this.DATA_KEY}`\n }\n\n static eventName(name) {\n return `${name}${this.EVENT_KEY}`\n }\n}\n\nexport default BaseComponent\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap dom/selector-engine.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport { isDisabled, isVisible, parseSelector } from '../util/index.js'\n\nconst getSelector = element => {\n let selector = element.getAttribute('data-bs-target')\n\n if (!selector || selector === '#') {\n let hrefAttribute = element.getAttribute('href')\n\n // The only valid content that could double as a selector are IDs or classes,\n // so everything starting with `#` or `.`. If a \"real\" URL is used as the selector,\n // `document.querySelector` will rightfully complain it is invalid.\n // See https://github.com/twbs/bootstrap/issues/32273\n if (!hrefAttribute || (!hrefAttribute.includes('#') && !hrefAttribute.startsWith('.'))) {\n return null\n }\n\n // Just in case some CMS puts out a full URL with the anchor appended\n if (hrefAttribute.includes('#') && !hrefAttribute.startsWith('#')) {\n hrefAttribute = `#${hrefAttribute.split('#')[1]}`\n }\n\n selector = hrefAttribute && hrefAttribute !== '#' ? hrefAttribute.trim() : null\n }\n\n return parseSelector(selector)\n}\n\nconst SelectorEngine = {\n find(selector, element = document.documentElement) {\n return [].concat(...Element.prototype.querySelectorAll.call(element, selector))\n },\n\n findOne(selector, element = document.documentElement) {\n return Element.prototype.querySelector.call(element, selector)\n },\n\n children(element, selector) {\n return [].concat(...element.children).filter(child => child.matches(selector))\n },\n\n parents(element, selector) {\n const parents = []\n let ancestor = element.parentNode.closest(selector)\n\n while (ancestor) {\n parents.push(ancestor)\n ancestor = ancestor.parentNode.closest(selector)\n }\n\n return parents\n },\n\n prev(element, selector) {\n let previous = element.previousElementSibling\n\n while (previous) {\n if (previous.matches(selector)) {\n return [previous]\n }\n\n previous = previous.previousElementSibling\n }\n\n return []\n },\n // TODO: this is now unused; remove later along with prev()\n next(element, selector) {\n let next = element.nextElementSibling\n\n while (next) {\n if (next.matches(selector)) {\n return [next]\n }\n\n next = next.nextElementSibling\n }\n\n return []\n },\n\n focusableChildren(element) {\n const focusables = [\n 'a',\n 'button',\n 'input',\n 'textarea',\n 'select',\n 'details',\n '[tabindex]',\n '[contenteditable=\"true\"]'\n ].map(selector => `${selector}:not([tabindex^=\"-\"])`).join(',')\n\n return this.find(focusables, element).filter(el => !isDisabled(el) && isVisible(el))\n },\n\n getSelectorFromElement(element) {\n const selector = getSelector(element)\n\n if (selector) {\n return SelectorEngine.findOne(selector) ? selector : null\n }\n\n return null\n },\n\n getElementFromSelector(element) {\n const selector = getSelector(element)\n\n return selector ? SelectorEngine.findOne(selector) : null\n },\n\n getMultipleElementsFromSelector(element) {\n const selector = getSelector(element)\n\n return selector ? SelectorEngine.find(selector) : []\n }\n}\n\nexport default SelectorEngine\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap util/component-functions.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport EventHandler from '../dom/event-handler.js'\nimport SelectorEngine from '../dom/selector-engine.js'\nimport { isDisabled } from './index.js'\n\nconst enableDismissTrigger = (component, method = 'hide') => {\n const clickEvent = `click.dismiss${component.EVENT_KEY}`\n const name = component.NAME\n\n EventHandler.on(document, clickEvent, `[data-bs-dismiss=\"${name}\"]`, function (event) {\n if (['A', 'AREA'].includes(this.tagName)) {\n event.preventDefault()\n }\n\n if (isDisabled(this)) {\n return\n }\n\n const target = SelectorEngine.getElementFromSelector(this) || this.closest(`.${name}`)\n const instance = component.getOrCreateInstance(target)\n\n // Method argument is left, for Alert and only, as it doesn't implement the 'hide' method\n instance[method]()\n })\n}\n\nexport {\n enableDismissTrigger\n}\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap alert.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport BaseComponent from './base-component.js'\nimport EventHandler from './dom/event-handler.js'\nimport { enableDismissTrigger } from './util/component-functions.js'\nimport { defineJQueryPlugin } from './util/index.js'\n\n/**\n * Constants\n */\n\nconst NAME = 'alert'\nconst DATA_KEY = 'bs.alert'\nconst EVENT_KEY = `.${DATA_KEY}`\n\nconst EVENT_CLOSE = `close${EVENT_KEY}`\nconst EVENT_CLOSED = `closed${EVENT_KEY}`\nconst CLASS_NAME_FADE = 'fade'\nconst CLASS_NAME_SHOW = 'show'\n\n/**\n * Class definition\n */\n\nclass Alert extends BaseComponent {\n // Getters\n static get NAME() {\n return NAME\n }\n\n // Public\n close() {\n const closeEvent = EventHandler.trigger(this._element, EVENT_CLOSE)\n\n if (closeEvent.defaultPrevented) {\n return\n }\n\n this._element.classList.remove(CLASS_NAME_SHOW)\n\n const isAnimated = this._element.classList.contains(CLASS_NAME_FADE)\n this._queueCallback(() => this._destroyElement(), this._element, isAnimated)\n }\n\n // Private\n _destroyElement() {\n this._element.remove()\n EventHandler.trigger(this._element, EVENT_CLOSED)\n this.dispose()\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Alert.getOrCreateInstance(this)\n\n if (typeof config !== 'string') {\n return\n }\n\n if (data[config] === undefined || config.startsWith('_') || config === 'constructor') {\n throw new TypeError(`No method named \"${config}\"`)\n }\n\n data[config](this)\n })\n }\n}\n\n/**\n * Data API implementation\n */\n\nenableDismissTrigger(Alert, 'close')\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Alert)\n\nexport default Alert\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap button.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport BaseComponent from './base-component.js'\nimport EventHandler from './dom/event-handler.js'\nimport { defineJQueryPlugin } from './util/index.js'\n\n/**\n * Constants\n */\n\nconst NAME = 'button'\nconst DATA_KEY = 'bs.button'\nconst EVENT_KEY = `.${DATA_KEY}`\nconst DATA_API_KEY = '.data-api'\n\nconst CLASS_NAME_ACTIVE = 'active'\nconst SELECTOR_DATA_TOGGLE = '[data-bs-toggle=\"button\"]'\nconst EVENT_CLICK_DATA_API = `click${EVENT_KEY}${DATA_API_KEY}`\n\n/**\n * Class definition\n */\n\nclass Button extends BaseComponent {\n // Getters\n static get NAME() {\n return NAME\n }\n\n // Public\n toggle() {\n // Toggle class and sync the `aria-pressed` attribute with the return value of the `.toggle()` method\n this._element.setAttribute('aria-pressed', this._element.classList.toggle(CLASS_NAME_ACTIVE))\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Button.getOrCreateInstance(this)\n\n if (config === 'toggle') {\n data[config]()\n }\n })\n }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_CLICK_DATA_API, SELECTOR_DATA_TOGGLE, event => {\n event.preventDefault()\n\n const button = event.target.closest(SELECTOR_DATA_TOGGLE)\n const data = Button.getOrCreateInstance(button)\n\n data.toggle()\n})\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Button)\n\nexport default Button\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap util/swipe.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport EventHandler from '../dom/event-handler.js'\nimport Config from './config.js'\nimport { execute } from './index.js'\n\n/**\n * Constants\n */\n\nconst NAME = 'swipe'\nconst EVENT_KEY = '.bs.swipe'\nconst EVENT_TOUCHSTART = `touchstart${EVENT_KEY}`\nconst EVENT_TOUCHMOVE = `touchmove${EVENT_KEY}`\nconst EVENT_TOUCHEND = `touchend${EVENT_KEY}`\nconst EVENT_POINTERDOWN = `pointerdown${EVENT_KEY}`\nconst EVENT_POINTERUP = `pointerup${EVENT_KEY}`\nconst POINTER_TYPE_TOUCH = 'touch'\nconst POINTER_TYPE_PEN = 'pen'\nconst CLASS_NAME_POINTER_EVENT = 'pointer-event'\nconst SWIPE_THRESHOLD = 40\n\nconst Default = {\n endCallback: null,\n leftCallback: null,\n rightCallback: null\n}\n\nconst DefaultType = {\n endCallback: '(function|null)',\n leftCallback: '(function|null)',\n rightCallback: '(function|null)'\n}\n\n/**\n * Class definition\n */\n\nclass Swipe extends Config {\n constructor(element, config) {\n super()\n this._element = element\n\n if (!element || !Swipe.isSupported()) {\n return\n }\n\n this._config = this._getConfig(config)\n this._deltaX = 0\n this._supportPointerEvents = Boolean(window.PointerEvent)\n this._initEvents()\n }\n\n // Getters\n static get Default() {\n return Default\n }\n\n static get DefaultType() {\n return DefaultType\n }\n\n static get NAME() {\n return NAME\n }\n\n // Public\n dispose() {\n EventHandler.off(this._element, EVENT_KEY)\n }\n\n // Private\n _start(event) {\n if (!this._supportPointerEvents) {\n this._deltaX = event.touches[0].clientX\n\n return\n }\n\n if (this._eventIsPointerPenTouch(event)) {\n this._deltaX = event.clientX\n }\n }\n\n _end(event) {\n if (this._eventIsPointerPenTouch(event)) {\n this._deltaX = event.clientX - this._deltaX\n }\n\n this._handleSwipe()\n execute(this._config.endCallback)\n }\n\n _move(event) {\n this._deltaX = event.touches && event.touches.length > 1 ?\n 0 :\n event.touches[0].clientX - this._deltaX\n }\n\n _handleSwipe() {\n const absDeltaX = Math.abs(this._deltaX)\n\n if (absDeltaX <= SWIPE_THRESHOLD) {\n return\n }\n\n const direction = absDeltaX / this._deltaX\n\n this._deltaX = 0\n\n if (!direction) {\n return\n }\n\n execute(direction > 0 ? this._config.rightCallback : this._config.leftCallback)\n }\n\n _initEvents() {\n if (this._supportPointerEvents) {\n EventHandler.on(this._element, EVENT_POINTERDOWN, event => this._start(event))\n EventHandler.on(this._element, EVENT_POINTERUP, event => this._end(event))\n\n this._element.classList.add(CLASS_NAME_POINTER_EVENT)\n } else {\n EventHandler.on(this._element, EVENT_TOUCHSTART, event => this._start(event))\n EventHandler.on(this._element, EVENT_TOUCHMOVE, event => this._move(event))\n EventHandler.on(this._element, EVENT_TOUCHEND, event => this._end(event))\n }\n }\n\n _eventIsPointerPenTouch(event) {\n return this._supportPointerEvents && (event.pointerType === POINTER_TYPE_PEN || event.pointerType === POINTER_TYPE_TOUCH)\n }\n\n // Static\n static isSupported() {\n return 'ontouchstart' in document.documentElement || navigator.maxTouchPoints > 0\n }\n}\n\nexport default Swipe\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap carousel.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport BaseComponent from './base-component.js'\nimport EventHandler from './dom/event-handler.js'\nimport Manipulator from './dom/manipulator.js'\nimport SelectorEngine from './dom/selector-engine.js'\nimport {\n defineJQueryPlugin,\n getNextActiveElement,\n isRTL,\n isVisible,\n reflow,\n triggerTransitionEnd\n} from './util/index.js'\nimport Swipe from './util/swipe.js'\n\n/**\n * Constants\n */\n\nconst NAME = 'carousel'\nconst DATA_KEY = 'bs.carousel'\nconst EVENT_KEY = `.${DATA_KEY}`\nconst DATA_API_KEY = '.data-api'\n\nconst ARROW_LEFT_KEY = 'ArrowLeft'\nconst ARROW_RIGHT_KEY = 'ArrowRight'\nconst TOUCHEVENT_COMPAT_WAIT = 500 // Time for mouse compat events to fire after touch\n\nconst ORDER_NEXT = 'next'\nconst ORDER_PREV = 'prev'\nconst DIRECTION_LEFT = 'left'\nconst DIRECTION_RIGHT = 'right'\n\nconst EVENT_SLIDE = `slide${EVENT_KEY}`\nconst EVENT_SLID = `slid${EVENT_KEY}`\nconst EVENT_KEYDOWN = `keydown${EVENT_KEY}`\nconst EVENT_MOUSEENTER = `mouseenter${EVENT_KEY}`\nconst EVENT_MOUSELEAVE = `mouseleave${EVENT_KEY}`\nconst EVENT_DRAG_START = `dragstart${EVENT_KEY}`\nconst EVENT_LOAD_DATA_API = `load${EVENT_KEY}${DATA_API_KEY}`\nconst EVENT_CLICK_DATA_API = `click${EVENT_KEY}${DATA_API_KEY}`\n\nconst CLASS_NAME_CAROUSEL = 'carousel'\nconst CLASS_NAME_ACTIVE = 'active'\nconst CLASS_NAME_SLIDE = 'slide'\nconst CLASS_NAME_END = 'carousel-item-end'\nconst CLASS_NAME_START = 'carousel-item-start'\nconst CLASS_NAME_NEXT = 'carousel-item-next'\nconst CLASS_NAME_PREV = 'carousel-item-prev'\n\nconst SELECTOR_ACTIVE = '.active'\nconst SELECTOR_ITEM = '.carousel-item'\nconst SELECTOR_ACTIVE_ITEM = SELECTOR_ACTIVE + SELECTOR_ITEM\nconst SELECTOR_ITEM_IMG = '.carousel-item img'\nconst SELECTOR_INDICATORS = '.carousel-indicators'\nconst SELECTOR_DATA_SLIDE = '[data-bs-slide], [data-bs-slide-to]'\nconst SELECTOR_DATA_RIDE = '[data-bs-ride=\"carousel\"]'\n\nconst KEY_TO_DIRECTION = {\n [ARROW_LEFT_KEY]: DIRECTION_RIGHT,\n [ARROW_RIGHT_KEY]: DIRECTION_LEFT\n}\n\nconst Default = {\n interval: 5000,\n keyboard: true,\n pause: 'hover',\n ride: false,\n touch: true,\n wrap: true\n}\n\nconst DefaultType = {\n interval: '(number|boolean)', // TODO:v6 remove boolean support\n keyboard: 'boolean',\n pause: '(string|boolean)',\n ride: '(boolean|string)',\n touch: 'boolean',\n wrap: 'boolean'\n}\n\n/**\n * Class definition\n */\n\nclass Carousel extends BaseComponent {\n constructor(element, config) {\n super(element, config)\n\n this._interval = null\n this._activeElement = null\n this._isSliding = false\n this.touchTimeout = null\n this._swipeHelper = null\n\n this._indicatorsElement = SelectorEngine.findOne(SELECTOR_INDICATORS, this._element)\n this._addEventListeners()\n\n if (this._config.ride === CLASS_NAME_CAROUSEL) {\n this.cycle()\n }\n }\n\n // Getters\n static get Default() {\n return Default\n }\n\n static get DefaultType() {\n return DefaultType\n }\n\n static get NAME() {\n return NAME\n }\n\n // Public\n next() {\n this._slide(ORDER_NEXT)\n }\n\n nextWhenVisible() {\n // FIXME TODO use `document.visibilityState`\n // Don't call next when the page isn't visible\n // or the carousel or its parent isn't visible\n if (!document.hidden && isVisible(this._element)) {\n this.next()\n }\n }\n\n prev() {\n this._slide(ORDER_PREV)\n }\n\n pause() {\n if (this._isSliding) {\n triggerTransitionEnd(this._element)\n }\n\n this._clearInterval()\n }\n\n cycle() {\n this._clearInterval()\n this._updateInterval()\n\n this._interval = setInterval(() => this.nextWhenVisible(), this._config.interval)\n }\n\n _maybeEnableCycle() {\n if (!this._config.ride) {\n return\n }\n\n if (this._isSliding) {\n EventHandler.one(this._element, EVENT_SLID, () => this.cycle())\n return\n }\n\n this.cycle()\n }\n\n to(index) {\n const items = this._getItems()\n if (index > items.length - 1 || index < 0) {\n return\n }\n\n if (this._isSliding) {\n EventHandler.one(this._element, EVENT_SLID, () => this.to(index))\n return\n }\n\n const activeIndex = this._getItemIndex(this._getActive())\n if (activeIndex === index) {\n return\n }\n\n const order = index > activeIndex ? ORDER_NEXT : ORDER_PREV\n\n this._slide(order, items[index])\n }\n\n dispose() {\n if (this._swipeHelper) {\n this._swipeHelper.dispose()\n }\n\n super.dispose()\n }\n\n // Private\n _configAfterMerge(config) {\n config.defaultInterval = config.interval\n return config\n }\n\n _addEventListeners() {\n if (this._config.keyboard) {\n EventHandler.on(this._element, EVENT_KEYDOWN, event => this._keydown(event))\n }\n\n if (this._config.pause === 'hover') {\n EventHandler.on(this._element, EVENT_MOUSEENTER, () => this.pause())\n EventHandler.on(this._element, EVENT_MOUSELEAVE, () => this._maybeEnableCycle())\n }\n\n if (this._config.touch && Swipe.isSupported()) {\n this._addTouchEventListeners()\n }\n }\n\n _addTouchEventListeners() {\n for (const img of SelectorEngine.find(SELECTOR_ITEM_IMG, this._element)) {\n EventHandler.on(img, EVENT_DRAG_START, event => event.preventDefault())\n }\n\n const endCallBack = () => {\n if (this._config.pause !== 'hover') {\n return\n }\n\n // If it's a touch-enabled device, mouseenter/leave are fired as\n // part of the mouse compatibility events on first tap - the carousel\n // would stop cycling until user tapped out of it;\n // here, we listen for touchend, explicitly pause the carousel\n // (as if it's the second time we tap on it, mouseenter compat event\n // is NOT fired) and after a timeout (to allow for mouse compatibility\n // events to fire) we explicitly restart cycling\n\n this.pause()\n if (this.touchTimeout) {\n clearTimeout(this.touchTimeout)\n }\n\n this.touchTimeout = setTimeout(() => this._maybeEnableCycle(), TOUCHEVENT_COMPAT_WAIT + this._config.interval)\n }\n\n const swipeConfig = {\n leftCallback: () => this._slide(this._directionToOrder(DIRECTION_LEFT)),\n rightCallback: () => this._slide(this._directionToOrder(DIRECTION_RIGHT)),\n endCallback: endCallBack\n }\n\n this._swipeHelper = new Swipe(this._element, swipeConfig)\n }\n\n _keydown(event) {\n if (/input|textarea/i.test(event.target.tagName)) {\n return\n }\n\n const direction = KEY_TO_DIRECTION[event.key]\n if (direction) {\n event.preventDefault()\n this._slide(this._directionToOrder(direction))\n }\n }\n\n _getItemIndex(element) {\n return this._getItems().indexOf(element)\n }\n\n _setActiveIndicatorElement(index) {\n if (!this._indicatorsElement) {\n return\n }\n\n const activeIndicator = SelectorEngine.findOne(SELECTOR_ACTIVE, this._indicatorsElement)\n\n activeIndicator.classList.remove(CLASS_NAME_ACTIVE)\n activeIndicator.removeAttribute('aria-current')\n\n const newActiveIndicator = SelectorEngine.findOne(`[data-bs-slide-to=\"${index}\"]`, this._indicatorsElement)\n\n if (newActiveIndicator) {\n newActiveIndicator.classList.add(CLASS_NAME_ACTIVE)\n newActiveIndicator.setAttribute('aria-current', 'true')\n }\n }\n\n _updateInterval() {\n const element = this._activeElement || this._getActive()\n\n if (!element) {\n return\n }\n\n const elementInterval = Number.parseInt(element.getAttribute('data-bs-interval'), 10)\n\n this._config.interval = elementInterval || this._config.defaultInterval\n }\n\n _slide(order, element = null) {\n if (this._isSliding) {\n return\n }\n\n const activeElement = this._getActive()\n const isNext = order === ORDER_NEXT\n const nextElement = element || getNextActiveElement(this._getItems(), activeElement, isNext, this._config.wrap)\n\n if (nextElement === activeElement) {\n return\n }\n\n const nextElementIndex = this._getItemIndex(nextElement)\n\n const triggerEvent = eventName => {\n return EventHandler.trigger(this._element, eventName, {\n relatedTarget: nextElement,\n direction: this._orderToDirection(order),\n from: this._getItemIndex(activeElement),\n to: nextElementIndex\n })\n }\n\n const slideEvent = triggerEvent(EVENT_SLIDE)\n\n if (slideEvent.defaultPrevented) {\n return\n }\n\n if (!activeElement || !nextElement) {\n // Some weirdness is happening, so we bail\n // TODO: change tests that use empty divs to avoid this check\n return\n }\n\n const isCycling = Boolean(this._interval)\n this.pause()\n\n this._isSliding = true\n\n this._setActiveIndicatorElement(nextElementIndex)\n this._activeElement = nextElement\n\n const directionalClassName = isNext ? CLASS_NAME_START : CLASS_NAME_END\n const orderClassName = isNext ? CLASS_NAME_NEXT : CLASS_NAME_PREV\n\n nextElement.classList.add(orderClassName)\n\n reflow(nextElement)\n\n activeElement.classList.add(directionalClassName)\n nextElement.classList.add(directionalClassName)\n\n const completeCallBack = () => {\n nextElement.classList.remove(directionalClassName, orderClassName)\n nextElement.classList.add(CLASS_NAME_ACTIVE)\n\n activeElement.classList.remove(CLASS_NAME_ACTIVE, orderClassName, directionalClassName)\n\n this._isSliding = false\n\n triggerEvent(EVENT_SLID)\n }\n\n this._queueCallback(completeCallBack, activeElement, this._isAnimated())\n\n if (isCycling) {\n this.cycle()\n }\n }\n\n _isAnimated() {\n return this._element.classList.contains(CLASS_NAME_SLIDE)\n }\n\n _getActive() {\n return SelectorEngine.findOne(SELECTOR_ACTIVE_ITEM, this._element)\n }\n\n _getItems() {\n return SelectorEngine.find(SELECTOR_ITEM, this._element)\n }\n\n _clearInterval() {\n if (this._interval) {\n clearInterval(this._interval)\n this._interval = null\n }\n }\n\n _directionToOrder(direction) {\n if (isRTL()) {\n return direction === DIRECTION_LEFT ? ORDER_PREV : ORDER_NEXT\n }\n\n return direction === DIRECTION_LEFT ? ORDER_NEXT : ORDER_PREV\n }\n\n _orderToDirection(order) {\n if (isRTL()) {\n return order === ORDER_PREV ? DIRECTION_LEFT : DIRECTION_RIGHT\n }\n\n return order === ORDER_PREV ? DIRECTION_RIGHT : DIRECTION_LEFT\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Carousel.getOrCreateInstance(this, config)\n\n if (typeof config === 'number') {\n data.to(config)\n return\n }\n\n if (typeof config === 'string') {\n if (data[config] === undefined || config.startsWith('_') || config === 'constructor') {\n throw new TypeError(`No method named \"${config}\"`)\n }\n\n data[config]()\n }\n })\n }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_CLICK_DATA_API, SELECTOR_DATA_SLIDE, function (event) {\n const target = SelectorEngine.getElementFromSelector(this)\n\n if (!target || !target.classList.contains(CLASS_NAME_CAROUSEL)) {\n return\n }\n\n event.preventDefault()\n\n const carousel = Carousel.getOrCreateInstance(target)\n const slideIndex = this.getAttribute('data-bs-slide-to')\n\n if (slideIndex) {\n carousel.to(slideIndex)\n carousel._maybeEnableCycle()\n return\n }\n\n if (Manipulator.getDataAttribute(this, 'slide') === 'next') {\n carousel.next()\n carousel._maybeEnableCycle()\n return\n }\n\n carousel.prev()\n carousel._maybeEnableCycle()\n})\n\nEventHandler.on(window, EVENT_LOAD_DATA_API, () => {\n const carousels = SelectorEngine.find(SELECTOR_DATA_RIDE)\n\n for (const carousel of carousels) {\n Carousel.getOrCreateInstance(carousel)\n }\n})\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Carousel)\n\nexport default Carousel\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap collapse.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport BaseComponent from './base-component.js'\nimport EventHandler from './dom/event-handler.js'\nimport SelectorEngine from './dom/selector-engine.js'\nimport {\n defineJQueryPlugin,\n getElement,\n reflow\n} from './util/index.js'\n\n/**\n * Constants\n */\n\nconst NAME = 'collapse'\nconst DATA_KEY = 'bs.collapse'\nconst EVENT_KEY = `.${DATA_KEY}`\nconst DATA_API_KEY = '.data-api'\n\nconst EVENT_SHOW = `show${EVENT_KEY}`\nconst EVENT_SHOWN = `shown${EVENT_KEY}`\nconst EVENT_HIDE = `hide${EVENT_KEY}`\nconst EVENT_HIDDEN = `hidden${EVENT_KEY}`\nconst EVENT_CLICK_DATA_API = `click${EVENT_KEY}${DATA_API_KEY}`\n\nconst CLASS_NAME_SHOW = 'show'\nconst CLASS_NAME_COLLAPSE = 'collapse'\nconst CLASS_NAME_COLLAPSING = 'collapsing'\nconst CLASS_NAME_COLLAPSED = 'collapsed'\nconst CLASS_NAME_DEEPER_CHILDREN = `:scope .${CLASS_NAME_COLLAPSE} .${CLASS_NAME_COLLAPSE}`\nconst CLASS_NAME_HORIZONTAL = 'collapse-horizontal'\n\nconst WIDTH = 'width'\nconst HEIGHT = 'height'\n\nconst SELECTOR_ACTIVES = '.collapse.show, .collapse.collapsing'\nconst SELECTOR_DATA_TOGGLE = '[data-bs-toggle=\"collapse\"]'\n\nconst Default = {\n parent: null,\n toggle: true\n}\n\nconst DefaultType = {\n parent: '(null|element)',\n toggle: 'boolean'\n}\n\n/**\n * Class definition\n */\n\nclass Collapse extends BaseComponent {\n constructor(element, config) {\n super(element, config)\n\n this._isTransitioning = false\n this._triggerArray = []\n\n const toggleList = SelectorEngine.find(SELECTOR_DATA_TOGGLE)\n\n for (const elem of toggleList) {\n const selector = SelectorEngine.getSelectorFromElement(elem)\n const filterElement = SelectorEngine.find(selector)\n .filter(foundElement => foundElement === this._element)\n\n if (selector !== null && filterElement.length) {\n this._triggerArray.push(elem)\n }\n }\n\n this._initializeChildren()\n\n if (!this._config.parent) {\n this._addAriaAndCollapsedClass(this._triggerArray, this._isShown())\n }\n\n if (this._config.toggle) {\n this.toggle()\n }\n }\n\n // Getters\n static get Default() {\n return Default\n }\n\n static get DefaultType() {\n return DefaultType\n }\n\n static get NAME() {\n return NAME\n }\n\n // Public\n toggle() {\n if (this._isShown()) {\n this.hide()\n } else {\n this.show()\n }\n }\n\n show() {\n if (this._isTransitioning || this._isShown()) {\n return\n }\n\n let activeChildren = []\n\n // find active children\n if (this._config.parent) {\n activeChildren = this._getFirstLevelChildren(SELECTOR_ACTIVES)\n .filter(element => element !== this._element)\n .map(element => Collapse.getOrCreateInstance(element, { toggle: false }))\n }\n\n if (activeChildren.length && activeChildren[0]._isTransitioning) {\n return\n }\n\n const startEvent = EventHandler.trigger(this._element, EVENT_SHOW)\n if (startEvent.defaultPrevented) {\n return\n }\n\n for (const activeInstance of activeChildren) {\n activeInstance.hide()\n }\n\n const dimension = this._getDimension()\n\n this._element.classList.remove(CLASS_NAME_COLLAPSE)\n this._element.classList.add(CLASS_NAME_COLLAPSING)\n\n this._element.style[dimension] = 0\n\n this._addAriaAndCollapsedClass(this._triggerArray, true)\n this._isTransitioning = true\n\n const complete = () => {\n this._isTransitioning = false\n\n this._element.classList.remove(CLASS_NAME_COLLAPSING)\n this._element.classList.add(CLASS_NAME_COLLAPSE, CLASS_NAME_SHOW)\n\n this._element.style[dimension] = ''\n\n EventHandler.trigger(this._element, EVENT_SHOWN)\n }\n\n const capitalizedDimension = dimension[0].toUpperCase() + dimension.slice(1)\n const scrollSize = `scroll${capitalizedDimension}`\n\n this._queueCallback(complete, this._element, true)\n this._element.style[dimension] = `${this._element[scrollSize]}px`\n }\n\n hide() {\n if (this._isTransitioning || !this._isShown()) {\n return\n }\n\n const startEvent = EventHandler.trigger(this._element, EVENT_HIDE)\n if (startEvent.defaultPrevented) {\n return\n }\n\n const dimension = this._getDimension()\n\n this._element.style[dimension] = `${this._element.getBoundingClientRect()[dimension]}px`\n\n reflow(this._element)\n\n this._element.classList.add(CLASS_NAME_COLLAPSING)\n this._element.classList.remove(CLASS_NAME_COLLAPSE, CLASS_NAME_SHOW)\n\n for (const trigger of this._triggerArray) {\n const element = SelectorEngine.getElementFromSelector(trigger)\n\n if (element && !this._isShown(element)) {\n this._addAriaAndCollapsedClass([trigger], false)\n }\n }\n\n this._isTransitioning = true\n\n const complete = () => {\n this._isTransitioning = false\n this._element.classList.remove(CLASS_NAME_COLLAPSING)\n this._element.classList.add(CLASS_NAME_COLLAPSE)\n EventHandler.trigger(this._element, EVENT_HIDDEN)\n }\n\n this._element.style[dimension] = ''\n\n this._queueCallback(complete, this._element, true)\n }\n\n _isShown(element = this._element) {\n return element.classList.contains(CLASS_NAME_SHOW)\n }\n\n // Private\n _configAfterMerge(config) {\n config.toggle = Boolean(config.toggle) // Coerce string values\n config.parent = getElement(config.parent)\n return config\n }\n\n _getDimension() {\n return this._element.classList.contains(CLASS_NAME_HORIZONTAL) ? WIDTH : HEIGHT\n }\n\n _initializeChildren() {\n if (!this._config.parent) {\n return\n }\n\n const children = this._getFirstLevelChildren(SELECTOR_DATA_TOGGLE)\n\n for (const element of children) {\n const selected = SelectorEngine.getElementFromSelector(element)\n\n if (selected) {\n this._addAriaAndCollapsedClass([element], this._isShown(selected))\n }\n }\n }\n\n _getFirstLevelChildren(selector) {\n const children = SelectorEngine.find(CLASS_NAME_DEEPER_CHILDREN, this._config.parent)\n // remove children if greater depth\n return SelectorEngine.find(selector, this._config.parent).filter(element => !children.includes(element))\n }\n\n _addAriaAndCollapsedClass(triggerArray, isOpen) {\n if (!triggerArray.length) {\n return\n }\n\n for (const element of triggerArray) {\n element.classList.toggle(CLASS_NAME_COLLAPSED, !isOpen)\n element.setAttribute('aria-expanded', isOpen)\n }\n }\n\n // Static\n static jQueryInterface(config) {\n const _config = {}\n if (typeof config === 'string' && /show|hide/.test(config)) {\n _config.toggle = false\n }\n\n return this.each(function () {\n const data = Collapse.getOrCreateInstance(this, _config)\n\n if (typeof config === 'string') {\n if (typeof data[config] === 'undefined') {\n throw new TypeError(`No method named \"${config}\"`)\n }\n\n data[config]()\n }\n })\n }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_CLICK_DATA_API, SELECTOR_DATA_TOGGLE, function (event) {\n // preventDefault only for elements (which change the URL) not inside the collapsible element\n if (event.target.tagName === 'A' || (event.delegateTarget && event.delegateTarget.tagName === 'A')) {\n event.preventDefault()\n }\n\n for (const element of SelectorEngine.getMultipleElementsFromSelector(this)) {\n Collapse.getOrCreateInstance(element, { toggle: false }).toggle()\n }\n})\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Collapse)\n\nexport default Collapse\n","export var top = 'top';\nexport var bottom = 'bottom';\nexport var right = 'right';\nexport var left = 'left';\nexport var auto = 'auto';\nexport var basePlacements = [top, bottom, right, left];\nexport var start = 'start';\nexport var end = 'end';\nexport var clippingParents = 'clippingParents';\nexport var viewport = 'viewport';\nexport var popper = 'popper';\nexport var reference = 'reference';\nexport var variationPlacements = /*#__PURE__*/basePlacements.reduce(function (acc, placement) {\n return acc.concat([placement + \"-\" + start, placement + \"-\" + end]);\n}, []);\nexport var placements = /*#__PURE__*/[].concat(basePlacements, [auto]).reduce(function (acc, placement) {\n return acc.concat([placement, placement + \"-\" + start, placement + \"-\" + end]);\n}, []); // modifiers that need to read the DOM\n\nexport var beforeRead = 'beforeRead';\nexport var read = 'read';\nexport var afterRead = 'afterRead'; // pure-logic modifiers\n\nexport var beforeMain = 'beforeMain';\nexport var main = 'main';\nexport var afterMain = 'afterMain'; // modifier with the purpose to write to the DOM (or write into a framework state)\n\nexport var beforeWrite = 'beforeWrite';\nexport var write = 'write';\nexport var afterWrite = 'afterWrite';\nexport var modifierPhases = [beforeRead, read, afterRead, beforeMain, main, afterMain, beforeWrite, write, afterWrite];","export default function getNodeName(element) {\n return element ? (element.nodeName || '').toLowerCase() : null;\n}","export default function getWindow(node) {\n if (node == null) {\n return window;\n }\n\n if (node.toString() !== '[object Window]') {\n var ownerDocument = node.ownerDocument;\n return ownerDocument ? ownerDocument.defaultView || window : window;\n }\n\n return node;\n}","import getWindow from \"./getWindow.js\";\n\nfunction isElement(node) {\n var OwnElement = getWindow(node).Element;\n return node instanceof OwnElement || node instanceof Element;\n}\n\nfunction isHTMLElement(node) {\n var OwnElement = getWindow(node).HTMLElement;\n return node instanceof OwnElement || node instanceof HTMLElement;\n}\n\nfunction isShadowRoot(node) {\n // IE 11 has no ShadowRoot\n if (typeof ShadowRoot === 'undefined') {\n return false;\n }\n\n var OwnElement = getWindow(node).ShadowRoot;\n return node instanceof OwnElement || node instanceof ShadowRoot;\n}\n\nexport { isElement, isHTMLElement, isShadowRoot };","import getNodeName from \"../dom-utils/getNodeName.js\";\nimport { isHTMLElement } from \"../dom-utils/instanceOf.js\"; // This modifier takes the styles prepared by the `computeStyles` modifier\n// and applies them to the HTMLElements such as popper and arrow\n\nfunction applyStyles(_ref) {\n var state = _ref.state;\n Object.keys(state.elements).forEach(function (name) {\n var style = state.styles[name] || {};\n var attributes = state.attributes[name] || {};\n var element = state.elements[name]; // arrow is optional + virtual elements\n\n if (!isHTMLElement(element) || !getNodeName(element)) {\n return;\n } // Flow doesn't support to extend this property, but it's the most\n // effective way to apply styles to an HTMLElement\n // $FlowFixMe[cannot-write]\n\n\n Object.assign(element.style, style);\n Object.keys(attributes).forEach(function (name) {\n var value = attributes[name];\n\n if (value === false) {\n element.removeAttribute(name);\n } else {\n element.setAttribute(name, value === true ? '' : value);\n }\n });\n });\n}\n\nfunction effect(_ref2) {\n var state = _ref2.state;\n var initialStyles = {\n popper: {\n position: state.options.strategy,\n left: '0',\n top: '0',\n margin: '0'\n },\n arrow: {\n position: 'absolute'\n },\n reference: {}\n };\n Object.assign(state.elements.popper.style, initialStyles.popper);\n state.styles = initialStyles;\n\n if (state.elements.arrow) {\n Object.assign(state.elements.arrow.style, initialStyles.arrow);\n }\n\n return function () {\n Object.keys(state.elements).forEach(function (name) {\n var element = state.elements[name];\n var attributes = state.attributes[name] || {};\n var styleProperties = Object.keys(state.styles.hasOwnProperty(name) ? state.styles[name] : initialStyles[name]); // Set all values to an empty string to unset them\n\n var style = styleProperties.reduce(function (style, property) {\n style[property] = '';\n return style;\n }, {}); // arrow is optional + virtual elements\n\n if (!isHTMLElement(element) || !getNodeName(element)) {\n return;\n }\n\n Object.assign(element.style, style);\n Object.keys(attributes).forEach(function (attribute) {\n element.removeAttribute(attribute);\n });\n });\n };\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'applyStyles',\n enabled: true,\n phase: 'write',\n fn: applyStyles,\n effect: effect,\n requires: ['computeStyles']\n};","import { auto } from \"../enums.js\";\nexport default function getBasePlacement(placement) {\n return placement.split('-')[0];\n}","export var max = Math.max;\nexport var min = Math.min;\nexport var round = Math.round;","export default function getUAString() {\n var uaData = navigator.userAgentData;\n\n if (uaData != null && uaData.brands && Array.isArray(uaData.brands)) {\n return uaData.brands.map(function (item) {\n return item.brand + \"/\" + item.version;\n }).join(' ');\n }\n\n return navigator.userAgent;\n}","import getUAString from \"../utils/userAgent.js\";\nexport default function isLayoutViewport() {\n return !/^((?!chrome|android).)*safari/i.test(getUAString());\n}","import { isElement, isHTMLElement } from \"./instanceOf.js\";\nimport { round } from \"../utils/math.js\";\nimport getWindow from \"./getWindow.js\";\nimport isLayoutViewport from \"./isLayoutViewport.js\";\nexport default function getBoundingClientRect(element, includeScale, isFixedStrategy) {\n if (includeScale === void 0) {\n includeScale = false;\n }\n\n if (isFixedStrategy === void 0) {\n isFixedStrategy = false;\n }\n\n var clientRect = element.getBoundingClientRect();\n var scaleX = 1;\n var scaleY = 1;\n\n if (includeScale && isHTMLElement(element)) {\n scaleX = element.offsetWidth > 0 ? round(clientRect.width) / element.offsetWidth || 1 : 1;\n scaleY = element.offsetHeight > 0 ? round(clientRect.height) / element.offsetHeight || 1 : 1;\n }\n\n var _ref = isElement(element) ? getWindow(element) : window,\n visualViewport = _ref.visualViewport;\n\n var addVisualOffsets = !isLayoutViewport() && isFixedStrategy;\n var x = (clientRect.left + (addVisualOffsets && visualViewport ? visualViewport.offsetLeft : 0)) / scaleX;\n var y = (clientRect.top + (addVisualOffsets && visualViewport ? visualViewport.offsetTop : 0)) / scaleY;\n var width = clientRect.width / scaleX;\n var height = clientRect.height / scaleY;\n return {\n width: width,\n height: height,\n top: y,\n right: x + width,\n bottom: y + height,\n left: x,\n x: x,\n y: y\n };\n}","import getBoundingClientRect from \"./getBoundingClientRect.js\"; // Returns the layout rect of an element relative to its offsetParent. Layout\n// means it doesn't take into account transforms.\n\nexport default function getLayoutRect(element) {\n var clientRect = getBoundingClientRect(element); // Use the clientRect sizes if it's not been transformed.\n // Fixes https://github.com/popperjs/popper-core/issues/1223\n\n var width = element.offsetWidth;\n var height = element.offsetHeight;\n\n if (Math.abs(clientRect.width - width) <= 1) {\n width = clientRect.width;\n }\n\n if (Math.abs(clientRect.height - height) <= 1) {\n height = clientRect.height;\n }\n\n return {\n x: element.offsetLeft,\n y: element.offsetTop,\n width: width,\n height: height\n };\n}","import { isShadowRoot } from \"./instanceOf.js\";\nexport default function contains(parent, child) {\n var rootNode = child.getRootNode && child.getRootNode(); // First, attempt with faster native method\n\n if (parent.contains(child)) {\n return true;\n } // then fallback to custom implementation with Shadow DOM support\n else if (rootNode && isShadowRoot(rootNode)) {\n var next = child;\n\n do {\n if (next && parent.isSameNode(next)) {\n return true;\n } // $FlowFixMe[prop-missing]: need a better way to handle this...\n\n\n next = next.parentNode || next.host;\n } while (next);\n } // Give up, the result is false\n\n\n return false;\n}","import getWindow from \"./getWindow.js\";\nexport default function getComputedStyle(element) {\n return getWindow(element).getComputedStyle(element);\n}","import getNodeName from \"./getNodeName.js\";\nexport default function isTableElement(element) {\n return ['table', 'td', 'th'].indexOf(getNodeName(element)) >= 0;\n}","import { isElement } from \"./instanceOf.js\";\nexport default function getDocumentElement(element) {\n // $FlowFixMe[incompatible-return]: assume body is always available\n return ((isElement(element) ? element.ownerDocument : // $FlowFixMe[prop-missing]\n element.document) || window.document).documentElement;\n}","import getNodeName from \"./getNodeName.js\";\nimport getDocumentElement from \"./getDocumentElement.js\";\nimport { isShadowRoot } from \"./instanceOf.js\";\nexport default function getParentNode(element) {\n if (getNodeName(element) === 'html') {\n return element;\n }\n\n return (// this is a quicker (but less type safe) way to save quite some bytes from the bundle\n // $FlowFixMe[incompatible-return]\n // $FlowFixMe[prop-missing]\n element.assignedSlot || // step into the shadow DOM of the parent of a slotted node\n element.parentNode || ( // DOM Element detected\n isShadowRoot(element) ? element.host : null) || // ShadowRoot detected\n // $FlowFixMe[incompatible-call]: HTMLElement is a Node\n getDocumentElement(element) // fallback\n\n );\n}","import getWindow from \"./getWindow.js\";\nimport getNodeName from \"./getNodeName.js\";\nimport getComputedStyle from \"./getComputedStyle.js\";\nimport { isHTMLElement, isShadowRoot } from \"./instanceOf.js\";\nimport isTableElement from \"./isTableElement.js\";\nimport getParentNode from \"./getParentNode.js\";\nimport getUAString from \"../utils/userAgent.js\";\n\nfunction getTrueOffsetParent(element) {\n if (!isHTMLElement(element) || // https://github.com/popperjs/popper-core/issues/837\n getComputedStyle(element).position === 'fixed') {\n return null;\n }\n\n return element.offsetParent;\n} // `.offsetParent` reports `null` for fixed elements, while absolute elements\n// return the containing block\n\n\nfunction getContainingBlock(element) {\n var isFirefox = /firefox/i.test(getUAString());\n var isIE = /Trident/i.test(getUAString());\n\n if (isIE && isHTMLElement(element)) {\n // In IE 9, 10 and 11 fixed elements containing block is always established by the viewport\n var elementCss = getComputedStyle(element);\n\n if (elementCss.position === 'fixed') {\n return null;\n }\n }\n\n var currentNode = getParentNode(element);\n\n if (isShadowRoot(currentNode)) {\n currentNode = currentNode.host;\n }\n\n while (isHTMLElement(currentNode) && ['html', 'body'].indexOf(getNodeName(currentNode)) < 0) {\n var css = getComputedStyle(currentNode); // This is non-exhaustive but covers the most common CSS properties that\n // create a containing block.\n // https://developer.mozilla.org/en-US/docs/Web/CSS/Containing_block#identifying_the_containing_block\n\n if (css.transform !== 'none' || css.perspective !== 'none' || css.contain === 'paint' || ['transform', 'perspective'].indexOf(css.willChange) !== -1 || isFirefox && css.willChange === 'filter' || isFirefox && css.filter && css.filter !== 'none') {\n return currentNode;\n } else {\n currentNode = currentNode.parentNode;\n }\n }\n\n return null;\n} // Gets the closest ancestor positioned element. Handles some edge cases,\n// such as table ancestors and cross browser bugs.\n\n\nexport default function getOffsetParent(element) {\n var window = getWindow(element);\n var offsetParent = getTrueOffsetParent(element);\n\n while (offsetParent && isTableElement(offsetParent) && getComputedStyle(offsetParent).position === 'static') {\n offsetParent = getTrueOffsetParent(offsetParent);\n }\n\n if (offsetParent && (getNodeName(offsetParent) === 'html' || getNodeName(offsetParent) === 'body' && getComputedStyle(offsetParent).position === 'static')) {\n return window;\n }\n\n return offsetParent || getContainingBlock(element) || window;\n}","export default function getMainAxisFromPlacement(placement) {\n return ['top', 'bottom'].indexOf(placement) >= 0 ? 'x' : 'y';\n}","import { max as mathMax, min as mathMin } from \"./math.js\";\nexport function within(min, value, max) {\n return mathMax(min, mathMin(value, max));\n}\nexport function withinMaxClamp(min, value, max) {\n var v = within(min, value, max);\n return v > max ? max : v;\n}","import getFreshSideObject from \"./getFreshSideObject.js\";\nexport default function mergePaddingObject(paddingObject) {\n return Object.assign({}, getFreshSideObject(), paddingObject);\n}","export default function getFreshSideObject() {\n return {\n top: 0,\n right: 0,\n bottom: 0,\n left: 0\n };\n}","export default function expandToHashMap(value, keys) {\n return keys.reduce(function (hashMap, key) {\n hashMap[key] = value;\n return hashMap;\n }, {});\n}","import getBasePlacement from \"../utils/getBasePlacement.js\";\nimport getLayoutRect from \"../dom-utils/getLayoutRect.js\";\nimport contains from \"../dom-utils/contains.js\";\nimport getOffsetParent from \"../dom-utils/getOffsetParent.js\";\nimport getMainAxisFromPlacement from \"../utils/getMainAxisFromPlacement.js\";\nimport { within } from \"../utils/within.js\";\nimport mergePaddingObject from \"../utils/mergePaddingObject.js\";\nimport expandToHashMap from \"../utils/expandToHashMap.js\";\nimport { left, right, basePlacements, top, bottom } from \"../enums.js\"; // eslint-disable-next-line import/no-unused-modules\n\nvar toPaddingObject = function toPaddingObject(padding, state) {\n padding = typeof padding === 'function' ? padding(Object.assign({}, state.rects, {\n placement: state.placement\n })) : padding;\n return mergePaddingObject(typeof padding !== 'number' ? padding : expandToHashMap(padding, basePlacements));\n};\n\nfunction arrow(_ref) {\n var _state$modifiersData$;\n\n var state = _ref.state,\n name = _ref.name,\n options = _ref.options;\n var arrowElement = state.elements.arrow;\n var popperOffsets = state.modifiersData.popperOffsets;\n var basePlacement = getBasePlacement(state.placement);\n var axis = getMainAxisFromPlacement(basePlacement);\n var isVertical = [left, right].indexOf(basePlacement) >= 0;\n var len = isVertical ? 'height' : 'width';\n\n if (!arrowElement || !popperOffsets) {\n return;\n }\n\n var paddingObject = toPaddingObject(options.padding, state);\n var arrowRect = getLayoutRect(arrowElement);\n var minProp = axis === 'y' ? top : left;\n var maxProp = axis === 'y' ? bottom : right;\n var endDiff = state.rects.reference[len] + state.rects.reference[axis] - popperOffsets[axis] - state.rects.popper[len];\n var startDiff = popperOffsets[axis] - state.rects.reference[axis];\n var arrowOffsetParent = getOffsetParent(arrowElement);\n var clientSize = arrowOffsetParent ? axis === 'y' ? arrowOffsetParent.clientHeight || 0 : arrowOffsetParent.clientWidth || 0 : 0;\n var centerToReference = endDiff / 2 - startDiff / 2; // Make sure the arrow doesn't overflow the popper if the center point is\n // outside of the popper bounds\n\n var min = paddingObject[minProp];\n var max = clientSize - arrowRect[len] - paddingObject[maxProp];\n var center = clientSize / 2 - arrowRect[len] / 2 + centerToReference;\n var offset = within(min, center, max); // Prevents breaking syntax highlighting...\n\n var axisProp = axis;\n state.modifiersData[name] = (_state$modifiersData$ = {}, _state$modifiersData$[axisProp] = offset, _state$modifiersData$.centerOffset = offset - center, _state$modifiersData$);\n}\n\nfunction effect(_ref2) {\n var state = _ref2.state,\n options = _ref2.options;\n var _options$element = options.element,\n arrowElement = _options$element === void 0 ? '[data-popper-arrow]' : _options$element;\n\n if (arrowElement == null) {\n return;\n } // CSS selector\n\n\n if (typeof arrowElement === 'string') {\n arrowElement = state.elements.popper.querySelector(arrowElement);\n\n if (!arrowElement) {\n return;\n }\n }\n\n if (!contains(state.elements.popper, arrowElement)) {\n return;\n }\n\n state.elements.arrow = arrowElement;\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'arrow',\n enabled: true,\n phase: 'main',\n fn: arrow,\n effect: effect,\n requires: ['popperOffsets'],\n requiresIfExists: ['preventOverflow']\n};","export default function getVariation(placement) {\n return placement.split('-')[1];\n}","import { top, left, right, bottom, end } from \"../enums.js\";\nimport getOffsetParent from \"../dom-utils/getOffsetParent.js\";\nimport getWindow from \"../dom-utils/getWindow.js\";\nimport getDocumentElement from \"../dom-utils/getDocumentElement.js\";\nimport getComputedStyle from \"../dom-utils/getComputedStyle.js\";\nimport getBasePlacement from \"../utils/getBasePlacement.js\";\nimport getVariation from \"../utils/getVariation.js\";\nimport { round } from \"../utils/math.js\"; // eslint-disable-next-line import/no-unused-modules\n\nvar unsetSides = {\n top: 'auto',\n right: 'auto',\n bottom: 'auto',\n left: 'auto'\n}; // Round the offsets to the nearest suitable subpixel based on the DPR.\n// Zooming can change the DPR, but it seems to report a value that will\n// cleanly divide the values into the appropriate subpixels.\n\nfunction roundOffsetsByDPR(_ref, win) {\n var x = _ref.x,\n y = _ref.y;\n var dpr = win.devicePixelRatio || 1;\n return {\n x: round(x * dpr) / dpr || 0,\n y: round(y * dpr) / dpr || 0\n };\n}\n\nexport function mapToStyles(_ref2) {\n var _Object$assign2;\n\n var popper = _ref2.popper,\n popperRect = _ref2.popperRect,\n placement = _ref2.placement,\n variation = _ref2.variation,\n offsets = _ref2.offsets,\n position = _ref2.position,\n gpuAcceleration = _ref2.gpuAcceleration,\n adaptive = _ref2.adaptive,\n roundOffsets = _ref2.roundOffsets,\n isFixed = _ref2.isFixed;\n var _offsets$x = offsets.x,\n x = _offsets$x === void 0 ? 0 : _offsets$x,\n _offsets$y = offsets.y,\n y = _offsets$y === void 0 ? 0 : _offsets$y;\n\n var _ref3 = typeof roundOffsets === 'function' ? roundOffsets({\n x: x,\n y: y\n }) : {\n x: x,\n y: y\n };\n\n x = _ref3.x;\n y = _ref3.y;\n var hasX = offsets.hasOwnProperty('x');\n var hasY = offsets.hasOwnProperty('y');\n var sideX = left;\n var sideY = top;\n var win = window;\n\n if (adaptive) {\n var offsetParent = getOffsetParent(popper);\n var heightProp = 'clientHeight';\n var widthProp = 'clientWidth';\n\n if (offsetParent === getWindow(popper)) {\n offsetParent = getDocumentElement(popper);\n\n if (getComputedStyle(offsetParent).position !== 'static' && position === 'absolute') {\n heightProp = 'scrollHeight';\n widthProp = 'scrollWidth';\n }\n } // $FlowFixMe[incompatible-cast]: force type refinement, we compare offsetParent with window above, but Flow doesn't detect it\n\n\n offsetParent = offsetParent;\n\n if (placement === top || (placement === left || placement === right) && variation === end) {\n sideY = bottom;\n var offsetY = isFixed && offsetParent === win && win.visualViewport ? win.visualViewport.height : // $FlowFixMe[prop-missing]\n offsetParent[heightProp];\n y -= offsetY - popperRect.height;\n y *= gpuAcceleration ? 1 : -1;\n }\n\n if (placement === left || (placement === top || placement === bottom) && variation === end) {\n sideX = right;\n var offsetX = isFixed && offsetParent === win && win.visualViewport ? win.visualViewport.width : // $FlowFixMe[prop-missing]\n offsetParent[widthProp];\n x -= offsetX - popperRect.width;\n x *= gpuAcceleration ? 1 : -1;\n }\n }\n\n var commonStyles = Object.assign({\n position: position\n }, adaptive && unsetSides);\n\n var _ref4 = roundOffsets === true ? roundOffsetsByDPR({\n x: x,\n y: y\n }, getWindow(popper)) : {\n x: x,\n y: y\n };\n\n x = _ref4.x;\n y = _ref4.y;\n\n if (gpuAcceleration) {\n var _Object$assign;\n\n return Object.assign({}, commonStyles, (_Object$assign = {}, _Object$assign[sideY] = hasY ? '0' : '', _Object$assign[sideX] = hasX ? '0' : '', _Object$assign.transform = (win.devicePixelRatio || 1) <= 1 ? \"translate(\" + x + \"px, \" + y + \"px)\" : \"translate3d(\" + x + \"px, \" + y + \"px, 0)\", _Object$assign));\n }\n\n return Object.assign({}, commonStyles, (_Object$assign2 = {}, _Object$assign2[sideY] = hasY ? y + \"px\" : '', _Object$assign2[sideX] = hasX ? x + \"px\" : '', _Object$assign2.transform = '', _Object$assign2));\n}\n\nfunction computeStyles(_ref5) {\n var state = _ref5.state,\n options = _ref5.options;\n var _options$gpuAccelerat = options.gpuAcceleration,\n gpuAcceleration = _options$gpuAccelerat === void 0 ? true : _options$gpuAccelerat,\n _options$adaptive = options.adaptive,\n adaptive = _options$adaptive === void 0 ? true : _options$adaptive,\n _options$roundOffsets = options.roundOffsets,\n roundOffsets = _options$roundOffsets === void 0 ? true : _options$roundOffsets;\n var commonStyles = {\n placement: getBasePlacement(state.placement),\n variation: getVariation(state.placement),\n popper: state.elements.popper,\n popperRect: state.rects.popper,\n gpuAcceleration: gpuAcceleration,\n isFixed: state.options.strategy === 'fixed'\n };\n\n if (state.modifiersData.popperOffsets != null) {\n state.styles.popper = Object.assign({}, state.styles.popper, mapToStyles(Object.assign({}, commonStyles, {\n offsets: state.modifiersData.popperOffsets,\n position: state.options.strategy,\n adaptive: adaptive,\n roundOffsets: roundOffsets\n })));\n }\n\n if (state.modifiersData.arrow != null) {\n state.styles.arrow = Object.assign({}, state.styles.arrow, mapToStyles(Object.assign({}, commonStyles, {\n offsets: state.modifiersData.arrow,\n position: 'absolute',\n adaptive: false,\n roundOffsets: roundOffsets\n })));\n }\n\n state.attributes.popper = Object.assign({}, state.attributes.popper, {\n 'data-popper-placement': state.placement\n });\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'computeStyles',\n enabled: true,\n phase: 'beforeWrite',\n fn: computeStyles,\n data: {}\n};","import getWindow from \"../dom-utils/getWindow.js\"; // eslint-disable-next-line import/no-unused-modules\n\nvar passive = {\n passive: true\n};\n\nfunction effect(_ref) {\n var state = _ref.state,\n instance = _ref.instance,\n options = _ref.options;\n var _options$scroll = options.scroll,\n scroll = _options$scroll === void 0 ? true : _options$scroll,\n _options$resize = options.resize,\n resize = _options$resize === void 0 ? true : _options$resize;\n var window = getWindow(state.elements.popper);\n var scrollParents = [].concat(state.scrollParents.reference, state.scrollParents.popper);\n\n if (scroll) {\n scrollParents.forEach(function (scrollParent) {\n scrollParent.addEventListener('scroll', instance.update, passive);\n });\n }\n\n if (resize) {\n window.addEventListener('resize', instance.update, passive);\n }\n\n return function () {\n if (scroll) {\n scrollParents.forEach(function (scrollParent) {\n scrollParent.removeEventListener('scroll', instance.update, passive);\n });\n }\n\n if (resize) {\n window.removeEventListener('resize', instance.update, passive);\n }\n };\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'eventListeners',\n enabled: true,\n phase: 'write',\n fn: function fn() {},\n effect: effect,\n data: {}\n};","var hash = {\n left: 'right',\n right: 'left',\n bottom: 'top',\n top: 'bottom'\n};\nexport default function getOppositePlacement(placement) {\n return placement.replace(/left|right|bottom|top/g, function (matched) {\n return hash[matched];\n });\n}","var hash = {\n start: 'end',\n end: 'start'\n};\nexport default function getOppositeVariationPlacement(placement) {\n return placement.replace(/start|end/g, function (matched) {\n return hash[matched];\n });\n}","import getWindow from \"./getWindow.js\";\nexport default function getWindowScroll(node) {\n var win = getWindow(node);\n var scrollLeft = win.pageXOffset;\n var scrollTop = win.pageYOffset;\n return {\n scrollLeft: scrollLeft,\n scrollTop: scrollTop\n };\n}","import getBoundingClientRect from \"./getBoundingClientRect.js\";\nimport getDocumentElement from \"./getDocumentElement.js\";\nimport getWindowScroll from \"./getWindowScroll.js\";\nexport default function getWindowScrollBarX(element) {\n // If has a CSS width greater than the viewport, then this will be\n // incorrect for RTL.\n // Popper 1 is broken in this case and never had a bug report so let's assume\n // it's not an issue. I don't think anyone ever specifies width on \n // anyway.\n // Browsers where the left scrollbar doesn't cause an issue report `0` for\n // this (e.g. Edge 2019, IE11, Safari)\n return getBoundingClientRect(getDocumentElement(element)).left + getWindowScroll(element).scrollLeft;\n}","import getComputedStyle from \"./getComputedStyle.js\";\nexport default function isScrollParent(element) {\n // Firefox wants us to check `-x` and `-y` variations as well\n var _getComputedStyle = getComputedStyle(element),\n overflow = _getComputedStyle.overflow,\n overflowX = _getComputedStyle.overflowX,\n overflowY = _getComputedStyle.overflowY;\n\n return /auto|scroll|overlay|hidden/.test(overflow + overflowY + overflowX);\n}","import getParentNode from \"./getParentNode.js\";\nimport isScrollParent from \"./isScrollParent.js\";\nimport getNodeName from \"./getNodeName.js\";\nimport { isHTMLElement } from \"./instanceOf.js\";\nexport default function getScrollParent(node) {\n if (['html', 'body', '#document'].indexOf(getNodeName(node)) >= 0) {\n // $FlowFixMe[incompatible-return]: assume body is always available\n return node.ownerDocument.body;\n }\n\n if (isHTMLElement(node) && isScrollParent(node)) {\n return node;\n }\n\n return getScrollParent(getParentNode(node));\n}","import getScrollParent from \"./getScrollParent.js\";\nimport getParentNode from \"./getParentNode.js\";\nimport getWindow from \"./getWindow.js\";\nimport isScrollParent from \"./isScrollParent.js\";\n/*\ngiven a DOM element, return the list of all scroll parents, up the list of ancesors\nuntil we get to the top window object. This list is what we attach scroll listeners\nto, because if any of these parent elements scroll, we'll need to re-calculate the\nreference element's position.\n*/\n\nexport default function listScrollParents(element, list) {\n var _element$ownerDocumen;\n\n if (list === void 0) {\n list = [];\n }\n\n var scrollParent = getScrollParent(element);\n var isBody = scrollParent === ((_element$ownerDocumen = element.ownerDocument) == null ? void 0 : _element$ownerDocumen.body);\n var win = getWindow(scrollParent);\n var target = isBody ? [win].concat(win.visualViewport || [], isScrollParent(scrollParent) ? scrollParent : []) : scrollParent;\n var updatedList = list.concat(target);\n return isBody ? updatedList : // $FlowFixMe[incompatible-call]: isBody tells us target will be an HTMLElement here\n updatedList.concat(listScrollParents(getParentNode(target)));\n}","export default function rectToClientRect(rect) {\n return Object.assign({}, rect, {\n left: rect.x,\n top: rect.y,\n right: rect.x + rect.width,\n bottom: rect.y + rect.height\n });\n}","import { viewport } from \"../enums.js\";\nimport getViewportRect from \"./getViewportRect.js\";\nimport getDocumentRect from \"./getDocumentRect.js\";\nimport listScrollParents from \"./listScrollParents.js\";\nimport getOffsetParent from \"./getOffsetParent.js\";\nimport getDocumentElement from \"./getDocumentElement.js\";\nimport getComputedStyle from \"./getComputedStyle.js\";\nimport { isElement, isHTMLElement } from \"./instanceOf.js\";\nimport getBoundingClientRect from \"./getBoundingClientRect.js\";\nimport getParentNode from \"./getParentNode.js\";\nimport contains from \"./contains.js\";\nimport getNodeName from \"./getNodeName.js\";\nimport rectToClientRect from \"../utils/rectToClientRect.js\";\nimport { max, min } from \"../utils/math.js\";\n\nfunction getInnerBoundingClientRect(element, strategy) {\n var rect = getBoundingClientRect(element, false, strategy === 'fixed');\n rect.top = rect.top + element.clientTop;\n rect.left = rect.left + element.clientLeft;\n rect.bottom = rect.top + element.clientHeight;\n rect.right = rect.left + element.clientWidth;\n rect.width = element.clientWidth;\n rect.height = element.clientHeight;\n rect.x = rect.left;\n rect.y = rect.top;\n return rect;\n}\n\nfunction getClientRectFromMixedType(element, clippingParent, strategy) {\n return clippingParent === viewport ? rectToClientRect(getViewportRect(element, strategy)) : isElement(clippingParent) ? getInnerBoundingClientRect(clippingParent, strategy) : rectToClientRect(getDocumentRect(getDocumentElement(element)));\n} // A \"clipping parent\" is an overflowable container with the characteristic of\n// clipping (or hiding) overflowing elements with a position different from\n// `initial`\n\n\nfunction getClippingParents(element) {\n var clippingParents = listScrollParents(getParentNode(element));\n var canEscapeClipping = ['absolute', 'fixed'].indexOf(getComputedStyle(element).position) >= 0;\n var clipperElement = canEscapeClipping && isHTMLElement(element) ? getOffsetParent(element) : element;\n\n if (!isElement(clipperElement)) {\n return [];\n } // $FlowFixMe[incompatible-return]: https://github.com/facebook/flow/issues/1414\n\n\n return clippingParents.filter(function (clippingParent) {\n return isElement(clippingParent) && contains(clippingParent, clipperElement) && getNodeName(clippingParent) !== 'body';\n });\n} // Gets the maximum area that the element is visible in due to any number of\n// clipping parents\n\n\nexport default function getClippingRect(element, boundary, rootBoundary, strategy) {\n var mainClippingParents = boundary === 'clippingParents' ? getClippingParents(element) : [].concat(boundary);\n var clippingParents = [].concat(mainClippingParents, [rootBoundary]);\n var firstClippingParent = clippingParents[0];\n var clippingRect = clippingParents.reduce(function (accRect, clippingParent) {\n var rect = getClientRectFromMixedType(element, clippingParent, strategy);\n accRect.top = max(rect.top, accRect.top);\n accRect.right = min(rect.right, accRect.right);\n accRect.bottom = min(rect.bottom, accRect.bottom);\n accRect.left = max(rect.left, accRect.left);\n return accRect;\n }, getClientRectFromMixedType(element, firstClippingParent, strategy));\n clippingRect.width = clippingRect.right - clippingRect.left;\n clippingRect.height = clippingRect.bottom - clippingRect.top;\n clippingRect.x = clippingRect.left;\n clippingRect.y = clippingRect.top;\n return clippingRect;\n}","import getWindow from \"./getWindow.js\";\nimport getDocumentElement from \"./getDocumentElement.js\";\nimport getWindowScrollBarX from \"./getWindowScrollBarX.js\";\nimport isLayoutViewport from \"./isLayoutViewport.js\";\nexport default function getViewportRect(element, strategy) {\n var win = getWindow(element);\n var html = getDocumentElement(element);\n var visualViewport = win.visualViewport;\n var width = html.clientWidth;\n var height = html.clientHeight;\n var x = 0;\n var y = 0;\n\n if (visualViewport) {\n width = visualViewport.width;\n height = visualViewport.height;\n var layoutViewport = isLayoutViewport();\n\n if (layoutViewport || !layoutViewport && strategy === 'fixed') {\n x = visualViewport.offsetLeft;\n y = visualViewport.offsetTop;\n }\n }\n\n return {\n width: width,\n height: height,\n x: x + getWindowScrollBarX(element),\n y: y\n };\n}","import getDocumentElement from \"./getDocumentElement.js\";\nimport getComputedStyle from \"./getComputedStyle.js\";\nimport getWindowScrollBarX from \"./getWindowScrollBarX.js\";\nimport getWindowScroll from \"./getWindowScroll.js\";\nimport { max } from \"../utils/math.js\"; // Gets the entire size of the scrollable document area, even extending outside\n// of the `` and `` rect bounds if horizontally scrollable\n\nexport default function getDocumentRect(element) {\n var _element$ownerDocumen;\n\n var html = getDocumentElement(element);\n var winScroll = getWindowScroll(element);\n var body = (_element$ownerDocumen = element.ownerDocument) == null ? void 0 : _element$ownerDocumen.body;\n var width = max(html.scrollWidth, html.clientWidth, body ? body.scrollWidth : 0, body ? body.clientWidth : 0);\n var height = max(html.scrollHeight, html.clientHeight, body ? body.scrollHeight : 0, body ? body.clientHeight : 0);\n var x = -winScroll.scrollLeft + getWindowScrollBarX(element);\n var y = -winScroll.scrollTop;\n\n if (getComputedStyle(body || html).direction === 'rtl') {\n x += max(html.clientWidth, body ? body.clientWidth : 0) - width;\n }\n\n return {\n width: width,\n height: height,\n x: x,\n y: y\n };\n}","import getBasePlacement from \"./getBasePlacement.js\";\nimport getVariation from \"./getVariation.js\";\nimport getMainAxisFromPlacement from \"./getMainAxisFromPlacement.js\";\nimport { top, right, bottom, left, start, end } from \"../enums.js\";\nexport default function computeOffsets(_ref) {\n var reference = _ref.reference,\n element = _ref.element,\n placement = _ref.placement;\n var basePlacement = placement ? getBasePlacement(placement) : null;\n var variation = placement ? getVariation(placement) : null;\n var commonX = reference.x + reference.width / 2 - element.width / 2;\n var commonY = reference.y + reference.height / 2 - element.height / 2;\n var offsets;\n\n switch (basePlacement) {\n case top:\n offsets = {\n x: commonX,\n y: reference.y - element.height\n };\n break;\n\n case bottom:\n offsets = {\n x: commonX,\n y: reference.y + reference.height\n };\n break;\n\n case right:\n offsets = {\n x: reference.x + reference.width,\n y: commonY\n };\n break;\n\n case left:\n offsets = {\n x: reference.x - element.width,\n y: commonY\n };\n break;\n\n default:\n offsets = {\n x: reference.x,\n y: reference.y\n };\n }\n\n var mainAxis = basePlacement ? getMainAxisFromPlacement(basePlacement) : null;\n\n if (mainAxis != null) {\n var len = mainAxis === 'y' ? 'height' : 'width';\n\n switch (variation) {\n case start:\n offsets[mainAxis] = offsets[mainAxis] - (reference[len] / 2 - element[len] / 2);\n break;\n\n case end:\n offsets[mainAxis] = offsets[mainAxis] + (reference[len] / 2 - element[len] / 2);\n break;\n\n default:\n }\n }\n\n return offsets;\n}","import getClippingRect from \"../dom-utils/getClippingRect.js\";\nimport getDocumentElement from \"../dom-utils/getDocumentElement.js\";\nimport getBoundingClientRect from \"../dom-utils/getBoundingClientRect.js\";\nimport computeOffsets from \"./computeOffsets.js\";\nimport rectToClientRect from \"./rectToClientRect.js\";\nimport { clippingParents, reference, popper, bottom, top, right, basePlacements, viewport } from \"../enums.js\";\nimport { isElement } from \"../dom-utils/instanceOf.js\";\nimport mergePaddingObject from \"./mergePaddingObject.js\";\nimport expandToHashMap from \"./expandToHashMap.js\"; // eslint-disable-next-line import/no-unused-modules\n\nexport default function detectOverflow(state, options) {\n if (options === void 0) {\n options = {};\n }\n\n var _options = options,\n _options$placement = _options.placement,\n placement = _options$placement === void 0 ? state.placement : _options$placement,\n _options$strategy = _options.strategy,\n strategy = _options$strategy === void 0 ? state.strategy : _options$strategy,\n _options$boundary = _options.boundary,\n boundary = _options$boundary === void 0 ? clippingParents : _options$boundary,\n _options$rootBoundary = _options.rootBoundary,\n rootBoundary = _options$rootBoundary === void 0 ? viewport : _options$rootBoundary,\n _options$elementConte = _options.elementContext,\n elementContext = _options$elementConte === void 0 ? popper : _options$elementConte,\n _options$altBoundary = _options.altBoundary,\n altBoundary = _options$altBoundary === void 0 ? false : _options$altBoundary,\n _options$padding = _options.padding,\n padding = _options$padding === void 0 ? 0 : _options$padding;\n var paddingObject = mergePaddingObject(typeof padding !== 'number' ? padding : expandToHashMap(padding, basePlacements));\n var altContext = elementContext === popper ? reference : popper;\n var popperRect = state.rects.popper;\n var element = state.elements[altBoundary ? altContext : elementContext];\n var clippingClientRect = getClippingRect(isElement(element) ? element : element.contextElement || getDocumentElement(state.elements.popper), boundary, rootBoundary, strategy);\n var referenceClientRect = getBoundingClientRect(state.elements.reference);\n var popperOffsets = computeOffsets({\n reference: referenceClientRect,\n element: popperRect,\n strategy: 'absolute',\n placement: placement\n });\n var popperClientRect = rectToClientRect(Object.assign({}, popperRect, popperOffsets));\n var elementClientRect = elementContext === popper ? popperClientRect : referenceClientRect; // positive = overflowing the clipping rect\n // 0 or negative = within the clipping rect\n\n var overflowOffsets = {\n top: clippingClientRect.top - elementClientRect.top + paddingObject.top,\n bottom: elementClientRect.bottom - clippingClientRect.bottom + paddingObject.bottom,\n left: clippingClientRect.left - elementClientRect.left + paddingObject.left,\n right: elementClientRect.right - clippingClientRect.right + paddingObject.right\n };\n var offsetData = state.modifiersData.offset; // Offsets can be applied only to the popper element\n\n if (elementContext === popper && offsetData) {\n var offset = offsetData[placement];\n Object.keys(overflowOffsets).forEach(function (key) {\n var multiply = [right, bottom].indexOf(key) >= 0 ? 1 : -1;\n var axis = [top, bottom].indexOf(key) >= 0 ? 'y' : 'x';\n overflowOffsets[key] += offset[axis] * multiply;\n });\n }\n\n return overflowOffsets;\n}","import getVariation from \"./getVariation.js\";\nimport { variationPlacements, basePlacements, placements as allPlacements } from \"../enums.js\";\nimport detectOverflow from \"./detectOverflow.js\";\nimport getBasePlacement from \"./getBasePlacement.js\";\nexport default function computeAutoPlacement(state, options) {\n if (options === void 0) {\n options = {};\n }\n\n var _options = options,\n placement = _options.placement,\n boundary = _options.boundary,\n rootBoundary = _options.rootBoundary,\n padding = _options.padding,\n flipVariations = _options.flipVariations,\n _options$allowedAutoP = _options.allowedAutoPlacements,\n allowedAutoPlacements = _options$allowedAutoP === void 0 ? allPlacements : _options$allowedAutoP;\n var variation = getVariation(placement);\n var placements = variation ? flipVariations ? variationPlacements : variationPlacements.filter(function (placement) {\n return getVariation(placement) === variation;\n }) : basePlacements;\n var allowedPlacements = placements.filter(function (placement) {\n return allowedAutoPlacements.indexOf(placement) >= 0;\n });\n\n if (allowedPlacements.length === 0) {\n allowedPlacements = placements;\n } // $FlowFixMe[incompatible-type]: Flow seems to have problems with two array unions...\n\n\n var overflows = allowedPlacements.reduce(function (acc, placement) {\n acc[placement] = detectOverflow(state, {\n placement: placement,\n boundary: boundary,\n rootBoundary: rootBoundary,\n padding: padding\n })[getBasePlacement(placement)];\n return acc;\n }, {});\n return Object.keys(overflows).sort(function (a, b) {\n return overflows[a] - overflows[b];\n });\n}","import getOppositePlacement from \"../utils/getOppositePlacement.js\";\nimport getBasePlacement from \"../utils/getBasePlacement.js\";\nimport getOppositeVariationPlacement from \"../utils/getOppositeVariationPlacement.js\";\nimport detectOverflow from \"../utils/detectOverflow.js\";\nimport computeAutoPlacement from \"../utils/computeAutoPlacement.js\";\nimport { bottom, top, start, right, left, auto } from \"../enums.js\";\nimport getVariation from \"../utils/getVariation.js\"; // eslint-disable-next-line import/no-unused-modules\n\nfunction getExpandedFallbackPlacements(placement) {\n if (getBasePlacement(placement) === auto) {\n return [];\n }\n\n var oppositePlacement = getOppositePlacement(placement);\n return [getOppositeVariationPlacement(placement), oppositePlacement, getOppositeVariationPlacement(oppositePlacement)];\n}\n\nfunction flip(_ref) {\n var state = _ref.state,\n options = _ref.options,\n name = _ref.name;\n\n if (state.modifiersData[name]._skip) {\n return;\n }\n\n var _options$mainAxis = options.mainAxis,\n checkMainAxis = _options$mainAxis === void 0 ? true : _options$mainAxis,\n _options$altAxis = options.altAxis,\n checkAltAxis = _options$altAxis === void 0 ? true : _options$altAxis,\n specifiedFallbackPlacements = options.fallbackPlacements,\n padding = options.padding,\n boundary = options.boundary,\n rootBoundary = options.rootBoundary,\n altBoundary = options.altBoundary,\n _options$flipVariatio = options.flipVariations,\n flipVariations = _options$flipVariatio === void 0 ? true : _options$flipVariatio,\n allowedAutoPlacements = options.allowedAutoPlacements;\n var preferredPlacement = state.options.placement;\n var basePlacement = getBasePlacement(preferredPlacement);\n var isBasePlacement = basePlacement === preferredPlacement;\n var fallbackPlacements = specifiedFallbackPlacements || (isBasePlacement || !flipVariations ? [getOppositePlacement(preferredPlacement)] : getExpandedFallbackPlacements(preferredPlacement));\n var placements = [preferredPlacement].concat(fallbackPlacements).reduce(function (acc, placement) {\n return acc.concat(getBasePlacement(placement) === auto ? computeAutoPlacement(state, {\n placement: placement,\n boundary: boundary,\n rootBoundary: rootBoundary,\n padding: padding,\n flipVariations: flipVariations,\n allowedAutoPlacements: allowedAutoPlacements\n }) : placement);\n }, []);\n var referenceRect = state.rects.reference;\n var popperRect = state.rects.popper;\n var checksMap = new Map();\n var makeFallbackChecks = true;\n var firstFittingPlacement = placements[0];\n\n for (var i = 0; i < placements.length; i++) {\n var placement = placements[i];\n\n var _basePlacement = getBasePlacement(placement);\n\n var isStartVariation = getVariation(placement) === start;\n var isVertical = [top, bottom].indexOf(_basePlacement) >= 0;\n var len = isVertical ? 'width' : 'height';\n var overflow = detectOverflow(state, {\n placement: placement,\n boundary: boundary,\n rootBoundary: rootBoundary,\n altBoundary: altBoundary,\n padding: padding\n });\n var mainVariationSide = isVertical ? isStartVariation ? right : left : isStartVariation ? bottom : top;\n\n if (referenceRect[len] > popperRect[len]) {\n mainVariationSide = getOppositePlacement(mainVariationSide);\n }\n\n var altVariationSide = getOppositePlacement(mainVariationSide);\n var checks = [];\n\n if (checkMainAxis) {\n checks.push(overflow[_basePlacement] <= 0);\n }\n\n if (checkAltAxis) {\n checks.push(overflow[mainVariationSide] <= 0, overflow[altVariationSide] <= 0);\n }\n\n if (checks.every(function (check) {\n return check;\n })) {\n firstFittingPlacement = placement;\n makeFallbackChecks = false;\n break;\n }\n\n checksMap.set(placement, checks);\n }\n\n if (makeFallbackChecks) {\n // `2` may be desired in some cases – research later\n var numberOfChecks = flipVariations ? 3 : 1;\n\n var _loop = function _loop(_i) {\n var fittingPlacement = placements.find(function (placement) {\n var checks = checksMap.get(placement);\n\n if (checks) {\n return checks.slice(0, _i).every(function (check) {\n return check;\n });\n }\n });\n\n if (fittingPlacement) {\n firstFittingPlacement = fittingPlacement;\n return \"break\";\n }\n };\n\n for (var _i = numberOfChecks; _i > 0; _i--) {\n var _ret = _loop(_i);\n\n if (_ret === \"break\") break;\n }\n }\n\n if (state.placement !== firstFittingPlacement) {\n state.modifiersData[name]._skip = true;\n state.placement = firstFittingPlacement;\n state.reset = true;\n }\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'flip',\n enabled: true,\n phase: 'main',\n fn: flip,\n requiresIfExists: ['offset'],\n data: {\n _skip: false\n }\n};","import { top, bottom, left, right } from \"../enums.js\";\nimport detectOverflow from \"../utils/detectOverflow.js\";\n\nfunction getSideOffsets(overflow, rect, preventedOffsets) {\n if (preventedOffsets === void 0) {\n preventedOffsets = {\n x: 0,\n y: 0\n };\n }\n\n return {\n top: overflow.top - rect.height - preventedOffsets.y,\n right: overflow.right - rect.width + preventedOffsets.x,\n bottom: overflow.bottom - rect.height + preventedOffsets.y,\n left: overflow.left - rect.width - preventedOffsets.x\n };\n}\n\nfunction isAnySideFullyClipped(overflow) {\n return [top, right, bottom, left].some(function (side) {\n return overflow[side] >= 0;\n });\n}\n\nfunction hide(_ref) {\n var state = _ref.state,\n name = _ref.name;\n var referenceRect = state.rects.reference;\n var popperRect = state.rects.popper;\n var preventedOffsets = state.modifiersData.preventOverflow;\n var referenceOverflow = detectOverflow(state, {\n elementContext: 'reference'\n });\n var popperAltOverflow = detectOverflow(state, {\n altBoundary: true\n });\n var referenceClippingOffsets = getSideOffsets(referenceOverflow, referenceRect);\n var popperEscapeOffsets = getSideOffsets(popperAltOverflow, popperRect, preventedOffsets);\n var isReferenceHidden = isAnySideFullyClipped(referenceClippingOffsets);\n var hasPopperEscaped = isAnySideFullyClipped(popperEscapeOffsets);\n state.modifiersData[name] = {\n referenceClippingOffsets: referenceClippingOffsets,\n popperEscapeOffsets: popperEscapeOffsets,\n isReferenceHidden: isReferenceHidden,\n hasPopperEscaped: hasPopperEscaped\n };\n state.attributes.popper = Object.assign({}, state.attributes.popper, {\n 'data-popper-reference-hidden': isReferenceHidden,\n 'data-popper-escaped': hasPopperEscaped\n });\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'hide',\n enabled: true,\n phase: 'main',\n requiresIfExists: ['preventOverflow'],\n fn: hide\n};","import getBasePlacement from \"../utils/getBasePlacement.js\";\nimport { top, left, right, placements } from \"../enums.js\"; // eslint-disable-next-line import/no-unused-modules\n\nexport function distanceAndSkiddingToXY(placement, rects, offset) {\n var basePlacement = getBasePlacement(placement);\n var invertDistance = [left, top].indexOf(basePlacement) >= 0 ? -1 : 1;\n\n var _ref = typeof offset === 'function' ? offset(Object.assign({}, rects, {\n placement: placement\n })) : offset,\n skidding = _ref[0],\n distance = _ref[1];\n\n skidding = skidding || 0;\n distance = (distance || 0) * invertDistance;\n return [left, right].indexOf(basePlacement) >= 0 ? {\n x: distance,\n y: skidding\n } : {\n x: skidding,\n y: distance\n };\n}\n\nfunction offset(_ref2) {\n var state = _ref2.state,\n options = _ref2.options,\n name = _ref2.name;\n var _options$offset = options.offset,\n offset = _options$offset === void 0 ? [0, 0] : _options$offset;\n var data = placements.reduce(function (acc, placement) {\n acc[placement] = distanceAndSkiddingToXY(placement, state.rects, offset);\n return acc;\n }, {});\n var _data$state$placement = data[state.placement],\n x = _data$state$placement.x,\n y = _data$state$placement.y;\n\n if (state.modifiersData.popperOffsets != null) {\n state.modifiersData.popperOffsets.x += x;\n state.modifiersData.popperOffsets.y += y;\n }\n\n state.modifiersData[name] = data;\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'offset',\n enabled: true,\n phase: 'main',\n requires: ['popperOffsets'],\n fn: offset\n};","import computeOffsets from \"../utils/computeOffsets.js\";\n\nfunction popperOffsets(_ref) {\n var state = _ref.state,\n name = _ref.name;\n // Offsets are the actual position the popper needs to have to be\n // properly positioned near its reference element\n // This is the most basic placement, and will be adjusted by\n // the modifiers in the next step\n state.modifiersData[name] = computeOffsets({\n reference: state.rects.reference,\n element: state.rects.popper,\n strategy: 'absolute',\n placement: state.placement\n });\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'popperOffsets',\n enabled: true,\n phase: 'read',\n fn: popperOffsets,\n data: {}\n};","import { top, left, right, bottom, start } from \"../enums.js\";\nimport getBasePlacement from \"../utils/getBasePlacement.js\";\nimport getMainAxisFromPlacement from \"../utils/getMainAxisFromPlacement.js\";\nimport getAltAxis from \"../utils/getAltAxis.js\";\nimport { within, withinMaxClamp } from \"../utils/within.js\";\nimport getLayoutRect from \"../dom-utils/getLayoutRect.js\";\nimport getOffsetParent from \"../dom-utils/getOffsetParent.js\";\nimport detectOverflow from \"../utils/detectOverflow.js\";\nimport getVariation from \"../utils/getVariation.js\";\nimport getFreshSideObject from \"../utils/getFreshSideObject.js\";\nimport { min as mathMin, max as mathMax } from \"../utils/math.js\";\n\nfunction preventOverflow(_ref) {\n var state = _ref.state,\n options = _ref.options,\n name = _ref.name;\n var _options$mainAxis = options.mainAxis,\n checkMainAxis = _options$mainAxis === void 0 ? true : _options$mainAxis,\n _options$altAxis = options.altAxis,\n checkAltAxis = _options$altAxis === void 0 ? false : _options$altAxis,\n boundary = options.boundary,\n rootBoundary = options.rootBoundary,\n altBoundary = options.altBoundary,\n padding = options.padding,\n _options$tether = options.tether,\n tether = _options$tether === void 0 ? true : _options$tether,\n _options$tetherOffset = options.tetherOffset,\n tetherOffset = _options$tetherOffset === void 0 ? 0 : _options$tetherOffset;\n var overflow = detectOverflow(state, {\n boundary: boundary,\n rootBoundary: rootBoundary,\n padding: padding,\n altBoundary: altBoundary\n });\n var basePlacement = getBasePlacement(state.placement);\n var variation = getVariation(state.placement);\n var isBasePlacement = !variation;\n var mainAxis = getMainAxisFromPlacement(basePlacement);\n var altAxis = getAltAxis(mainAxis);\n var popperOffsets = state.modifiersData.popperOffsets;\n var referenceRect = state.rects.reference;\n var popperRect = state.rects.popper;\n var tetherOffsetValue = typeof tetherOffset === 'function' ? tetherOffset(Object.assign({}, state.rects, {\n placement: state.placement\n })) : tetherOffset;\n var normalizedTetherOffsetValue = typeof tetherOffsetValue === 'number' ? {\n mainAxis: tetherOffsetValue,\n altAxis: tetherOffsetValue\n } : Object.assign({\n mainAxis: 0,\n altAxis: 0\n }, tetherOffsetValue);\n var offsetModifierState = state.modifiersData.offset ? state.modifiersData.offset[state.placement] : null;\n var data = {\n x: 0,\n y: 0\n };\n\n if (!popperOffsets) {\n return;\n }\n\n if (checkMainAxis) {\n var _offsetModifierState$;\n\n var mainSide = mainAxis === 'y' ? top : left;\n var altSide = mainAxis === 'y' ? bottom : right;\n var len = mainAxis === 'y' ? 'height' : 'width';\n var offset = popperOffsets[mainAxis];\n var min = offset + overflow[mainSide];\n var max = offset - overflow[altSide];\n var additive = tether ? -popperRect[len] / 2 : 0;\n var minLen = variation === start ? referenceRect[len] : popperRect[len];\n var maxLen = variation === start ? -popperRect[len] : -referenceRect[len]; // We need to include the arrow in the calculation so the arrow doesn't go\n // outside the reference bounds\n\n var arrowElement = state.elements.arrow;\n var arrowRect = tether && arrowElement ? getLayoutRect(arrowElement) : {\n width: 0,\n height: 0\n };\n var arrowPaddingObject = state.modifiersData['arrow#persistent'] ? state.modifiersData['arrow#persistent'].padding : getFreshSideObject();\n var arrowPaddingMin = arrowPaddingObject[mainSide];\n var arrowPaddingMax = arrowPaddingObject[altSide]; // If the reference length is smaller than the arrow length, we don't want\n // to include its full size in the calculation. If the reference is small\n // and near the edge of a boundary, the popper can overflow even if the\n // reference is not overflowing as well (e.g. virtual elements with no\n // width or height)\n\n var arrowLen = within(0, referenceRect[len], arrowRect[len]);\n var minOffset = isBasePlacement ? referenceRect[len] / 2 - additive - arrowLen - arrowPaddingMin - normalizedTetherOffsetValue.mainAxis : minLen - arrowLen - arrowPaddingMin - normalizedTetherOffsetValue.mainAxis;\n var maxOffset = isBasePlacement ? -referenceRect[len] / 2 + additive + arrowLen + arrowPaddingMax + normalizedTetherOffsetValue.mainAxis : maxLen + arrowLen + arrowPaddingMax + normalizedTetherOffsetValue.mainAxis;\n var arrowOffsetParent = state.elements.arrow && getOffsetParent(state.elements.arrow);\n var clientOffset = arrowOffsetParent ? mainAxis === 'y' ? arrowOffsetParent.clientTop || 0 : arrowOffsetParent.clientLeft || 0 : 0;\n var offsetModifierValue = (_offsetModifierState$ = offsetModifierState == null ? void 0 : offsetModifierState[mainAxis]) != null ? _offsetModifierState$ : 0;\n var tetherMin = offset + minOffset - offsetModifierValue - clientOffset;\n var tetherMax = offset + maxOffset - offsetModifierValue;\n var preventedOffset = within(tether ? mathMin(min, tetherMin) : min, offset, tether ? mathMax(max, tetherMax) : max);\n popperOffsets[mainAxis] = preventedOffset;\n data[mainAxis] = preventedOffset - offset;\n }\n\n if (checkAltAxis) {\n var _offsetModifierState$2;\n\n var _mainSide = mainAxis === 'x' ? top : left;\n\n var _altSide = mainAxis === 'x' ? bottom : right;\n\n var _offset = popperOffsets[altAxis];\n\n var _len = altAxis === 'y' ? 'height' : 'width';\n\n var _min = _offset + overflow[_mainSide];\n\n var _max = _offset - overflow[_altSide];\n\n var isOriginSide = [top, left].indexOf(basePlacement) !== -1;\n\n var _offsetModifierValue = (_offsetModifierState$2 = offsetModifierState == null ? void 0 : offsetModifierState[altAxis]) != null ? _offsetModifierState$2 : 0;\n\n var _tetherMin = isOriginSide ? _min : _offset - referenceRect[_len] - popperRect[_len] - _offsetModifierValue + normalizedTetherOffsetValue.altAxis;\n\n var _tetherMax = isOriginSide ? _offset + referenceRect[_len] + popperRect[_len] - _offsetModifierValue - normalizedTetherOffsetValue.altAxis : _max;\n\n var _preventedOffset = tether && isOriginSide ? withinMaxClamp(_tetherMin, _offset, _tetherMax) : within(tether ? _tetherMin : _min, _offset, tether ? _tetherMax : _max);\n\n popperOffsets[altAxis] = _preventedOffset;\n data[altAxis] = _preventedOffset - _offset;\n }\n\n state.modifiersData[name] = data;\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'preventOverflow',\n enabled: true,\n phase: 'main',\n fn: preventOverflow,\n requiresIfExists: ['offset']\n};","export default function getAltAxis(axis) {\n return axis === 'x' ? 'y' : 'x';\n}","import getBoundingClientRect from \"./getBoundingClientRect.js\";\nimport getNodeScroll from \"./getNodeScroll.js\";\nimport getNodeName from \"./getNodeName.js\";\nimport { isHTMLElement } from \"./instanceOf.js\";\nimport getWindowScrollBarX from \"./getWindowScrollBarX.js\";\nimport getDocumentElement from \"./getDocumentElement.js\";\nimport isScrollParent from \"./isScrollParent.js\";\nimport { round } from \"../utils/math.js\";\n\nfunction isElementScaled(element) {\n var rect = element.getBoundingClientRect();\n var scaleX = round(rect.width) / element.offsetWidth || 1;\n var scaleY = round(rect.height) / element.offsetHeight || 1;\n return scaleX !== 1 || scaleY !== 1;\n} // Returns the composite rect of an element relative to its offsetParent.\n// Composite means it takes into account transforms as well as layout.\n\n\nexport default function getCompositeRect(elementOrVirtualElement, offsetParent, isFixed) {\n if (isFixed === void 0) {\n isFixed = false;\n }\n\n var isOffsetParentAnElement = isHTMLElement(offsetParent);\n var offsetParentIsScaled = isHTMLElement(offsetParent) && isElementScaled(offsetParent);\n var documentElement = getDocumentElement(offsetParent);\n var rect = getBoundingClientRect(elementOrVirtualElement, offsetParentIsScaled, isFixed);\n var scroll = {\n scrollLeft: 0,\n scrollTop: 0\n };\n var offsets = {\n x: 0,\n y: 0\n };\n\n if (isOffsetParentAnElement || !isOffsetParentAnElement && !isFixed) {\n if (getNodeName(offsetParent) !== 'body' || // https://github.com/popperjs/popper-core/issues/1078\n isScrollParent(documentElement)) {\n scroll = getNodeScroll(offsetParent);\n }\n\n if (isHTMLElement(offsetParent)) {\n offsets = getBoundingClientRect(offsetParent, true);\n offsets.x += offsetParent.clientLeft;\n offsets.y += offsetParent.clientTop;\n } else if (documentElement) {\n offsets.x = getWindowScrollBarX(documentElement);\n }\n }\n\n return {\n x: rect.left + scroll.scrollLeft - offsets.x,\n y: rect.top + scroll.scrollTop - offsets.y,\n width: rect.width,\n height: rect.height\n };\n}","import getWindowScroll from \"./getWindowScroll.js\";\nimport getWindow from \"./getWindow.js\";\nimport { isHTMLElement } from \"./instanceOf.js\";\nimport getHTMLElementScroll from \"./getHTMLElementScroll.js\";\nexport default function getNodeScroll(node) {\n if (node === getWindow(node) || !isHTMLElement(node)) {\n return getWindowScroll(node);\n } else {\n return getHTMLElementScroll(node);\n }\n}","export default function getHTMLElementScroll(element) {\n return {\n scrollLeft: element.scrollLeft,\n scrollTop: element.scrollTop\n };\n}","import { modifierPhases } from \"../enums.js\"; // source: https://stackoverflow.com/questions/49875255\n\nfunction order(modifiers) {\n var map = new Map();\n var visited = new Set();\n var result = [];\n modifiers.forEach(function (modifier) {\n map.set(modifier.name, modifier);\n }); // On visiting object, check for its dependencies and visit them recursively\n\n function sort(modifier) {\n visited.add(modifier.name);\n var requires = [].concat(modifier.requires || [], modifier.requiresIfExists || []);\n requires.forEach(function (dep) {\n if (!visited.has(dep)) {\n var depModifier = map.get(dep);\n\n if (depModifier) {\n sort(depModifier);\n }\n }\n });\n result.push(modifier);\n }\n\n modifiers.forEach(function (modifier) {\n if (!visited.has(modifier.name)) {\n // check for visited object\n sort(modifier);\n }\n });\n return result;\n}\n\nexport default function orderModifiers(modifiers) {\n // order based on dependencies\n var orderedModifiers = order(modifiers); // order based on phase\n\n return modifierPhases.reduce(function (acc, phase) {\n return acc.concat(orderedModifiers.filter(function (modifier) {\n return modifier.phase === phase;\n }));\n }, []);\n}","import getCompositeRect from \"./dom-utils/getCompositeRect.js\";\nimport getLayoutRect from \"./dom-utils/getLayoutRect.js\";\nimport listScrollParents from \"./dom-utils/listScrollParents.js\";\nimport getOffsetParent from \"./dom-utils/getOffsetParent.js\";\nimport orderModifiers from \"./utils/orderModifiers.js\";\nimport debounce from \"./utils/debounce.js\";\nimport mergeByName from \"./utils/mergeByName.js\";\nimport detectOverflow from \"./utils/detectOverflow.js\";\nimport { isElement } from \"./dom-utils/instanceOf.js\";\nvar DEFAULT_OPTIONS = {\n placement: 'bottom',\n modifiers: [],\n strategy: 'absolute'\n};\n\nfunction areValidElements() {\n for (var _len = arguments.length, args = new Array(_len), _key = 0; _key < _len; _key++) {\n args[_key] = arguments[_key];\n }\n\n return !args.some(function (element) {\n return !(element && typeof element.getBoundingClientRect === 'function');\n });\n}\n\nexport function popperGenerator(generatorOptions) {\n if (generatorOptions === void 0) {\n generatorOptions = {};\n }\n\n var _generatorOptions = generatorOptions,\n _generatorOptions$def = _generatorOptions.defaultModifiers,\n defaultModifiers = _generatorOptions$def === void 0 ? [] : _generatorOptions$def,\n _generatorOptions$def2 = _generatorOptions.defaultOptions,\n defaultOptions = _generatorOptions$def2 === void 0 ? DEFAULT_OPTIONS : _generatorOptions$def2;\n return function createPopper(reference, popper, options) {\n if (options === void 0) {\n options = defaultOptions;\n }\n\n var state = {\n placement: 'bottom',\n orderedModifiers: [],\n options: Object.assign({}, DEFAULT_OPTIONS, defaultOptions),\n modifiersData: {},\n elements: {\n reference: reference,\n popper: popper\n },\n attributes: {},\n styles: {}\n };\n var effectCleanupFns = [];\n var isDestroyed = false;\n var instance = {\n state: state,\n setOptions: function setOptions(setOptionsAction) {\n var options = typeof setOptionsAction === 'function' ? setOptionsAction(state.options) : setOptionsAction;\n cleanupModifierEffects();\n state.options = Object.assign({}, defaultOptions, state.options, options);\n state.scrollParents = {\n reference: isElement(reference) ? listScrollParents(reference) : reference.contextElement ? listScrollParents(reference.contextElement) : [],\n popper: listScrollParents(popper)\n }; // Orders the modifiers based on their dependencies and `phase`\n // properties\n\n var orderedModifiers = orderModifiers(mergeByName([].concat(defaultModifiers, state.options.modifiers))); // Strip out disabled modifiers\n\n state.orderedModifiers = orderedModifiers.filter(function (m) {\n return m.enabled;\n });\n runModifierEffects();\n return instance.update();\n },\n // Sync update – it will always be executed, even if not necessary. This\n // is useful for low frequency updates where sync behavior simplifies the\n // logic.\n // For high frequency updates (e.g. `resize` and `scroll` events), always\n // prefer the async Popper#update method\n forceUpdate: function forceUpdate() {\n if (isDestroyed) {\n return;\n }\n\n var _state$elements = state.elements,\n reference = _state$elements.reference,\n popper = _state$elements.popper; // Don't proceed if `reference` or `popper` are not valid elements\n // anymore\n\n if (!areValidElements(reference, popper)) {\n return;\n } // Store the reference and popper rects to be read by modifiers\n\n\n state.rects = {\n reference: getCompositeRect(reference, getOffsetParent(popper), state.options.strategy === 'fixed'),\n popper: getLayoutRect(popper)\n }; // Modifiers have the ability to reset the current update cycle. The\n // most common use case for this is the `flip` modifier changing the\n // placement, which then needs to re-run all the modifiers, because the\n // logic was previously ran for the previous placement and is therefore\n // stale/incorrect\n\n state.reset = false;\n state.placement = state.options.placement; // On each update cycle, the `modifiersData` property for each modifier\n // is filled with the initial data specified by the modifier. This means\n // it doesn't persist and is fresh on each update.\n // To ensure persistent data, use `${name}#persistent`\n\n state.orderedModifiers.forEach(function (modifier) {\n return state.modifiersData[modifier.name] = Object.assign({}, modifier.data);\n });\n\n for (var index = 0; index < state.orderedModifiers.length; index++) {\n if (state.reset === true) {\n state.reset = false;\n index = -1;\n continue;\n }\n\n var _state$orderedModifie = state.orderedModifiers[index],\n fn = _state$orderedModifie.fn,\n _state$orderedModifie2 = _state$orderedModifie.options,\n _options = _state$orderedModifie2 === void 0 ? {} : _state$orderedModifie2,\n name = _state$orderedModifie.name;\n\n if (typeof fn === 'function') {\n state = fn({\n state: state,\n options: _options,\n name: name,\n instance: instance\n }) || state;\n }\n }\n },\n // Async and optimistically optimized update – it will not be executed if\n // not necessary (debounced to run at most once-per-tick)\n update: debounce(function () {\n return new Promise(function (resolve) {\n instance.forceUpdate();\n resolve(state);\n });\n }),\n destroy: function destroy() {\n cleanupModifierEffects();\n isDestroyed = true;\n }\n };\n\n if (!areValidElements(reference, popper)) {\n return instance;\n }\n\n instance.setOptions(options).then(function (state) {\n if (!isDestroyed && options.onFirstUpdate) {\n options.onFirstUpdate(state);\n }\n }); // Modifiers have the ability to execute arbitrary code before the first\n // update cycle runs. They will be executed in the same order as the update\n // cycle. This is useful when a modifier adds some persistent data that\n // other modifiers need to use, but the modifier is run after the dependent\n // one.\n\n function runModifierEffects() {\n state.orderedModifiers.forEach(function (_ref) {\n var name = _ref.name,\n _ref$options = _ref.options,\n options = _ref$options === void 0 ? {} : _ref$options,\n effect = _ref.effect;\n\n if (typeof effect === 'function') {\n var cleanupFn = effect({\n state: state,\n name: name,\n instance: instance,\n options: options\n });\n\n var noopFn = function noopFn() {};\n\n effectCleanupFns.push(cleanupFn || noopFn);\n }\n });\n }\n\n function cleanupModifierEffects() {\n effectCleanupFns.forEach(function (fn) {\n return fn();\n });\n effectCleanupFns = [];\n }\n\n return instance;\n };\n}\nexport var createPopper = /*#__PURE__*/popperGenerator(); // eslint-disable-next-line import/no-unused-modules\n\nexport { detectOverflow };","export default function debounce(fn) {\n var pending;\n return function () {\n if (!pending) {\n pending = new Promise(function (resolve) {\n Promise.resolve().then(function () {\n pending = undefined;\n resolve(fn());\n });\n });\n }\n\n return pending;\n };\n}","export default function mergeByName(modifiers) {\n var merged = modifiers.reduce(function (merged, current) {\n var existing = merged[current.name];\n merged[current.name] = existing ? Object.assign({}, existing, current, {\n options: Object.assign({}, existing.options, current.options),\n data: Object.assign({}, existing.data, current.data)\n }) : current;\n return merged;\n }, {}); // IE11 does not support Object.values\n\n return Object.keys(merged).map(function (key) {\n return merged[key];\n });\n}","import { popperGenerator, detectOverflow } from \"./createPopper.js\";\nimport eventListeners from \"./modifiers/eventListeners.js\";\nimport popperOffsets from \"./modifiers/popperOffsets.js\";\nimport computeStyles from \"./modifiers/computeStyles.js\";\nimport applyStyles from \"./modifiers/applyStyles.js\";\nvar defaultModifiers = [eventListeners, popperOffsets, computeStyles, applyStyles];\nvar createPopper = /*#__PURE__*/popperGenerator({\n defaultModifiers: defaultModifiers\n}); // eslint-disable-next-line import/no-unused-modules\n\nexport { createPopper, popperGenerator, defaultModifiers, detectOverflow };","import { popperGenerator, detectOverflow } from \"./createPopper.js\";\nimport eventListeners from \"./modifiers/eventListeners.js\";\nimport popperOffsets from \"./modifiers/popperOffsets.js\";\nimport computeStyles from \"./modifiers/computeStyles.js\";\nimport applyStyles from \"./modifiers/applyStyles.js\";\nimport offset from \"./modifiers/offset.js\";\nimport flip from \"./modifiers/flip.js\";\nimport preventOverflow from \"./modifiers/preventOverflow.js\";\nimport arrow from \"./modifiers/arrow.js\";\nimport hide from \"./modifiers/hide.js\";\nvar defaultModifiers = [eventListeners, popperOffsets, computeStyles, applyStyles, offset, flip, preventOverflow, arrow, hide];\nvar createPopper = /*#__PURE__*/popperGenerator({\n defaultModifiers: defaultModifiers\n}); // eslint-disable-next-line import/no-unused-modules\n\nexport { createPopper, popperGenerator, defaultModifiers, detectOverflow }; // eslint-disable-next-line import/no-unused-modules\n\nexport { createPopper as createPopperLite } from \"./popper-lite.js\"; // eslint-disable-next-line import/no-unused-modules\n\nexport * from \"./modifiers/index.js\";","/**\n * --------------------------------------------------------------------------\n * Bootstrap dropdown.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport * as Popper from '@popperjs/core'\nimport BaseComponent from './base-component.js'\nimport EventHandler from './dom/event-handler.js'\nimport Manipulator from './dom/manipulator.js'\nimport SelectorEngine from './dom/selector-engine.js'\nimport {\n defineJQueryPlugin,\n execute,\n getElement,\n getNextActiveElement,\n isDisabled,\n isElement,\n isRTL,\n isVisible,\n noop\n} from './util/index.js'\n\n/**\n * Constants\n */\n\nconst NAME = 'dropdown'\nconst DATA_KEY = 'bs.dropdown'\nconst EVENT_KEY = `.${DATA_KEY}`\nconst DATA_API_KEY = '.data-api'\n\nconst ESCAPE_KEY = 'Escape'\nconst TAB_KEY = 'Tab'\nconst ARROW_UP_KEY = 'ArrowUp'\nconst ARROW_DOWN_KEY = 'ArrowDown'\nconst RIGHT_MOUSE_BUTTON = 2 // MouseEvent.button value for the secondary button, usually the right button\n\nconst EVENT_HIDE = `hide${EVENT_KEY}`\nconst EVENT_HIDDEN = `hidden${EVENT_KEY}`\nconst EVENT_SHOW = `show${EVENT_KEY}`\nconst EVENT_SHOWN = `shown${EVENT_KEY}`\nconst EVENT_CLICK_DATA_API = `click${EVENT_KEY}${DATA_API_KEY}`\nconst EVENT_KEYDOWN_DATA_API = `keydown${EVENT_KEY}${DATA_API_KEY}`\nconst EVENT_KEYUP_DATA_API = `keyup${EVENT_KEY}${DATA_API_KEY}`\n\nconst CLASS_NAME_SHOW = 'show'\nconst CLASS_NAME_DROPUP = 'dropup'\nconst CLASS_NAME_DROPEND = 'dropend'\nconst CLASS_NAME_DROPSTART = 'dropstart'\nconst CLASS_NAME_DROPUP_CENTER = 'dropup-center'\nconst CLASS_NAME_DROPDOWN_CENTER = 'dropdown-center'\n\nconst SELECTOR_DATA_TOGGLE = '[data-bs-toggle=\"dropdown\"]:not(.disabled):not(:disabled)'\nconst SELECTOR_DATA_TOGGLE_SHOWN = `${SELECTOR_DATA_TOGGLE}.${CLASS_NAME_SHOW}`\nconst SELECTOR_MENU = '.dropdown-menu'\nconst SELECTOR_NAVBAR = '.navbar'\nconst SELECTOR_NAVBAR_NAV = '.navbar-nav'\nconst SELECTOR_VISIBLE_ITEMS = '.dropdown-menu .dropdown-item:not(.disabled):not(:disabled)'\n\nconst PLACEMENT_TOP = isRTL() ? 'top-end' : 'top-start'\nconst PLACEMENT_TOPEND = isRTL() ? 'top-start' : 'top-end'\nconst PLACEMENT_BOTTOM = isRTL() ? 'bottom-end' : 'bottom-start'\nconst PLACEMENT_BOTTOMEND = isRTL() ? 'bottom-start' : 'bottom-end'\nconst PLACEMENT_RIGHT = isRTL() ? 'left-start' : 'right-start'\nconst PLACEMENT_LEFT = isRTL() ? 'right-start' : 'left-start'\nconst PLACEMENT_TOPCENTER = 'top'\nconst PLACEMENT_BOTTOMCENTER = 'bottom'\n\nconst Default = {\n autoClose: true,\n boundary: 'clippingParents',\n display: 'dynamic',\n offset: [0, 2],\n popperConfig: null,\n reference: 'toggle'\n}\n\nconst DefaultType = {\n autoClose: '(boolean|string)',\n boundary: '(string|element)',\n display: 'string',\n offset: '(array|string|function)',\n popperConfig: '(null|object|function)',\n reference: '(string|element|object)'\n}\n\n/**\n * Class definition\n */\n\nclass Dropdown extends BaseComponent {\n constructor(element, config) {\n super(element, config)\n\n this._popper = null\n this._parent = this._element.parentNode // dropdown wrapper\n // TODO: v6 revert #37011 & change markup https://getbootstrap.com/docs/5.3/forms/input-group/\n this._menu = SelectorEngine.next(this._element, SELECTOR_MENU)[0] ||\n SelectorEngine.prev(this._element, SELECTOR_MENU)[0] ||\n SelectorEngine.findOne(SELECTOR_MENU, this._parent)\n this._inNavbar = this._detectNavbar()\n }\n\n // Getters\n static get Default() {\n return Default\n }\n\n static get DefaultType() {\n return DefaultType\n }\n\n static get NAME() {\n return NAME\n }\n\n // Public\n toggle() {\n return this._isShown() ? this.hide() : this.show()\n }\n\n show() {\n if (isDisabled(this._element) || this._isShown()) {\n return\n }\n\n const relatedTarget = {\n relatedTarget: this._element\n }\n\n const showEvent = EventHandler.trigger(this._element, EVENT_SHOW, relatedTarget)\n\n if (showEvent.defaultPrevented) {\n return\n }\n\n this._createPopper()\n\n // If this is a touch-enabled device we add extra\n // empty mouseover listeners to the body's immediate children;\n // only needed because of broken event delegation on iOS\n // https://www.quirksmode.org/blog/archives/2014/02/mouse_event_bub.html\n if ('ontouchstart' in document.documentElement && !this._parent.closest(SELECTOR_NAVBAR_NAV)) {\n for (const element of [].concat(...document.body.children)) {\n EventHandler.on(element, 'mouseover', noop)\n }\n }\n\n this._element.focus()\n this._element.setAttribute('aria-expanded', true)\n\n this._menu.classList.add(CLASS_NAME_SHOW)\n this._element.classList.add(CLASS_NAME_SHOW)\n EventHandler.trigger(this._element, EVENT_SHOWN, relatedTarget)\n }\n\n hide() {\n if (isDisabled(this._element) || !this._isShown()) {\n return\n }\n\n const relatedTarget = {\n relatedTarget: this._element\n }\n\n this._completeHide(relatedTarget)\n }\n\n dispose() {\n if (this._popper) {\n this._popper.destroy()\n }\n\n super.dispose()\n }\n\n update() {\n this._inNavbar = this._detectNavbar()\n if (this._popper) {\n this._popper.update()\n }\n }\n\n // Private\n _completeHide(relatedTarget) {\n const hideEvent = EventHandler.trigger(this._element, EVENT_HIDE, relatedTarget)\n if (hideEvent.defaultPrevented) {\n return\n }\n\n // If this is a touch-enabled device we remove the extra\n // empty mouseover listeners we added for iOS support\n if ('ontouchstart' in document.documentElement) {\n for (const element of [].concat(...document.body.children)) {\n EventHandler.off(element, 'mouseover', noop)\n }\n }\n\n if (this._popper) {\n this._popper.destroy()\n }\n\n this._menu.classList.remove(CLASS_NAME_SHOW)\n this._element.classList.remove(CLASS_NAME_SHOW)\n this._element.setAttribute('aria-expanded', 'false')\n Manipulator.removeDataAttribute(this._menu, 'popper')\n EventHandler.trigger(this._element, EVENT_HIDDEN, relatedTarget)\n }\n\n _getConfig(config) {\n config = super._getConfig(config)\n\n if (typeof config.reference === 'object' && !isElement(config.reference) &&\n typeof config.reference.getBoundingClientRect !== 'function'\n ) {\n // Popper virtual elements require a getBoundingClientRect method\n throw new TypeError(`${NAME.toUpperCase()}: Option \"reference\" provided type \"object\" without a required \"getBoundingClientRect\" method.`)\n }\n\n return config\n }\n\n _createPopper() {\n if (typeof Popper === 'undefined') {\n throw new TypeError('Bootstrap\\'s dropdowns require Popper (https://popper.js.org)')\n }\n\n let referenceElement = this._element\n\n if (this._config.reference === 'parent') {\n referenceElement = this._parent\n } else if (isElement(this._config.reference)) {\n referenceElement = getElement(this._config.reference)\n } else if (typeof this._config.reference === 'object') {\n referenceElement = this._config.reference\n }\n\n const popperConfig = this._getPopperConfig()\n this._popper = Popper.createPopper(referenceElement, this._menu, popperConfig)\n }\n\n _isShown() {\n return this._menu.classList.contains(CLASS_NAME_SHOW)\n }\n\n _getPlacement() {\n const parentDropdown = this._parent\n\n if (parentDropdown.classList.contains(CLASS_NAME_DROPEND)) {\n return PLACEMENT_RIGHT\n }\n\n if (parentDropdown.classList.contains(CLASS_NAME_DROPSTART)) {\n return PLACEMENT_LEFT\n }\n\n if (parentDropdown.classList.contains(CLASS_NAME_DROPUP_CENTER)) {\n return PLACEMENT_TOPCENTER\n }\n\n if (parentDropdown.classList.contains(CLASS_NAME_DROPDOWN_CENTER)) {\n return PLACEMENT_BOTTOMCENTER\n }\n\n // We need to trim the value because custom properties can also include spaces\n const isEnd = getComputedStyle(this._menu).getPropertyValue('--bs-position').trim() === 'end'\n\n if (parentDropdown.classList.contains(CLASS_NAME_DROPUP)) {\n return isEnd ? PLACEMENT_TOPEND : PLACEMENT_TOP\n }\n\n return isEnd ? PLACEMENT_BOTTOMEND : PLACEMENT_BOTTOM\n }\n\n _detectNavbar() {\n return this._element.closest(SELECTOR_NAVBAR) !== null\n }\n\n _getOffset() {\n const { offset } = this._config\n\n if (typeof offset === 'string') {\n return offset.split(',').map(value => Number.parseInt(value, 10))\n }\n\n if (typeof offset === 'function') {\n return popperData => offset(popperData, this._element)\n }\n\n return offset\n }\n\n _getPopperConfig() {\n const defaultBsPopperConfig = {\n placement: this._getPlacement(),\n modifiers: [{\n name: 'preventOverflow',\n options: {\n boundary: this._config.boundary\n }\n },\n {\n name: 'offset',\n options: {\n offset: this._getOffset()\n }\n }]\n }\n\n // Disable Popper if we have a static display or Dropdown is in Navbar\n if (this._inNavbar || this._config.display === 'static') {\n Manipulator.setDataAttribute(this._menu, 'popper', 'static') // TODO: v6 remove\n defaultBsPopperConfig.modifiers = [{\n name: 'applyStyles',\n enabled: false\n }]\n }\n\n return {\n ...defaultBsPopperConfig,\n ...execute(this._config.popperConfig, [defaultBsPopperConfig])\n }\n }\n\n _selectMenuItem({ key, target }) {\n const items = SelectorEngine.find(SELECTOR_VISIBLE_ITEMS, this._menu).filter(element => isVisible(element))\n\n if (!items.length) {\n return\n }\n\n // if target isn't included in items (e.g. when expanding the dropdown)\n // allow cycling to get the last item in case key equals ARROW_UP_KEY\n getNextActiveElement(items, target, key === ARROW_DOWN_KEY, !items.includes(target)).focus()\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Dropdown.getOrCreateInstance(this, config)\n\n if (typeof config !== 'string') {\n return\n }\n\n if (typeof data[config] === 'undefined') {\n throw new TypeError(`No method named \"${config}\"`)\n }\n\n data[config]()\n })\n }\n\n static clearMenus(event) {\n if (event.button === RIGHT_MOUSE_BUTTON || (event.type === 'keyup' && event.key !== TAB_KEY)) {\n return\n }\n\n const openToggles = SelectorEngine.find(SELECTOR_DATA_TOGGLE_SHOWN)\n\n for (const toggle of openToggles) {\n const context = Dropdown.getInstance(toggle)\n if (!context || context._config.autoClose === false) {\n continue\n }\n\n const composedPath = event.composedPath()\n const isMenuTarget = composedPath.includes(context._menu)\n if (\n composedPath.includes(context._element) ||\n (context._config.autoClose === 'inside' && !isMenuTarget) ||\n (context._config.autoClose === 'outside' && isMenuTarget)\n ) {\n continue\n }\n\n // Tab navigation through the dropdown menu or events from contained inputs shouldn't close the menu\n if (context._menu.contains(event.target) && ((event.type === 'keyup' && event.key === TAB_KEY) || /input|select|option|textarea|form/i.test(event.target.tagName))) {\n continue\n }\n\n const relatedTarget = { relatedTarget: context._element }\n\n if (event.type === 'click') {\n relatedTarget.clickEvent = event\n }\n\n context._completeHide(relatedTarget)\n }\n }\n\n static dataApiKeydownHandler(event) {\n // If not an UP | DOWN | ESCAPE key => not a dropdown command\n // If input/textarea && if key is other than ESCAPE => not a dropdown command\n\n const isInput = /input|textarea/i.test(event.target.tagName)\n const isEscapeEvent = event.key === ESCAPE_KEY\n const isUpOrDownEvent = [ARROW_UP_KEY, ARROW_DOWN_KEY].includes(event.key)\n\n if (!isUpOrDownEvent && !isEscapeEvent) {\n return\n }\n\n if (isInput && !isEscapeEvent) {\n return\n }\n\n event.preventDefault()\n\n // TODO: v6 revert #37011 & change markup https://getbootstrap.com/docs/5.3/forms/input-group/\n const getToggleButton = this.matches(SELECTOR_DATA_TOGGLE) ?\n this :\n (SelectorEngine.prev(this, SELECTOR_DATA_TOGGLE)[0] ||\n SelectorEngine.next(this, SELECTOR_DATA_TOGGLE)[0] ||\n SelectorEngine.findOne(SELECTOR_DATA_TOGGLE, event.delegateTarget.parentNode))\n\n const instance = Dropdown.getOrCreateInstance(getToggleButton)\n\n if (isUpOrDownEvent) {\n event.stopPropagation()\n instance.show()\n instance._selectMenuItem(event)\n return\n }\n\n if (instance._isShown()) { // else is escape and we check if it is shown\n event.stopPropagation()\n instance.hide()\n getToggleButton.focus()\n }\n }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_KEYDOWN_DATA_API, SELECTOR_DATA_TOGGLE, Dropdown.dataApiKeydownHandler)\nEventHandler.on(document, EVENT_KEYDOWN_DATA_API, SELECTOR_MENU, Dropdown.dataApiKeydownHandler)\nEventHandler.on(document, EVENT_CLICK_DATA_API, Dropdown.clearMenus)\nEventHandler.on(document, EVENT_KEYUP_DATA_API, Dropdown.clearMenus)\nEventHandler.on(document, EVENT_CLICK_DATA_API, SELECTOR_DATA_TOGGLE, function (event) {\n event.preventDefault()\n Dropdown.getOrCreateInstance(this).toggle()\n})\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Dropdown)\n\nexport default Dropdown\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap util/backdrop.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport EventHandler from '../dom/event-handler.js'\nimport Config from './config.js'\nimport { execute, executeAfterTransition, getElement, reflow } from './index.js'\n\n/**\n * Constants\n */\n\nconst NAME = 'backdrop'\nconst CLASS_NAME_FADE = 'fade'\nconst CLASS_NAME_SHOW = 'show'\nconst EVENT_MOUSEDOWN = `mousedown.bs.${NAME}`\n\nconst Default = {\n className: 'modal-backdrop',\n clickCallback: null,\n isAnimated: false,\n isVisible: true, // if false, we use the backdrop helper without adding any element to the dom\n rootElement: 'body' // give the choice to place backdrop under different elements\n}\n\nconst DefaultType = {\n className: 'string',\n clickCallback: '(function|null)',\n isAnimated: 'boolean',\n isVisible: 'boolean',\n rootElement: '(element|string)'\n}\n\n/**\n * Class definition\n */\n\nclass Backdrop extends Config {\n constructor(config) {\n super()\n this._config = this._getConfig(config)\n this._isAppended = false\n this._element = null\n }\n\n // Getters\n static get Default() {\n return Default\n }\n\n static get DefaultType() {\n return DefaultType\n }\n\n static get NAME() {\n return NAME\n }\n\n // Public\n show(callback) {\n if (!this._config.isVisible) {\n execute(callback)\n return\n }\n\n this._append()\n\n const element = this._getElement()\n if (this._config.isAnimated) {\n reflow(element)\n }\n\n element.classList.add(CLASS_NAME_SHOW)\n\n this._emulateAnimation(() => {\n execute(callback)\n })\n }\n\n hide(callback) {\n if (!this._config.isVisible) {\n execute(callback)\n return\n }\n\n this._getElement().classList.remove(CLASS_NAME_SHOW)\n\n this._emulateAnimation(() => {\n this.dispose()\n execute(callback)\n })\n }\n\n dispose() {\n if (!this._isAppended) {\n return\n }\n\n EventHandler.off(this._element, EVENT_MOUSEDOWN)\n\n this._element.remove()\n this._isAppended = false\n }\n\n // Private\n _getElement() {\n if (!this._element) {\n const backdrop = document.createElement('div')\n backdrop.className = this._config.className\n if (this._config.isAnimated) {\n backdrop.classList.add(CLASS_NAME_FADE)\n }\n\n this._element = backdrop\n }\n\n return this._element\n }\n\n _configAfterMerge(config) {\n // use getElement() with the default \"body\" to get a fresh Element on each instantiation\n config.rootElement = getElement(config.rootElement)\n return config\n }\n\n _append() {\n if (this._isAppended) {\n return\n }\n\n const element = this._getElement()\n this._config.rootElement.append(element)\n\n EventHandler.on(element, EVENT_MOUSEDOWN, () => {\n execute(this._config.clickCallback)\n })\n\n this._isAppended = true\n }\n\n _emulateAnimation(callback) {\n executeAfterTransition(callback, this._getElement(), this._config.isAnimated)\n }\n}\n\nexport default Backdrop\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap util/focustrap.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport EventHandler from '../dom/event-handler.js'\nimport SelectorEngine from '../dom/selector-engine.js'\nimport Config from './config.js'\n\n/**\n * Constants\n */\n\nconst NAME = 'focustrap'\nconst DATA_KEY = 'bs.focustrap'\nconst EVENT_KEY = `.${DATA_KEY}`\nconst EVENT_FOCUSIN = `focusin${EVENT_KEY}`\nconst EVENT_KEYDOWN_TAB = `keydown.tab${EVENT_KEY}`\n\nconst TAB_KEY = 'Tab'\nconst TAB_NAV_FORWARD = 'forward'\nconst TAB_NAV_BACKWARD = 'backward'\n\nconst Default = {\n autofocus: true,\n trapElement: null // The element to trap focus inside of\n}\n\nconst DefaultType = {\n autofocus: 'boolean',\n trapElement: 'element'\n}\n\n/**\n * Class definition\n */\n\nclass FocusTrap extends Config {\n constructor(config) {\n super()\n this._config = this._getConfig(config)\n this._isActive = false\n this._lastTabNavDirection = null\n }\n\n // Getters\n static get Default() {\n return Default\n }\n\n static get DefaultType() {\n return DefaultType\n }\n\n static get NAME() {\n return NAME\n }\n\n // Public\n activate() {\n if (this._isActive) {\n return\n }\n\n if (this._config.autofocus) {\n this._config.trapElement.focus()\n }\n\n EventHandler.off(document, EVENT_KEY) // guard against infinite focus loop\n EventHandler.on(document, EVENT_FOCUSIN, event => this._handleFocusin(event))\n EventHandler.on(document, EVENT_KEYDOWN_TAB, event => this._handleKeydown(event))\n\n this._isActive = true\n }\n\n deactivate() {\n if (!this._isActive) {\n return\n }\n\n this._isActive = false\n EventHandler.off(document, EVENT_KEY)\n }\n\n // Private\n _handleFocusin(event) {\n const { trapElement } = this._config\n\n if (event.target === document || event.target === trapElement || trapElement.contains(event.target)) {\n return\n }\n\n const elements = SelectorEngine.focusableChildren(trapElement)\n\n if (elements.length === 0) {\n trapElement.focus()\n } else if (this._lastTabNavDirection === TAB_NAV_BACKWARD) {\n elements[elements.length - 1].focus()\n } else {\n elements[0].focus()\n }\n }\n\n _handleKeydown(event) {\n if (event.key !== TAB_KEY) {\n return\n }\n\n this._lastTabNavDirection = event.shiftKey ? TAB_NAV_BACKWARD : TAB_NAV_FORWARD\n }\n}\n\nexport default FocusTrap\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap util/scrollBar.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport Manipulator from '../dom/manipulator.js'\nimport SelectorEngine from '../dom/selector-engine.js'\nimport { isElement } from './index.js'\n\n/**\n * Constants\n */\n\nconst SELECTOR_FIXED_CONTENT = '.fixed-top, .fixed-bottom, .is-fixed, .sticky-top'\nconst SELECTOR_STICKY_CONTENT = '.sticky-top'\nconst PROPERTY_PADDING = 'padding-right'\nconst PROPERTY_MARGIN = 'margin-right'\n\n/**\n * Class definition\n */\n\nclass ScrollBarHelper {\n constructor() {\n this._element = document.body\n }\n\n // Public\n getWidth() {\n // https://developer.mozilla.org/en-US/docs/Web/API/Window/innerWidth#usage_notes\n const documentWidth = document.documentElement.clientWidth\n return Math.abs(window.innerWidth - documentWidth)\n }\n\n hide() {\n const width = this.getWidth()\n this._disableOverFlow()\n // give padding to element to balance the hidden scrollbar width\n this._setElementAttributes(this._element, PROPERTY_PADDING, calculatedValue => calculatedValue + width)\n // trick: We adjust positive paddingRight and negative marginRight to sticky-top elements to keep showing fullwidth\n this._setElementAttributes(SELECTOR_FIXED_CONTENT, PROPERTY_PADDING, calculatedValue => calculatedValue + width)\n this._setElementAttributes(SELECTOR_STICKY_CONTENT, PROPERTY_MARGIN, calculatedValue => calculatedValue - width)\n }\n\n reset() {\n this._resetElementAttributes(this._element, 'overflow')\n this._resetElementAttributes(this._element, PROPERTY_PADDING)\n this._resetElementAttributes(SELECTOR_FIXED_CONTENT, PROPERTY_PADDING)\n this._resetElementAttributes(SELECTOR_STICKY_CONTENT, PROPERTY_MARGIN)\n }\n\n isOverflowing() {\n return this.getWidth() > 0\n }\n\n // Private\n _disableOverFlow() {\n this._saveInitialAttribute(this._element, 'overflow')\n this._element.style.overflow = 'hidden'\n }\n\n _setElementAttributes(selector, styleProperty, callback) {\n const scrollbarWidth = this.getWidth()\n const manipulationCallBack = element => {\n if (element !== this._element && window.innerWidth > element.clientWidth + scrollbarWidth) {\n return\n }\n\n this._saveInitialAttribute(element, styleProperty)\n const calculatedValue = window.getComputedStyle(element).getPropertyValue(styleProperty)\n element.style.setProperty(styleProperty, `${callback(Number.parseFloat(calculatedValue))}px`)\n }\n\n this._applyManipulationCallback(selector, manipulationCallBack)\n }\n\n _saveInitialAttribute(element, styleProperty) {\n const actualValue = element.style.getPropertyValue(styleProperty)\n if (actualValue) {\n Manipulator.setDataAttribute(element, styleProperty, actualValue)\n }\n }\n\n _resetElementAttributes(selector, styleProperty) {\n const manipulationCallBack = element => {\n const value = Manipulator.getDataAttribute(element, styleProperty)\n // We only want to remove the property if the value is `null`; the value can also be zero\n if (value === null) {\n element.style.removeProperty(styleProperty)\n return\n }\n\n Manipulator.removeDataAttribute(element, styleProperty)\n element.style.setProperty(styleProperty, value)\n }\n\n this._applyManipulationCallback(selector, manipulationCallBack)\n }\n\n _applyManipulationCallback(selector, callBack) {\n if (isElement(selector)) {\n callBack(selector)\n return\n }\n\n for (const sel of SelectorEngine.find(selector, this._element)) {\n callBack(sel)\n }\n }\n}\n\nexport default ScrollBarHelper\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap modal.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport BaseComponent from './base-component.js'\nimport EventHandler from './dom/event-handler.js'\nimport SelectorEngine from './dom/selector-engine.js'\nimport Backdrop from './util/backdrop.js'\nimport { enableDismissTrigger } from './util/component-functions.js'\nimport FocusTrap from './util/focustrap.js'\nimport { defineJQueryPlugin, isRTL, isVisible, reflow } from './util/index.js'\nimport ScrollBarHelper from './util/scrollbar.js'\n\n/**\n * Constants\n */\n\nconst NAME = 'modal'\nconst DATA_KEY = 'bs.modal'\nconst EVENT_KEY = `.${DATA_KEY}`\nconst DATA_API_KEY = '.data-api'\nconst ESCAPE_KEY = 'Escape'\n\nconst EVENT_HIDE = `hide${EVENT_KEY}`\nconst EVENT_HIDE_PREVENTED = `hidePrevented${EVENT_KEY}`\nconst EVENT_HIDDEN = `hidden${EVENT_KEY}`\nconst EVENT_SHOW = `show${EVENT_KEY}`\nconst EVENT_SHOWN = `shown${EVENT_KEY}`\nconst EVENT_RESIZE = `resize${EVENT_KEY}`\nconst EVENT_CLICK_DISMISS = `click.dismiss${EVENT_KEY}`\nconst EVENT_MOUSEDOWN_DISMISS = `mousedown.dismiss${EVENT_KEY}`\nconst EVENT_KEYDOWN_DISMISS = `keydown.dismiss${EVENT_KEY}`\nconst EVENT_CLICK_DATA_API = `click${EVENT_KEY}${DATA_API_KEY}`\n\nconst CLASS_NAME_OPEN = 'modal-open'\nconst CLASS_NAME_FADE = 'fade'\nconst CLASS_NAME_SHOW = 'show'\nconst CLASS_NAME_STATIC = 'modal-static'\n\nconst OPEN_SELECTOR = '.modal.show'\nconst SELECTOR_DIALOG = '.modal-dialog'\nconst SELECTOR_MODAL_BODY = '.modal-body'\nconst SELECTOR_DATA_TOGGLE = '[data-bs-toggle=\"modal\"]'\n\nconst Default = {\n backdrop: true,\n focus: true,\n keyboard: true\n}\n\nconst DefaultType = {\n backdrop: '(boolean|string)',\n focus: 'boolean',\n keyboard: 'boolean'\n}\n\n/**\n * Class definition\n */\n\nclass Modal extends BaseComponent {\n constructor(element, config) {\n super(element, config)\n\n this._dialog = SelectorEngine.findOne(SELECTOR_DIALOG, this._element)\n this._backdrop = this._initializeBackDrop()\n this._focustrap = this._initializeFocusTrap()\n this._isShown = false\n this._isTransitioning = false\n this._scrollBar = new ScrollBarHelper()\n\n this._addEventListeners()\n }\n\n // Getters\n static get Default() {\n return Default\n }\n\n static get DefaultType() {\n return DefaultType\n }\n\n static get NAME() {\n return NAME\n }\n\n // Public\n toggle(relatedTarget) {\n return this._isShown ? this.hide() : this.show(relatedTarget)\n }\n\n show(relatedTarget) {\n if (this._isShown || this._isTransitioning) {\n return\n }\n\n const showEvent = EventHandler.trigger(this._element, EVENT_SHOW, {\n relatedTarget\n })\n\n if (showEvent.defaultPrevented) {\n return\n }\n\n this._isShown = true\n this._isTransitioning = true\n\n this._scrollBar.hide()\n\n document.body.classList.add(CLASS_NAME_OPEN)\n\n this._adjustDialog()\n\n this._backdrop.show(() => this._showElement(relatedTarget))\n }\n\n hide() {\n if (!this._isShown || this._isTransitioning) {\n return\n }\n\n const hideEvent = EventHandler.trigger(this._element, EVENT_HIDE)\n\n if (hideEvent.defaultPrevented) {\n return\n }\n\n this._isShown = false\n this._isTransitioning = true\n this._focustrap.deactivate()\n\n this._element.classList.remove(CLASS_NAME_SHOW)\n\n this._queueCallback(() => this._hideModal(), this._element, this._isAnimated())\n }\n\n dispose() {\n EventHandler.off(window, EVENT_KEY)\n EventHandler.off(this._dialog, EVENT_KEY)\n\n this._backdrop.dispose()\n this._focustrap.deactivate()\n\n super.dispose()\n }\n\n handleUpdate() {\n this._adjustDialog()\n }\n\n // Private\n _initializeBackDrop() {\n return new Backdrop({\n isVisible: Boolean(this._config.backdrop), // 'static' option will be translated to true, and booleans will keep their value,\n isAnimated: this._isAnimated()\n })\n }\n\n _initializeFocusTrap() {\n return new FocusTrap({\n trapElement: this._element\n })\n }\n\n _showElement(relatedTarget) {\n // try to append dynamic modal\n if (!document.body.contains(this._element)) {\n document.body.append(this._element)\n }\n\n this._element.style.display = 'block'\n this._element.removeAttribute('aria-hidden')\n this._element.setAttribute('aria-modal', true)\n this._element.setAttribute('role', 'dialog')\n this._element.scrollTop = 0\n\n const modalBody = SelectorEngine.findOne(SELECTOR_MODAL_BODY, this._dialog)\n if (modalBody) {\n modalBody.scrollTop = 0\n }\n\n reflow(this._element)\n\n this._element.classList.add(CLASS_NAME_SHOW)\n\n const transitionComplete = () => {\n if (this._config.focus) {\n this._focustrap.activate()\n }\n\n this._isTransitioning = false\n EventHandler.trigger(this._element, EVENT_SHOWN, {\n relatedTarget\n })\n }\n\n this._queueCallback(transitionComplete, this._dialog, this._isAnimated())\n }\n\n _addEventListeners() {\n EventHandler.on(this._element, EVENT_KEYDOWN_DISMISS, event => {\n if (event.key !== ESCAPE_KEY) {\n return\n }\n\n if (this._config.keyboard) {\n this.hide()\n return\n }\n\n this._triggerBackdropTransition()\n })\n\n EventHandler.on(window, EVENT_RESIZE, () => {\n if (this._isShown && !this._isTransitioning) {\n this._adjustDialog()\n }\n })\n\n EventHandler.on(this._element, EVENT_MOUSEDOWN_DISMISS, event => {\n // a bad trick to segregate clicks that may start inside dialog but end outside, and avoid listen to scrollbar clicks\n EventHandler.one(this._element, EVENT_CLICK_DISMISS, event2 => {\n if (this._element !== event.target || this._element !== event2.target) {\n return\n }\n\n if (this._config.backdrop === 'static') {\n this._triggerBackdropTransition()\n return\n }\n\n if (this._config.backdrop) {\n this.hide()\n }\n })\n })\n }\n\n _hideModal() {\n this._element.style.display = 'none'\n this._element.setAttribute('aria-hidden', true)\n this._element.removeAttribute('aria-modal')\n this._element.removeAttribute('role')\n this._isTransitioning = false\n\n this._backdrop.hide(() => {\n document.body.classList.remove(CLASS_NAME_OPEN)\n this._resetAdjustments()\n this._scrollBar.reset()\n EventHandler.trigger(this._element, EVENT_HIDDEN)\n })\n }\n\n _isAnimated() {\n return this._element.classList.contains(CLASS_NAME_FADE)\n }\n\n _triggerBackdropTransition() {\n const hideEvent = EventHandler.trigger(this._element, EVENT_HIDE_PREVENTED)\n if (hideEvent.defaultPrevented) {\n return\n }\n\n const isModalOverflowing = this._element.scrollHeight > document.documentElement.clientHeight\n const initialOverflowY = this._element.style.overflowY\n // return if the following background transition hasn't yet completed\n if (initialOverflowY === 'hidden' || this._element.classList.contains(CLASS_NAME_STATIC)) {\n return\n }\n\n if (!isModalOverflowing) {\n this._element.style.overflowY = 'hidden'\n }\n\n this._element.classList.add(CLASS_NAME_STATIC)\n this._queueCallback(() => {\n this._element.classList.remove(CLASS_NAME_STATIC)\n this._queueCallback(() => {\n this._element.style.overflowY = initialOverflowY\n }, this._dialog)\n }, this._dialog)\n\n this._element.focus()\n }\n\n /**\n * The following methods are used to handle overflowing modals\n */\n\n _adjustDialog() {\n const isModalOverflowing = this._element.scrollHeight > document.documentElement.clientHeight\n const scrollbarWidth = this._scrollBar.getWidth()\n const isBodyOverflowing = scrollbarWidth > 0\n\n if (isBodyOverflowing && !isModalOverflowing) {\n const property = isRTL() ? 'paddingLeft' : 'paddingRight'\n this._element.style[property] = `${scrollbarWidth}px`\n }\n\n if (!isBodyOverflowing && isModalOverflowing) {\n const property = isRTL() ? 'paddingRight' : 'paddingLeft'\n this._element.style[property] = `${scrollbarWidth}px`\n }\n }\n\n _resetAdjustments() {\n this._element.style.paddingLeft = ''\n this._element.style.paddingRight = ''\n }\n\n // Static\n static jQueryInterface(config, relatedTarget) {\n return this.each(function () {\n const data = Modal.getOrCreateInstance(this, config)\n\n if (typeof config !== 'string') {\n return\n }\n\n if (typeof data[config] === 'undefined') {\n throw new TypeError(`No method named \"${config}\"`)\n }\n\n data[config](relatedTarget)\n })\n }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_CLICK_DATA_API, SELECTOR_DATA_TOGGLE, function (event) {\n const target = SelectorEngine.getElementFromSelector(this)\n\n if (['A', 'AREA'].includes(this.tagName)) {\n event.preventDefault()\n }\n\n EventHandler.one(target, EVENT_SHOW, showEvent => {\n if (showEvent.defaultPrevented) {\n // only register focus restorer if modal will actually get shown\n return\n }\n\n EventHandler.one(target, EVENT_HIDDEN, () => {\n if (isVisible(this)) {\n this.focus()\n }\n })\n })\n\n // avoid conflict when clicking modal toggler while another one is open\n const alreadyOpen = SelectorEngine.findOne(OPEN_SELECTOR)\n if (alreadyOpen) {\n Modal.getInstance(alreadyOpen).hide()\n }\n\n const data = Modal.getOrCreateInstance(target)\n\n data.toggle(this)\n})\n\nenableDismissTrigger(Modal)\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Modal)\n\nexport default Modal\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap offcanvas.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport BaseComponent from './base-component.js'\nimport EventHandler from './dom/event-handler.js'\nimport SelectorEngine from './dom/selector-engine.js'\nimport Backdrop from './util/backdrop.js'\nimport { enableDismissTrigger } from './util/component-functions.js'\nimport FocusTrap from './util/focustrap.js'\nimport {\n defineJQueryPlugin,\n isDisabled,\n isVisible\n} from './util/index.js'\nimport ScrollBarHelper from './util/scrollbar.js'\n\n/**\n * Constants\n */\n\nconst NAME = 'offcanvas'\nconst DATA_KEY = 'bs.offcanvas'\nconst EVENT_KEY = `.${DATA_KEY}`\nconst DATA_API_KEY = '.data-api'\nconst EVENT_LOAD_DATA_API = `load${EVENT_KEY}${DATA_API_KEY}`\nconst ESCAPE_KEY = 'Escape'\n\nconst CLASS_NAME_SHOW = 'show'\nconst CLASS_NAME_SHOWING = 'showing'\nconst CLASS_NAME_HIDING = 'hiding'\nconst CLASS_NAME_BACKDROP = 'offcanvas-backdrop'\nconst OPEN_SELECTOR = '.offcanvas.show'\n\nconst EVENT_SHOW = `show${EVENT_KEY}`\nconst EVENT_SHOWN = `shown${EVENT_KEY}`\nconst EVENT_HIDE = `hide${EVENT_KEY}`\nconst EVENT_HIDE_PREVENTED = `hidePrevented${EVENT_KEY}`\nconst EVENT_HIDDEN = `hidden${EVENT_KEY}`\nconst EVENT_RESIZE = `resize${EVENT_KEY}`\nconst EVENT_CLICK_DATA_API = `click${EVENT_KEY}${DATA_API_KEY}`\nconst EVENT_KEYDOWN_DISMISS = `keydown.dismiss${EVENT_KEY}`\n\nconst SELECTOR_DATA_TOGGLE = '[data-bs-toggle=\"offcanvas\"]'\n\nconst Default = {\n backdrop: true,\n keyboard: true,\n scroll: false\n}\n\nconst DefaultType = {\n backdrop: '(boolean|string)',\n keyboard: 'boolean',\n scroll: 'boolean'\n}\n\n/**\n * Class definition\n */\n\nclass Offcanvas extends BaseComponent {\n constructor(element, config) {\n super(element, config)\n\n this._isShown = false\n this._backdrop = this._initializeBackDrop()\n this._focustrap = this._initializeFocusTrap()\n this._addEventListeners()\n }\n\n // Getters\n static get Default() {\n return Default\n }\n\n static get DefaultType() {\n return DefaultType\n }\n\n static get NAME() {\n return NAME\n }\n\n // Public\n toggle(relatedTarget) {\n return this._isShown ? this.hide() : this.show(relatedTarget)\n }\n\n show(relatedTarget) {\n if (this._isShown) {\n return\n }\n\n const showEvent = EventHandler.trigger(this._element, EVENT_SHOW, { relatedTarget })\n\n if (showEvent.defaultPrevented) {\n return\n }\n\n this._isShown = true\n this._backdrop.show()\n\n if (!this._config.scroll) {\n new ScrollBarHelper().hide()\n }\n\n this._element.setAttribute('aria-modal', true)\n this._element.setAttribute('role', 'dialog')\n this._element.classList.add(CLASS_NAME_SHOWING)\n\n const completeCallBack = () => {\n if (!this._config.scroll || this._config.backdrop) {\n this._focustrap.activate()\n }\n\n this._element.classList.add(CLASS_NAME_SHOW)\n this._element.classList.remove(CLASS_NAME_SHOWING)\n EventHandler.trigger(this._element, EVENT_SHOWN, { relatedTarget })\n }\n\n this._queueCallback(completeCallBack, this._element, true)\n }\n\n hide() {\n if (!this._isShown) {\n return\n }\n\n const hideEvent = EventHandler.trigger(this._element, EVENT_HIDE)\n\n if (hideEvent.defaultPrevented) {\n return\n }\n\n this._focustrap.deactivate()\n this._element.blur()\n this._isShown = false\n this._element.classList.add(CLASS_NAME_HIDING)\n this._backdrop.hide()\n\n const completeCallback = () => {\n this._element.classList.remove(CLASS_NAME_SHOW, CLASS_NAME_HIDING)\n this._element.removeAttribute('aria-modal')\n this._element.removeAttribute('role')\n\n if (!this._config.scroll) {\n new ScrollBarHelper().reset()\n }\n\n EventHandler.trigger(this._element, EVENT_HIDDEN)\n }\n\n this._queueCallback(completeCallback, this._element, true)\n }\n\n dispose() {\n this._backdrop.dispose()\n this._focustrap.deactivate()\n super.dispose()\n }\n\n // Private\n _initializeBackDrop() {\n const clickCallback = () => {\n if (this._config.backdrop === 'static') {\n EventHandler.trigger(this._element, EVENT_HIDE_PREVENTED)\n return\n }\n\n this.hide()\n }\n\n // 'static' option will be translated to true, and booleans will keep their value\n const isVisible = Boolean(this._config.backdrop)\n\n return new Backdrop({\n className: CLASS_NAME_BACKDROP,\n isVisible,\n isAnimated: true,\n rootElement: this._element.parentNode,\n clickCallback: isVisible ? clickCallback : null\n })\n }\n\n _initializeFocusTrap() {\n return new FocusTrap({\n trapElement: this._element\n })\n }\n\n _addEventListeners() {\n EventHandler.on(this._element, EVENT_KEYDOWN_DISMISS, event => {\n if (event.key !== ESCAPE_KEY) {\n return\n }\n\n if (this._config.keyboard) {\n this.hide()\n return\n }\n\n EventHandler.trigger(this._element, EVENT_HIDE_PREVENTED)\n })\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Offcanvas.getOrCreateInstance(this, config)\n\n if (typeof config !== 'string') {\n return\n }\n\n if (data[config] === undefined || config.startsWith('_') || config === 'constructor') {\n throw new TypeError(`No method named \"${config}\"`)\n }\n\n data[config](this)\n })\n }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_CLICK_DATA_API, SELECTOR_DATA_TOGGLE, function (event) {\n const target = SelectorEngine.getElementFromSelector(this)\n\n if (['A', 'AREA'].includes(this.tagName)) {\n event.preventDefault()\n }\n\n if (isDisabled(this)) {\n return\n }\n\n EventHandler.one(target, EVENT_HIDDEN, () => {\n // focus on trigger when it is closed\n if (isVisible(this)) {\n this.focus()\n }\n })\n\n // avoid conflict when clicking a toggler of an offcanvas, while another is open\n const alreadyOpen = SelectorEngine.findOne(OPEN_SELECTOR)\n if (alreadyOpen && alreadyOpen !== target) {\n Offcanvas.getInstance(alreadyOpen).hide()\n }\n\n const data = Offcanvas.getOrCreateInstance(target)\n data.toggle(this)\n})\n\nEventHandler.on(window, EVENT_LOAD_DATA_API, () => {\n for (const selector of SelectorEngine.find(OPEN_SELECTOR)) {\n Offcanvas.getOrCreateInstance(selector).show()\n }\n})\n\nEventHandler.on(window, EVENT_RESIZE, () => {\n for (const element of SelectorEngine.find('[aria-modal][class*=show][class*=offcanvas-]')) {\n if (getComputedStyle(element).position !== 'fixed') {\n Offcanvas.getOrCreateInstance(element).hide()\n }\n }\n})\n\nenableDismissTrigger(Offcanvas)\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Offcanvas)\n\nexport default Offcanvas\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap util/sanitizer.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n// js-docs-start allow-list\nconst ARIA_ATTRIBUTE_PATTERN = /^aria-[\\w-]*$/i\n\nexport const DefaultAllowlist = {\n // Global attributes allowed on any supplied element below.\n '*': ['class', 'dir', 'id', 'lang', 'role', ARIA_ATTRIBUTE_PATTERN],\n a: ['target', 'href', 'title', 'rel'],\n area: [],\n b: [],\n br: [],\n col: [],\n code: [],\n div: [],\n em: [],\n hr: [],\n h1: [],\n h2: [],\n h3: [],\n h4: [],\n h5: [],\n h6: [],\n i: [],\n img: ['src', 'srcset', 'alt', 'title', 'width', 'height'],\n li: [],\n ol: [],\n p: [],\n pre: [],\n s: [],\n small: [],\n span: [],\n sub: [],\n sup: [],\n strong: [],\n u: [],\n ul: []\n}\n// js-docs-end allow-list\n\nconst uriAttributes = new Set([\n 'background',\n 'cite',\n 'href',\n 'itemtype',\n 'longdesc',\n 'poster',\n 'src',\n 'xlink:href'\n])\n\n/**\n * A pattern that recognizes URLs that are safe wrt. XSS in URL navigation\n * contexts.\n *\n * Shout-out to Angular https://github.com/angular/angular/blob/15.2.8/packages/core/src/sanitization/url_sanitizer.ts#L38\n */\n// eslint-disable-next-line unicorn/better-regex\nconst SAFE_URL_PATTERN = /^(?!javascript:)(?:[a-z0-9+.-]+:|[^&:/?#]*(?:[/?#]|$))/i\n\nconst allowedAttribute = (attribute, allowedAttributeList) => {\n const attributeName = attribute.nodeName.toLowerCase()\n\n if (allowedAttributeList.includes(attributeName)) {\n if (uriAttributes.has(attributeName)) {\n return Boolean(SAFE_URL_PATTERN.test(attribute.nodeValue))\n }\n\n return true\n }\n\n // Check if a regular expression validates the attribute.\n return allowedAttributeList.filter(attributeRegex => attributeRegex instanceof RegExp)\n .some(regex => regex.test(attributeName))\n}\n\nexport function sanitizeHtml(unsafeHtml, allowList, sanitizeFunction) {\n if (!unsafeHtml.length) {\n return unsafeHtml\n }\n\n if (sanitizeFunction && typeof sanitizeFunction === 'function') {\n return sanitizeFunction(unsafeHtml)\n }\n\n const domParser = new window.DOMParser()\n const createdDocument = domParser.parseFromString(unsafeHtml, 'text/html')\n const elements = [].concat(...createdDocument.body.querySelectorAll('*'))\n\n for (const element of elements) {\n const elementName = element.nodeName.toLowerCase()\n\n if (!Object.keys(allowList).includes(elementName)) {\n element.remove()\n continue\n }\n\n const attributeList = [].concat(...element.attributes)\n const allowedAttributes = [].concat(allowList['*'] || [], allowList[elementName] || [])\n\n for (const attribute of attributeList) {\n if (!allowedAttribute(attribute, allowedAttributes)) {\n element.removeAttribute(attribute.nodeName)\n }\n }\n }\n\n return createdDocument.body.innerHTML\n}\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap util/template-factory.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport SelectorEngine from '../dom/selector-engine.js'\nimport Config from './config.js'\nimport { DefaultAllowlist, sanitizeHtml } from './sanitizer.js'\nimport { execute, getElement, isElement } from './index.js'\n\n/**\n * Constants\n */\n\nconst NAME = 'TemplateFactory'\n\nconst Default = {\n allowList: DefaultAllowlist,\n content: {}, // { selector : text , selector2 : text2 , }\n extraClass: '',\n html: false,\n sanitize: true,\n sanitizeFn: null,\n template: '
'\n}\n\nconst DefaultType = {\n allowList: 'object',\n content: 'object',\n extraClass: '(string|function)',\n html: 'boolean',\n sanitize: 'boolean',\n sanitizeFn: '(null|function)',\n template: 'string'\n}\n\nconst DefaultContentType = {\n entry: '(string|element|function|null)',\n selector: '(string|element)'\n}\n\n/**\n * Class definition\n */\n\nclass TemplateFactory extends Config {\n constructor(config) {\n super()\n this._config = this._getConfig(config)\n }\n\n // Getters\n static get Default() {\n return Default\n }\n\n static get DefaultType() {\n return DefaultType\n }\n\n static get NAME() {\n return NAME\n }\n\n // Public\n getContent() {\n return Object.values(this._config.content)\n .map(config => this._resolvePossibleFunction(config))\n .filter(Boolean)\n }\n\n hasContent() {\n return this.getContent().length > 0\n }\n\n changeContent(content) {\n this._checkContent(content)\n this._config.content = { ...this._config.content, ...content }\n return this\n }\n\n toHtml() {\n const templateWrapper = document.createElement('div')\n templateWrapper.innerHTML = this._maybeSanitize(this._config.template)\n\n for (const [selector, text] of Object.entries(this._config.content)) {\n this._setContent(templateWrapper, text, selector)\n }\n\n const template = templateWrapper.children[0]\n const extraClass = this._resolvePossibleFunction(this._config.extraClass)\n\n if (extraClass) {\n template.classList.add(...extraClass.split(' '))\n }\n\n return template\n }\n\n // Private\n _typeCheckConfig(config) {\n super._typeCheckConfig(config)\n this._checkContent(config.content)\n }\n\n _checkContent(arg) {\n for (const [selector, content] of Object.entries(arg)) {\n super._typeCheckConfig({ selector, entry: content }, DefaultContentType)\n }\n }\n\n _setContent(template, content, selector) {\n const templateElement = SelectorEngine.findOne(selector, template)\n\n if (!templateElement) {\n return\n }\n\n content = this._resolvePossibleFunction(content)\n\n if (!content) {\n templateElement.remove()\n return\n }\n\n if (isElement(content)) {\n this._putElementInTemplate(getElement(content), templateElement)\n return\n }\n\n if (this._config.html) {\n templateElement.innerHTML = this._maybeSanitize(content)\n return\n }\n\n templateElement.textContent = content\n }\n\n _maybeSanitize(arg) {\n return this._config.sanitize ? sanitizeHtml(arg, this._config.allowList, this._config.sanitizeFn) : arg\n }\n\n _resolvePossibleFunction(arg) {\n return execute(arg, [this])\n }\n\n _putElementInTemplate(element, templateElement) {\n if (this._config.html) {\n templateElement.innerHTML = ''\n templateElement.append(element)\n return\n }\n\n templateElement.textContent = element.textContent\n }\n}\n\nexport default TemplateFactory\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap tooltip.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport * as Popper from '@popperjs/core'\nimport BaseComponent from './base-component.js'\nimport EventHandler from './dom/event-handler.js'\nimport Manipulator from './dom/manipulator.js'\nimport { defineJQueryPlugin, execute, findShadowRoot, getElement, getUID, isRTL, noop } from './util/index.js'\nimport { DefaultAllowlist } from './util/sanitizer.js'\nimport TemplateFactory from './util/template-factory.js'\n\n/**\n * Constants\n */\n\nconst NAME = 'tooltip'\nconst DISALLOWED_ATTRIBUTES = new Set(['sanitize', 'allowList', 'sanitizeFn'])\n\nconst CLASS_NAME_FADE = 'fade'\nconst CLASS_NAME_MODAL = 'modal'\nconst CLASS_NAME_SHOW = 'show'\n\nconst SELECTOR_TOOLTIP_INNER = '.tooltip-inner'\nconst SELECTOR_MODAL = `.${CLASS_NAME_MODAL}`\n\nconst EVENT_MODAL_HIDE = 'hide.bs.modal'\n\nconst TRIGGER_HOVER = 'hover'\nconst TRIGGER_FOCUS = 'focus'\nconst TRIGGER_CLICK = 'click'\nconst TRIGGER_MANUAL = 'manual'\n\nconst EVENT_HIDE = 'hide'\nconst EVENT_HIDDEN = 'hidden'\nconst EVENT_SHOW = 'show'\nconst EVENT_SHOWN = 'shown'\nconst EVENT_INSERTED = 'inserted'\nconst EVENT_CLICK = 'click'\nconst EVENT_FOCUSIN = 'focusin'\nconst EVENT_FOCUSOUT = 'focusout'\nconst EVENT_MOUSEENTER = 'mouseenter'\nconst EVENT_MOUSELEAVE = 'mouseleave'\n\nconst AttachmentMap = {\n AUTO: 'auto',\n TOP: 'top',\n RIGHT: isRTL() ? 'left' : 'right',\n BOTTOM: 'bottom',\n LEFT: isRTL() ? 'right' : 'left'\n}\n\nconst Default = {\n allowList: DefaultAllowlist,\n animation: true,\n boundary: 'clippingParents',\n container: false,\n customClass: '',\n delay: 0,\n fallbackPlacements: ['top', 'right', 'bottom', 'left'],\n html: false,\n offset: [0, 6],\n placement: 'top',\n popperConfig: null,\n sanitize: true,\n sanitizeFn: null,\n selector: false,\n template: '
' +\n '
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',\n title: '',\n trigger: 'hover focus'\n}\n\nconst DefaultType = {\n allowList: 'object',\n animation: 'boolean',\n boundary: '(string|element)',\n container: '(string|element|boolean)',\n customClass: '(string|function)',\n delay: '(number|object)',\n fallbackPlacements: 'array',\n html: 'boolean',\n offset: '(array|string|function)',\n placement: '(string|function)',\n popperConfig: '(null|object|function)',\n sanitize: 'boolean',\n sanitizeFn: '(null|function)',\n selector: '(string|boolean)',\n template: 'string',\n title: '(string|element|function)',\n trigger: 'string'\n}\n\n/**\n * Class definition\n */\n\nclass Tooltip extends BaseComponent {\n constructor(element, config) {\n if (typeof Popper === 'undefined') {\n throw new TypeError('Bootstrap\\'s tooltips require Popper (https://popper.js.org)')\n }\n\n super(element, config)\n\n // Private\n this._isEnabled = true\n this._timeout = 0\n this._isHovered = null\n this._activeTrigger = {}\n this._popper = null\n this._templateFactory = null\n this._newContent = null\n\n // Protected\n this.tip = null\n\n this._setListeners()\n\n if (!this._config.selector) {\n this._fixTitle()\n }\n }\n\n // Getters\n static get Default() {\n return Default\n }\n\n static get DefaultType() {\n return DefaultType\n }\n\n static get NAME() {\n return NAME\n }\n\n // Public\n enable() {\n this._isEnabled = true\n }\n\n disable() {\n this._isEnabled = false\n }\n\n toggleEnabled() {\n this._isEnabled = !this._isEnabled\n }\n\n toggle() {\n if (!this._isEnabled) {\n return\n }\n\n this._activeTrigger.click = !this._activeTrigger.click\n if (this._isShown()) {\n this._leave()\n return\n }\n\n this._enter()\n }\n\n dispose() {\n clearTimeout(this._timeout)\n\n EventHandler.off(this._element.closest(SELECTOR_MODAL), EVENT_MODAL_HIDE, this._hideModalHandler)\n\n if (this._element.getAttribute('data-bs-original-title')) {\n this._element.setAttribute('title', this._element.getAttribute('data-bs-original-title'))\n }\n\n this._disposePopper()\n super.dispose()\n }\n\n show() {\n if (this._element.style.display === 'none') {\n throw new Error('Please use show on visible elements')\n }\n\n if (!(this._isWithContent() && this._isEnabled)) {\n return\n }\n\n const showEvent = EventHandler.trigger(this._element, this.constructor.eventName(EVENT_SHOW))\n const shadowRoot = findShadowRoot(this._element)\n const isInTheDom = (shadowRoot || this._element.ownerDocument.documentElement).contains(this._element)\n\n if (showEvent.defaultPrevented || !isInTheDom) {\n return\n }\n\n // TODO: v6 remove this or make it optional\n this._disposePopper()\n\n const tip = this._getTipElement()\n\n this._element.setAttribute('aria-describedby', tip.getAttribute('id'))\n\n const { container } = this._config\n\n if (!this._element.ownerDocument.documentElement.contains(this.tip)) {\n container.append(tip)\n EventHandler.trigger(this._element, this.constructor.eventName(EVENT_INSERTED))\n }\n\n this._popper = this._createPopper(tip)\n\n tip.classList.add(CLASS_NAME_SHOW)\n\n // If this is a touch-enabled device we add extra\n // empty mouseover listeners to the body's immediate children;\n // only needed because of broken event delegation on iOS\n // https://www.quirksmode.org/blog/archives/2014/02/mouse_event_bub.html\n if ('ontouchstart' in document.documentElement) {\n for (const element of [].concat(...document.body.children)) {\n EventHandler.on(element, 'mouseover', noop)\n }\n }\n\n const complete = () => {\n EventHandler.trigger(this._element, this.constructor.eventName(EVENT_SHOWN))\n\n if (this._isHovered === false) {\n this._leave()\n }\n\n this._isHovered = false\n }\n\n this._queueCallback(complete, this.tip, this._isAnimated())\n }\n\n hide() {\n if (!this._isShown()) {\n return\n }\n\n const hideEvent = EventHandler.trigger(this._element, this.constructor.eventName(EVENT_HIDE))\n if (hideEvent.defaultPrevented) {\n return\n }\n\n const tip = this._getTipElement()\n tip.classList.remove(CLASS_NAME_SHOW)\n\n // If this is a touch-enabled device we remove the extra\n // empty mouseover listeners we added for iOS support\n if ('ontouchstart' in document.documentElement) {\n for (const element of [].concat(...document.body.children)) {\n EventHandler.off(element, 'mouseover', noop)\n }\n }\n\n this._activeTrigger[TRIGGER_CLICK] = false\n this._activeTrigger[TRIGGER_FOCUS] = false\n this._activeTrigger[TRIGGER_HOVER] = false\n this._isHovered = null // it is a trick to support manual triggering\n\n const complete = () => {\n if (this._isWithActiveTrigger()) {\n return\n }\n\n if (!this._isHovered) {\n this._disposePopper()\n }\n\n this._element.removeAttribute('aria-describedby')\n EventHandler.trigger(this._element, this.constructor.eventName(EVENT_HIDDEN))\n }\n\n this._queueCallback(complete, this.tip, this._isAnimated())\n }\n\n update() {\n if (this._popper) {\n this._popper.update()\n }\n }\n\n // Protected\n _isWithContent() {\n return Boolean(this._getTitle())\n }\n\n _getTipElement() {\n if (!this.tip) {\n this.tip = this._createTipElement(this._newContent || this._getContentForTemplate())\n }\n\n return this.tip\n }\n\n _createTipElement(content) {\n const tip = this._getTemplateFactory(content).toHtml()\n\n // TODO: remove this check in v6\n if (!tip) {\n return null\n }\n\n tip.classList.remove(CLASS_NAME_FADE, CLASS_NAME_SHOW)\n // TODO: v6 the following can be achieved with CSS only\n tip.classList.add(`bs-${this.constructor.NAME}-auto`)\n\n const tipId = getUID(this.constructor.NAME).toString()\n\n tip.setAttribute('id', tipId)\n\n if (this._isAnimated()) {\n tip.classList.add(CLASS_NAME_FADE)\n }\n\n return tip\n }\n\n setContent(content) {\n this._newContent = content\n if (this._isShown()) {\n this._disposePopper()\n this.show()\n }\n }\n\n _getTemplateFactory(content) {\n if (this._templateFactory) {\n this._templateFactory.changeContent(content)\n } else {\n this._templateFactory = new TemplateFactory({\n ...this._config,\n // the `content` var has to be after `this._config`\n // to override config.content in case of popover\n content,\n extraClass: this._resolvePossibleFunction(this._config.customClass)\n })\n }\n\n return this._templateFactory\n }\n\n _getContentForTemplate() {\n return {\n [SELECTOR_TOOLTIP_INNER]: this._getTitle()\n }\n }\n\n _getTitle() {\n return this._resolvePossibleFunction(this._config.title) || this._element.getAttribute('data-bs-original-title')\n }\n\n // Private\n _initializeOnDelegatedTarget(event) {\n return this.constructor.getOrCreateInstance(event.delegateTarget, this._getDelegateConfig())\n }\n\n _isAnimated() {\n return this._config.animation || (this.tip && this.tip.classList.contains(CLASS_NAME_FADE))\n }\n\n _isShown() {\n return this.tip && this.tip.classList.contains(CLASS_NAME_SHOW)\n }\n\n _createPopper(tip) {\n const placement = execute(this._config.placement, [this, tip, this._element])\n const attachment = AttachmentMap[placement.toUpperCase()]\n return Popper.createPopper(this._element, tip, this._getPopperConfig(attachment))\n }\n\n _getOffset() {\n const { offset } = this._config\n\n if (typeof offset === 'string') {\n return offset.split(',').map(value => Number.parseInt(value, 10))\n }\n\n if (typeof offset === 'function') {\n return popperData => offset(popperData, this._element)\n }\n\n return offset\n }\n\n _resolvePossibleFunction(arg) {\n return execute(arg, [this._element])\n }\n\n _getPopperConfig(attachment) {\n const defaultBsPopperConfig = {\n placement: attachment,\n modifiers: [\n {\n name: 'flip',\n options: {\n fallbackPlacements: this._config.fallbackPlacements\n }\n },\n {\n name: 'offset',\n options: {\n offset: this._getOffset()\n }\n },\n {\n name: 'preventOverflow',\n options: {\n boundary: this._config.boundary\n }\n },\n {\n name: 'arrow',\n options: {\n element: `.${this.constructor.NAME}-arrow`\n }\n },\n {\n name: 'preSetPlacement',\n enabled: true,\n phase: 'beforeMain',\n fn: data => {\n // Pre-set Popper's placement attribute in order to read the arrow sizes properly.\n // Otherwise, Popper mixes up the width and height dimensions since the initial arrow style is for top placement\n this._getTipElement().setAttribute('data-popper-placement', data.state.placement)\n }\n }\n ]\n }\n\n return {\n ...defaultBsPopperConfig,\n ...execute(this._config.popperConfig, [defaultBsPopperConfig])\n }\n }\n\n _setListeners() {\n const triggers = this._config.trigger.split(' ')\n\n for (const trigger of triggers) {\n if (trigger === 'click') {\n EventHandler.on(this._element, this.constructor.eventName(EVENT_CLICK), this._config.selector, event => {\n const context = this._initializeOnDelegatedTarget(event)\n context.toggle()\n })\n } else if (trigger !== TRIGGER_MANUAL) {\n const eventIn = trigger === TRIGGER_HOVER ?\n this.constructor.eventName(EVENT_MOUSEENTER) :\n this.constructor.eventName(EVENT_FOCUSIN)\n const eventOut = trigger === TRIGGER_HOVER ?\n this.constructor.eventName(EVENT_MOUSELEAVE) :\n this.constructor.eventName(EVENT_FOCUSOUT)\n\n EventHandler.on(this._element, eventIn, this._config.selector, event => {\n const context = this._initializeOnDelegatedTarget(event)\n context._activeTrigger[event.type === 'focusin' ? TRIGGER_FOCUS : TRIGGER_HOVER] = true\n context._enter()\n })\n EventHandler.on(this._element, eventOut, this._config.selector, event => {\n const context = this._initializeOnDelegatedTarget(event)\n context._activeTrigger[event.type === 'focusout' ? TRIGGER_FOCUS : TRIGGER_HOVER] =\n context._element.contains(event.relatedTarget)\n\n context._leave()\n })\n }\n }\n\n this._hideModalHandler = () => {\n if (this._element) {\n this.hide()\n }\n }\n\n EventHandler.on(this._element.closest(SELECTOR_MODAL), EVENT_MODAL_HIDE, this._hideModalHandler)\n }\n\n _fixTitle() {\n const title = this._element.getAttribute('title')\n\n if (!title) {\n return\n }\n\n if (!this._element.getAttribute('aria-label') && !this._element.textContent.trim()) {\n this._element.setAttribute('aria-label', title)\n }\n\n this._element.setAttribute('data-bs-original-title', title) // DO NOT USE IT. Is only for backwards compatibility\n this._element.removeAttribute('title')\n }\n\n _enter() {\n if (this._isShown() || this._isHovered) {\n this._isHovered = true\n return\n }\n\n this._isHovered = true\n\n this._setTimeout(() => {\n if (this._isHovered) {\n this.show()\n }\n }, this._config.delay.show)\n }\n\n _leave() {\n if (this._isWithActiveTrigger()) {\n return\n }\n\n this._isHovered = false\n\n this._setTimeout(() => {\n if (!this._isHovered) {\n this.hide()\n }\n }, this._config.delay.hide)\n }\n\n _setTimeout(handler, timeout) {\n clearTimeout(this._timeout)\n this._timeout = setTimeout(handler, timeout)\n }\n\n _isWithActiveTrigger() {\n return Object.values(this._activeTrigger).includes(true)\n }\n\n _getConfig(config) {\n const dataAttributes = Manipulator.getDataAttributes(this._element)\n\n for (const dataAttribute of Object.keys(dataAttributes)) {\n if (DISALLOWED_ATTRIBUTES.has(dataAttribute)) {\n delete dataAttributes[dataAttribute]\n }\n }\n\n config = {\n ...dataAttributes,\n ...(typeof config === 'object' && config ? config : {})\n }\n config = this._mergeConfigObj(config)\n config = this._configAfterMerge(config)\n this._typeCheckConfig(config)\n return config\n }\n\n _configAfterMerge(config) {\n config.container = config.container === false ? document.body : getElement(config.container)\n\n if (typeof config.delay === 'number') {\n config.delay = {\n show: config.delay,\n hide: config.delay\n }\n }\n\n if (typeof config.title === 'number') {\n config.title = config.title.toString()\n }\n\n if (typeof config.content === 'number') {\n config.content = config.content.toString()\n }\n\n return config\n }\n\n _getDelegateConfig() {\n const config = {}\n\n for (const [key, value] of Object.entries(this._config)) {\n if (this.constructor.Default[key] !== value) {\n config[key] = value\n }\n }\n\n config.selector = false\n config.trigger = 'manual'\n\n // In the future can be replaced with:\n // const keysWithDifferentValues = Object.entries(this._config).filter(entry => this.constructor.Default[entry[0]] !== this._config[entry[0]])\n // `Object.fromEntries(keysWithDifferentValues)`\n return config\n }\n\n _disposePopper() {\n if (this._popper) {\n this._popper.destroy()\n this._popper = null\n }\n\n if (this.tip) {\n this.tip.remove()\n this.tip = null\n }\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Tooltip.getOrCreateInstance(this, config)\n\n if (typeof config !== 'string') {\n return\n }\n\n if (typeof data[config] === 'undefined') {\n throw new TypeError(`No method named \"${config}\"`)\n }\n\n data[config]()\n })\n }\n}\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Tooltip)\n\nexport default Tooltip\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap popover.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport Tooltip from './tooltip.js'\nimport { defineJQueryPlugin } from './util/index.js'\n\n/**\n * Constants\n */\n\nconst NAME = 'popover'\n\nconst SELECTOR_TITLE = '.popover-header'\nconst SELECTOR_CONTENT = '.popover-body'\n\nconst Default = {\n ...Tooltip.Default,\n content: '',\n offset: [0, 8],\n placement: 'right',\n template: '
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' +\n '
' +\n '
',\n trigger: 'click'\n}\n\nconst DefaultType = {\n ...Tooltip.DefaultType,\n content: '(null|string|element|function)'\n}\n\n/**\n * Class definition\n */\n\nclass Popover extends Tooltip {\n // Getters\n static get Default() {\n return Default\n }\n\n static get DefaultType() {\n return DefaultType\n }\n\n static get NAME() {\n return NAME\n }\n\n // Overrides\n _isWithContent() {\n return this._getTitle() || this._getContent()\n }\n\n // Private\n _getContentForTemplate() {\n return {\n [SELECTOR_TITLE]: this._getTitle(),\n [SELECTOR_CONTENT]: this._getContent()\n }\n }\n\n _getContent() {\n return this._resolvePossibleFunction(this._config.content)\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Popover.getOrCreateInstance(this, config)\n\n if (typeof config !== 'string') {\n return\n }\n\n if (typeof data[config] === 'undefined') {\n throw new TypeError(`No method named \"${config}\"`)\n }\n\n data[config]()\n })\n }\n}\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Popover)\n\nexport default Popover\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap scrollspy.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport BaseComponent from './base-component.js'\nimport EventHandler from './dom/event-handler.js'\nimport SelectorEngine from './dom/selector-engine.js'\nimport { defineJQueryPlugin, getElement, isDisabled, isVisible } from './util/index.js'\n\n/**\n * Constants\n */\n\nconst NAME = 'scrollspy'\nconst DATA_KEY = 'bs.scrollspy'\nconst EVENT_KEY = `.${DATA_KEY}`\nconst DATA_API_KEY = '.data-api'\n\nconst EVENT_ACTIVATE = `activate${EVENT_KEY}`\nconst EVENT_CLICK = `click${EVENT_KEY}`\nconst EVENT_LOAD_DATA_API = `load${EVENT_KEY}${DATA_API_KEY}`\n\nconst CLASS_NAME_DROPDOWN_ITEM = 'dropdown-item'\nconst CLASS_NAME_ACTIVE = 'active'\n\nconst SELECTOR_DATA_SPY = '[data-bs-spy=\"scroll\"]'\nconst SELECTOR_TARGET_LINKS = '[href]'\nconst SELECTOR_NAV_LIST_GROUP = '.nav, .list-group'\nconst SELECTOR_NAV_LINKS = '.nav-link'\nconst SELECTOR_NAV_ITEMS = '.nav-item'\nconst SELECTOR_LIST_ITEMS = '.list-group-item'\nconst SELECTOR_LINK_ITEMS = `${SELECTOR_NAV_LINKS}, ${SELECTOR_NAV_ITEMS} > ${SELECTOR_NAV_LINKS}, ${SELECTOR_LIST_ITEMS}`\nconst SELECTOR_DROPDOWN = '.dropdown'\nconst SELECTOR_DROPDOWN_TOGGLE = '.dropdown-toggle'\n\nconst Default = {\n offset: null, // TODO: v6 @deprecated, keep it for backwards compatibility reasons\n rootMargin: '0px 0px -25%',\n smoothScroll: false,\n target: null,\n threshold: [0.1, 0.5, 1]\n}\n\nconst DefaultType = {\n offset: '(number|null)', // TODO v6 @deprecated, keep it for backwards compatibility reasons\n rootMargin: 'string',\n smoothScroll: 'boolean',\n target: 'element',\n threshold: 'array'\n}\n\n/**\n * Class definition\n */\n\nclass ScrollSpy extends BaseComponent {\n constructor(element, config) {\n super(element, config)\n\n // this._element is the observablesContainer and config.target the menu links wrapper\n this._targetLinks = new Map()\n this._observableSections = new Map()\n this._rootElement = getComputedStyle(this._element).overflowY === 'visible' ? null : this._element\n this._activeTarget = null\n this._observer = null\n this._previousScrollData = {\n visibleEntryTop: 0,\n parentScrollTop: 0\n }\n this.refresh() // initialize\n }\n\n // Getters\n static get Default() {\n return Default\n }\n\n static get DefaultType() {\n return DefaultType\n }\n\n static get NAME() {\n return NAME\n }\n\n // Public\n refresh() {\n this._initializeTargetsAndObservables()\n this._maybeEnableSmoothScroll()\n\n if (this._observer) {\n this._observer.disconnect()\n } else {\n this._observer = this._getNewObserver()\n }\n\n for (const section of this._observableSections.values()) {\n this._observer.observe(section)\n }\n }\n\n dispose() {\n this._observer.disconnect()\n super.dispose()\n }\n\n // Private\n _configAfterMerge(config) {\n // TODO: on v6 target should be given explicitly & remove the {target: 'ss-target'} case\n config.target = getElement(config.target) || document.body\n\n // TODO: v6 Only for backwards compatibility reasons. Use rootMargin only\n config.rootMargin = config.offset ? `${config.offset}px 0px -30%` : config.rootMargin\n\n if (typeof config.threshold === 'string') {\n config.threshold = config.threshold.split(',').map(value => Number.parseFloat(value))\n }\n\n return config\n }\n\n _maybeEnableSmoothScroll() {\n if (!this._config.smoothScroll) {\n return\n }\n\n // unregister any previous listeners\n EventHandler.off(this._config.target, EVENT_CLICK)\n\n EventHandler.on(this._config.target, EVENT_CLICK, SELECTOR_TARGET_LINKS, event => {\n const observableSection = this._observableSections.get(event.target.hash)\n if (observableSection) {\n event.preventDefault()\n const root = this._rootElement || window\n const height = observableSection.offsetTop - this._element.offsetTop\n if (root.scrollTo) {\n root.scrollTo({ top: height, behavior: 'smooth' })\n return\n }\n\n // Chrome 60 doesn't support `scrollTo`\n root.scrollTop = height\n }\n })\n }\n\n _getNewObserver() {\n const options = {\n root: this._rootElement,\n threshold: this._config.threshold,\n rootMargin: this._config.rootMargin\n }\n\n return new IntersectionObserver(entries => this._observerCallback(entries), options)\n }\n\n // The logic of selection\n _observerCallback(entries) {\n const targetElement = entry => this._targetLinks.get(`#${entry.target.id}`)\n const activate = entry => {\n this._previousScrollData.visibleEntryTop = entry.target.offsetTop\n this._process(targetElement(entry))\n }\n\n const parentScrollTop = (this._rootElement || document.documentElement).scrollTop\n const userScrollsDown = parentScrollTop >= this._previousScrollData.parentScrollTop\n this._previousScrollData.parentScrollTop = parentScrollTop\n\n for (const entry of entries) {\n if (!entry.isIntersecting) {\n this._activeTarget = null\n this._clearActiveClass(targetElement(entry))\n\n continue\n }\n\n const entryIsLowerThanPrevious = entry.target.offsetTop >= this._previousScrollData.visibleEntryTop\n // if we are scrolling down, pick the bigger offsetTop\n if (userScrollsDown && entryIsLowerThanPrevious) {\n activate(entry)\n // if parent isn't scrolled, let's keep the first visible item, breaking the iteration\n if (!parentScrollTop) {\n return\n }\n\n continue\n }\n\n // if we are scrolling up, pick the smallest offsetTop\n if (!userScrollsDown && !entryIsLowerThanPrevious) {\n activate(entry)\n }\n }\n }\n\n _initializeTargetsAndObservables() {\n this._targetLinks = new Map()\n this._observableSections = new Map()\n\n const targetLinks = SelectorEngine.find(SELECTOR_TARGET_LINKS, this._config.target)\n\n for (const anchor of targetLinks) {\n // ensure that the anchor has an id and is not disabled\n if (!anchor.hash || isDisabled(anchor)) {\n continue\n }\n\n const observableSection = SelectorEngine.findOne(decodeURI(anchor.hash), this._element)\n\n // ensure that the observableSection exists & is visible\n if (isVisible(observableSection)) {\n this._targetLinks.set(decodeURI(anchor.hash), anchor)\n this._observableSections.set(anchor.hash, observableSection)\n }\n }\n }\n\n _process(target) {\n if (this._activeTarget === target) {\n return\n }\n\n this._clearActiveClass(this._config.target)\n this._activeTarget = target\n target.classList.add(CLASS_NAME_ACTIVE)\n this._activateParents(target)\n\n EventHandler.trigger(this._element, EVENT_ACTIVATE, { relatedTarget: target })\n }\n\n _activateParents(target) {\n // Activate dropdown parents\n if (target.classList.contains(CLASS_NAME_DROPDOWN_ITEM)) {\n SelectorEngine.findOne(SELECTOR_DROPDOWN_TOGGLE, target.closest(SELECTOR_DROPDOWN))\n .classList.add(CLASS_NAME_ACTIVE)\n return\n }\n\n for (const listGroup of SelectorEngine.parents(target, SELECTOR_NAV_LIST_GROUP)) {\n // Set triggered links parents as active\n // With both
    and