Merge pull request #14 from iatgen/master

Update with iatgen head

.Rbuildignore

@@ -1,2 +1,3 @@
 ^.*\.Rproj$
 ^\.Rproj\.user$
+.github

.github/workflows/ci-tests.yml

@@ -0,0 +1,12 @@
+name: ci-tests
+on: [push]
+jobs:
+  r-cmd-check:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v3
+      - uses: r-lib/actions/setup-r@v2
+      - uses: r-lib/actions/setup-r-dependencies@v2
+        with:
+          extra-packages: any::rcmdcheck
+      - uses: r-lib/actions/check-r-package@v2

DESCRIPTION

@@ -1,13 +1,14 @@
 Package: iatgen
 Type: Package
 Title: IATs for Qualtrics
-Version: 1.5.0
+Version: 1.6.0
 Authors@R: c(person("Tom","Carpenter", role = c("aut"), email = "[email protected]"),
 	     person("Michal","Kouril", role = c("aut", "cre"), email = "[email protected]"))
 Description: Generate and analyze IATs (Implicit Association Tests) for use in Qualtrics
     <https://iatgen.wordpress.com/>.
 License: CC BY-NC 4.0
 Encoding: UTF-8
-RoxygenNote: 7.1.1
-Imports: jsonlite, psych, stringr, testthat
+RoxygenNote: 7.2.3
+Imports: jsonlite, psych, stringr
+Suggests: testthat
 NeedsCompilation: no

NAMESPACE

@@ -10,6 +10,12 @@ export(parcelIAT)
 export(writeIATfull)
 importFrom(jsonlite,minify)
 importFrom(jsonlite,toJSON)
+importFrom(psych,alpha)
 importFrom(stats,cor)
 importFrom(stats,median)
 importFrom(stats,sd)
+importFrom(stringr,str_count)
+importFrom(stringr,str_length)
+importFrom(stringr,str_locate)
+importFrom(stringr,str_replace_all)
+importFrom(stringr,str_sub)

R/IATalpha.R

@@ -4,6 +4,7 @@
 #' @param data an object created by \code{cleanIAT()} representing a cleaned IAT.
 #' @return Returns a list with alphas based on the practice trials, the critical trials, and the entire IAT. Also retuns a matrix `diffscores` of the differences in latency for all matched trials (pooled practice and critical into one matrix)
 #' @export
+#' @importFrom psych alpha
 #' @references Schnabel, K., Asendorpf, J. B., & Greenwald, A. G. (2008). Using Implicit Association Tests for the Assessment of Implicit Personality Self-Concept. In The SAGE Handbook of Personality Theory and Assessment: Volume 2—Personality Measurement and Testing (pp. 508–528). SAGE Publications Ltd. https://doi.org/10.4135/9781849200479.n24
 #' @examples \dontrun{
 #' ### RELIABILITY ANALYSIS - ESTIMATE ONLY ###
@@ -12,33 +13,31 @@
 #' ### RELIABILITY ANALYSIS - ENTIRE RELIABILITY OUTPUT ###
 #' IATalpha(clean)
 #' }
-
-IATalpha <- function(data){
-  # require(psych)
+IATalpha <- function(data) {
   prac1 <- data$clean.latencies.prac1
   prac2 <- data$clean.latencies.prac2
   crit1 <- data$clean.latencies.crit1
   crit2 <- data$clean.latencies.crit2
 
-  #matricies must have exact same dimensions.
+  # matricies must have exact same dimensions.
   # Any weird or extra trials due to error will cause issues. id correct dimensions and coerce.
   getmode <- function(v) {
     uniqv <- unique(v)
     uniqv[which.max(tabulate(match(v, uniqv)))]
   }
 
-  prac1.cols <- getmode(rowSums(!is.na(prac1[!data$skipped & !data$drop.participant,])))
-  prac2.cols <- getmode(rowSums(!is.na(prac2[!data$skipped & !data$drop.participant,])))
-  crit1.cols <- getmode(rowSums(!is.na(crit1[!data$skipped & !data$drop.participant,])))
-  crit2.cols <- getmode(rowSums(!is.na(crit2[!data$skipped & !data$drop.participant,])))
+  prac1.cols <- getmode(rowSums(!is.na(prac1[!data$skipped & !data$drop.participant, ])))
+  prac2.cols <- getmode(rowSums(!is.na(prac2[!data$skipped & !data$drop.participant, ])))
+  crit1.cols <- getmode(rowSums(!is.na(crit1[!data$skipped & !data$drop.participant, ])))
+  crit2.cols <- getmode(rowSums(!is.na(crit2[!data$skipped & !data$drop.participant, ])))
 
-  prac1 <- prac1[,1:prac1.cols]
-  prac2 <- prac2[,1:prac2.cols]
-  crit1 <- crit1[,1:crit1.cols]
-  crit2 <- crit2[,1:crit2.cols]
+  prac1 <- prac1[, 1:prac1.cols]
+  prac2 <- prac2[, 1:prac2.cols]
+  crit1 <- crit1[, 1:crit1.cols]
+  crit2 <- crit2[, 1:crit2.cols]
 
-  prac <- prac1-prac2
-  crit <- crit1-crit2
+  prac <- prac1 - prac2
+  crit <- crit1 - crit2
 
   df <- cbind(prac, crit)
   colnames(df) <- paste0("trial", 1:ncol(df))
@@ -47,5 +46,5 @@ IATalpha <- function(data){
   alpha.crit <- suppressMessages(suppressWarnings(psych::alpha(crit)$total[1]))
   alpha.total <- suppressMessages(suppressWarnings(psych::alpha(df)$total[1]))
 
-  return(list(alpha.prac=alpha.prac, alpha.crit=alpha.crit, alpha.total=alpha.total, diffscores=df))
+  return(list(alpha.prac = alpha.prac, alpha.crit = alpha.crit, alpha.total = alpha.total, diffscores = df))
 }