@@ -2749,19 +2756,19 @@ Trial type by age interac
(Intercept)
|
-2.36
+2.51
|
2.55
|
-0.93
+0.98
|
--2.63
+-2.49
|
-7.34
+7.52
|
@@ -2772,19 +2779,19 @@ Trial type by age interac
condition_disagree
|
--5.81
+-6.01
|
-2.73
+2.74
|
--2.13
+-2.20
|
--11.16
+-11.38
|
--0.47
+-0.65
|
@@ -2795,19 +2802,19 @@ Trial type by age interac
age_continuous
|
--0.46
+-0.47
|
0.28
|
--1.66
+-1.71
|
--1.00
+-1.02
|
-0.08
+0.07
|
@@ -2818,19 +2825,19 @@ Trial type by age interac
condition_disagree:age_continuous
|
-0.83
+0.85
|
0.30
|
-2.77
+2.83
|
-0.24
+0.26
|
-1.41
+1.43
|
@@ -2942,85 +2949,84 @@ Inference
df.age.means = df.plot.individual %>%
distinct(participant, age_continuous) %>%
- mutate(age_continuous = ifelse(age_continuous == 12, 11.99, age_continuous),
- age_group = floor(age_continuous)) %>%
- group_by(age_group) %>%
- summarize(age_mean = mean(age_continuous),
- n = str_c("n = ", n())) %>%
- ungroup()
-
-df.plot.means = df.exp1 %>%
- mutate(condition_disagree = as.character(condition_disagree)) %>%
- group_by(participant, age_group, condition_disagree) %>%
- summarize(pct_amb = sum(ambiguous_yes)/n()) %>%
- group_by(age_group, condition_disagree) %>%
- reframe(response = smean.cl.boot(pct_amb),
- name = c("mean", "low", "high")) %>%
- left_join(df.age.means,
- by = "age_group") %>%
- pivot_wider(names_from = name,
- values_from = response) %>%
- mutate(age_mean = ifelse(condition_disagree == 0, age_mean - 0.05, age_mean + 0.05))
-
-df.plot.text = df.plot.means %>%
- distinct(age_group, n)
-
-ggplot() +
- geom_hline(yintercept = 0.5,
- linetype = 2,
- alpha = 0.1) +
- geom_point(data = df.plot.individual,
- mapping = aes(x = age_continuous,
- y = pct_amb,
- color = condition_disagree),
- alpha = 0.5,
- show.legend = T,
- shape = 16,
- size = 1.5) +
- geom_linerange(data = df.plot.means,
- mapping = aes(x = age_mean,
- y = mean,
- ymin = low,
- ymax = high),
- color = "gray40") +
- geom_point(data = df.plot.means,
- mapping = aes(x = age_mean,
- y = mean,
- fill = condition_disagree),
- shape = 21,
- size = 3,
- show.legend = T) +
- geom_text(data = df.plot.text,
- mapping = aes(x = age_group + 0.5,
- y = 1.05,
- label = n),
- hjust = 0.5) +
- scale_y_continuous(labels = percent) +
- labs(x = "Age (in years)",
- y = "% Infer Ambiguous Utterance",
- title = "Experiment 1: Inference") +
- coord_cartesian(xlim = c(7, 12),
- ylim = c(0, 1),
- clip = "off") +
- scale_color_manual(name = "Trial Type",
- labels = c("Agreement", "Disagreement"),
- values = c(l.color$agreement, l.color$disagreement),
- guide = guide_legend(reverse = T)) +
- scale_fill_manual(name = "Trial Type",
- labels = c("Agreement", "Disagreement"),
- values = c(l.color$agreement, l.color$disagreement),
- guide = guide_legend(reverse = T)) +
- theme(plot.title = element_text(hjust = 0.5,
- vjust = 2,
- size = 18,
- face = "bold"),
- axis.title.y = element_markdown(color = l.color$ambiguous),
- legend.position = "right")
-
-ggsave(filename = "../figures/plots/exp1_inference.pdf",
- width = 8,
- height = 4)
-
+ mutate(age_group = floor(age_continuous)) %>%
+ group_by(age_group) %>%
+ summarize(age_mean = mean(age_continuous),
+ n = str_c("n = ", n())) %>%
+ ungroup()
+
+df.plot.means = df.exp1 %>%
+ mutate(condition_disagree = as.character(condition_disagree)) %>%
+ group_by(participant, age_group, condition_disagree) %>%
+ summarize(pct_amb = sum(ambiguous_yes)/n()) %>%
+ group_by(age_group, condition_disagree) %>%
+ reframe(response = smean.cl.boot(pct_amb),
+ name = c("mean", "low", "high")) %>%
+ left_join(df.age.means,
+ by = "age_group") %>%
+ pivot_wider(names_from = name,
+ values_from = response) %>%
+ mutate(age_mean = ifelse(condition_disagree == 0, age_mean - 0.05, age_mean + 0.05))
+
+df.plot.text = df.plot.means %>%
+ distinct(age_group, n)
+
+ggplot() +
+ geom_hline(yintercept = 0.5,
+ linetype = 2,
+ alpha = 0.1) +
+ geom_point(data = df.plot.individual,
+ mapping = aes(x = age_continuous,
+ y = pct_amb,
+ color = condition_disagree),
+ alpha = 0.5,
+ show.legend = T,
+ shape = 16,
+ size = 1.5) +
+ geom_linerange(data = df.plot.means,
+ mapping = aes(x = age_mean,
+ y = mean,
+ ymin = low,
+ ymax = high),
+ color = "gray40") +
+ geom_point(data = df.plot.means,
+ mapping = aes(x = age_mean,
+ y = mean,
+ fill = condition_disagree),
+ shape = 21,
+ size = 3,
+ show.legend = T) +
+ geom_text(data = df.plot.text,
+ mapping = aes(x = age_group + 0.5,
+ y = 1.05,
+ label = n),
+ hjust = 0.5) +
+ scale_y_continuous(labels = percent) +
+ labs(x = "Age (in years)",
+ y = "% Infer Ambiguous Utterance",
+ title = "Experiment 1: Inference") +
+ coord_cartesian(xlim = c(7, 12),
+ ylim = c(0, 1),
+ clip = "off") +
+ scale_color_manual(name = "Trial Type",
+ labels = c("Agreement", "Disagreement"),
+ values = c(l.color$agreement, l.color$disagreement),
+ guide = guide_legend(reverse = T)) +
+ scale_fill_manual(name = "Trial Type",
+ labels = c("Agreement", "Disagreement"),
+ values = c(l.color$agreement, l.color$disagreement),
+ guide = guide_legend(reverse = T)) +
+ theme(plot.title = element_text(hjust = 0.5,
+ vjust = 2,
+ size = 18,
+ face = "bold"),
+ axis.title.y = element_markdown(color = l.color$ambiguous),
+ legend.position = "right")
+
+ggsave(filename = "../figures/plots/exp1_inference.pdf",
+ width = 8,
+ height = 4)
+
@@ -4049,7 +4055,8 @@ Inference condition
-prop.table(table(df.exp2.infer$condition_disagree, df.exp2.infer$ambiguous_yes), margin=1)
prop.table(table(df.exp2.infer$condition_disagree, df.exp2.infer$ambiguous_yes),
+ margin = 1)
0 1
0 0.91071429 0.08928571
@@ -4650,7 +4657,8 @@ Inference condition: Fi
(Intercept) condition_disagree
-0.6931 -0.4055
optimizer (Nelder_Mead) convergence code: 0 (OK) ; 0 optimizer warnings; 1 lme4 warnings
-prop.table(table(df.exp2.infer.7.1$condition_disagree, df.exp2.infer.7.1$ambiguous_yes), margin=1)
prop.table(table(df.exp2.infer.7.1$condition_disagree, df.exp2.infer.7.1$ambiguous_yes),
+ margin = 1)
0 1
0 0.6666667 0.3333333
@@ -4764,7 +4772,8 @@ Inference condition: Fi
(Intercept) condition_disagree
-1.099 1.435
optimizer (Nelder_Mead) convergence code: 0 (OK) ; 0 optimizer warnings; 1 lme4 warnings
-prop.table(table(df.exp2.infer.7.4$condition_disagree, df.exp2.infer.7.4$ambiguous_yes), margin=1)
prop.table(table(df.exp2.infer.7.4$condition_disagree, df.exp2.infer.7.4$ambiguous_yes),
+ margin = 1)
0 1
0 0.7500000 0.2500000
@@ -5125,85 +5134,84 @@ Prediction
df.age.means = df.plot.individual %>%
distinct(participant, age_continuous) %>%
- mutate(age_continuous = ifelse(age_continuous == 12, 11.99, age_continuous),
- age_group = floor(age_continuous)) %>%
- group_by(age_group) %>%
- summarize(age_mean = mean(age_continuous),
- n = str_c("n = ", n())) %>%
- ungroup()
-
-df.plot.means = df.exp2.predict %>%
- mutate(condition_amb = as.character(condition_amb)) %>%
- group_by(participant, age_group, condition_amb) %>%
- summarize(pct_dis = sum(dis_yes)/n()) %>%
- group_by(age_group, condition_amb) %>%
- reframe(response = smean.cl.boot(pct_dis),
- name = c("mean", "low", "high")) %>%
- left_join(df.age.means,
- by = "age_group") %>%
- pivot_wider(names_from = name,
- values_from = response) %>%
- mutate(age_mean = ifelse(condition_amb == 0, age_mean - 0.05, age_mean + 0.05))
-
-df.plot.text = df.plot.means %>%
- distinct(age_group, n)
+ mutate(age_group = floor(age_continuous)) %>%
+ group_by(age_group) %>%
+ summarize(age_mean = mean(age_continuous),
+ n = str_c("n = ", n())) %>%
+ ungroup()
+
+df.plot.means = df.exp2.predict %>%
+ mutate(condition_amb = as.character(condition_amb)) %>%
+ group_by(participant, age_group, condition_amb) %>%
+ summarize(pct_dis = sum(dis_yes)/n()) %>%
+ group_by(age_group, condition_amb) %>%
+ reframe(response = smean.cl.boot(pct_dis),
+ name = c("mean", "low", "high")) %>%
+ left_join(df.age.means,
+ by = "age_group") %>%
+ pivot_wider(names_from = name,
+ values_from = response) %>%
+ mutate(age_mean = ifelse(condition_amb == 0, age_mean - 0.05, age_mean + 0.05))
+
+df.plot.text = df.plot.means %>%
+ distinct(age_group, n)
+
-
-ggplot() +
- geom_hline(yintercept = 0.5,
- linetype = 2,
- alpha = 0.1) +
- geom_point(data = df.plot.individual,
- mapping = aes(x = age_continuous,
- y = pct_dis,
- color = condition_amb),
- alpha = 0.5,
- show.legend = T,
- shape = 16,
- size = 1.5) +
- geom_linerange(data = df.plot.means,
- mapping = aes(x = age_mean,
- y = mean,
- ymin = low,
- ymax = high),
- color = "gray40") +
- geom_point(data = df.plot.means,
- mapping = aes(x = age_mean,
- y = mean,
- fill = condition_amb),
- shape = 21,
- size = 3,
- show.legend = T) +
- geom_text(data = df.plot.text,
- mapping = aes(x = age_group + 0.5,
- y = 1.05,
- label = n),
- hjust = 0.5) +
- scale_y_continuous(labels = percent) +
- labs(x = "Age (in years)",
- y = "% Predict Disagreement",
- title = "Experiment 2: Prediction") +
- coord_cartesian(xlim = c(7, 12),
- ylim = c(0, 1),
- clip = "off") +
- scale_color_manual(name = "Trial Type",
- labels = c("Unambiguous", "Ambiguous"),
- values = c(l.color$unambiguous, l.color$ambiguous),
- guide = guide_legend(reverse = T)) +
- scale_fill_manual(name = "Trial Type",
- labels = c("Unambiguous", "Ambiguous"),
- values = c(l.color$unambiguous, l.color$ambiguous),
- guide = guide_legend(reverse = T)) +
- theme(plot.title = element_text(hjust = 0.5,
- vjust = 2,
- size = 18,
- face = "bold"),
- axis.title.y = element_markdown(color = l.color$disagreement),
- legend.position = "right")
-
-ggsave(filename = "../figures/plots/exp2_prediction.pdf",
- width = 8,
- height = 4)
+ggplot() +
+ geom_hline(yintercept = 0.5,
+ linetype = 2,
+ alpha = 0.1) +
+ geom_point(data = df.plot.individual,
+ mapping = aes(x = age_continuous,
+ y = pct_dis,
+ color = condition_amb),
+ alpha = 0.5,
+ show.legend = T,
+ shape = 16,
+ size = 1.5) +
+ geom_linerange(data = df.plot.means,
+ mapping = aes(x = age_mean,
+ y = mean,
+ ymin = low,
+ ymax = high),
+ color = "gray40") +
+ geom_point(data = df.plot.means,
+ mapping = aes(x = age_mean,
+ y = mean,
+ fill = condition_amb),
+ shape = 21,
+ size = 3,
+ show.legend = T) +
+ geom_text(data = df.plot.text,
+ mapping = aes(x = age_group + 0.5,
+ y = 1.05,
+ label = n),
+ hjust = 0.5) +
+ scale_y_continuous(labels = percent) +
+ labs(x = "Age (in years)",
+ y = "% Predict Disagreement",
+ title = "Experiment 2: Prediction") +
+ coord_cartesian(xlim = c(7, 12),
+ ylim = c(0, 1),
+ clip = "off") +
+ scale_color_manual(name = "Trial Type",
+ labels = c("Unambiguous", "Ambiguous"),
+ values = c(l.color$unambiguous, l.color$ambiguous),
+ guide = guide_legend(reverse = T)) +
+ scale_fill_manual(name = "Trial Type",
+ labels = c("Unambiguous", "Ambiguous"),
+ values = c(l.color$unambiguous, l.color$ambiguous),
+ guide = guide_legend(reverse = T)) +
+ theme(plot.title = element_text(hjust = 0.5,
+ vjust = 2,
+ size = 18,
+ face = "bold"),
+ axis.title.y = element_markdown(color = l.color$disagreement),
+ legend.position = "right")
+
+ggsave(filename = "../figures/plots/exp2_prediction.pdf",
+ width = 8,
+ height = 4)
@@ -5217,120 +5225,121 @@
Inference
df.age.means = df.plot.individual %>%
distinct(participant, age_continuous) %>%
-
mutate(age_continuous = ifelse(age_continuous == 12, 11.99, age_continuous),
-
age_group = floor(age_continuous)) %>%
-
group_by(age_group) %>%
-
summarize(age_mean = mean(age_continuous),
-
n = str_c("n = ", n())) %>%
-
ungroup()
-
-
df.plot.means = df.exp2.infer %>%
-
mutate(condition_disagree = as.character(condition_disagree)) %>%
-
group_by(participant, age_group, condition_disagree) %>%
-
summarize(pct_amb = sum(ambiguous_yes)/n()) %>%
-
group_by(age_group, condition_disagree) %>%
-
reframe(response = smean.cl.boot(pct_amb),
-
name = c("mean", "low", "high")) %>%
-
left_join(df.age.means,
-
by = "age_group") %>%
-
pivot_wider(names_from = name,
-
values_from = response) %>%
-
mutate(age_mean = ifelse(condition_disagree == 0, age_mean - 0.05, age_mean + 0.05))
-
-
df.plot.text = df.plot.means %>%
-
distinct(age_group, n)
-
-
df.model = df.model.posterior %>%
-
mutate(name = "posterior") %>%
-
select(-c(utterance, probability, prior)) %>%
-
bind_rows(df.model.softmax %>%
-
mutate(name = "softmax")) %>%
-
bind_rows(df.model.softmax.linear %>%
-
mutate(name = "softmax increase")) %>%
-
mutate(condition_disagree = factor(condition,
-
levels = c("Agreement Trials",
-
"Disagreement Trials"),
-
labels = c(0,
-
1))) %>%
-
left_join(df.age.means %>%
-
select(-n),
-
by = "age_group") %>%
-
mutate(age_mean = ifelse(condition_disagree == 0,
-
age_mean - 0.05,
-
age_mean + 0.05))
-
-
ggplot() +
-
geom_hline(yintercept = 0.5,
-
linetype = 2,
-
alpha = 0.1) +
-
geom_point(data = df.plot.individual,
-
mapping = aes(x = age_continuous,
-
y = pct_amb,
-
color = condition_disagree),
-
alpha = 0.5,
-
show.legend = T,
-
shape = 16,
-
size = 1.5) +
-
geom_linerange(data = df.plot.means,
-
mapping = aes(x = age_mean,
-
y = mean,
-
ymin = low,
-
ymax = high),
-
color = "gray40",
-
show.legend = F) +
-
geom_point(data = df.plot.means,
-
mapping = aes(x = age_mean,
-
y = mean,
-
fill = condition_disagree),
-
shape = 21,
-
size = 3,
-
show.legend = F) +
-
geom_point(data = df.model,
-
mapping = aes(x = age_mean,
-
y = posterior,
-
shape = name,
-
fill = condition_disagree),
-
size = 1.5,
-
alpha = 0.5,
-
show.legend = T) +
-
geom_text(data = df.plot.text,
-
mapping = aes(x = age_group + 0.5,
-
y = 1.05,
-
label = n),
-
hjust = 0.5) +
-
scale_y_continuous(labels = percent) +
-
labs(x = "Age (in years)",
-
y = "% Infer Ambiguous Utterance",
-
title = "Experiment 2: Inference") +
-
coord_cartesian(xlim = c(7, 12),
-
ylim = c(0, 1),
-
clip = "off") +
-
scale_color_manual(name = "Trial Type",
-
labels = c("Agreement", "Disagreement"),
-
values = c(l.color$agreement, l.color$disagreement)) +
-
scale_fill_manual(name = "Trial Type",
-
labels = c("Agreement", "Disagreement"),
-
values = c(l.color$agreement, l.color$disagreement)) +
-
scale_shape_manual(name = "Model",
-
labels = c("posterior", "softmax", "softmax increase"),
-
values = c(21, 22, 23)) +
-
theme(plot.title = element_text(hjust = 0.5,
-
vjust = 2,
-
size = 18,
-
face = "bold"),
-
axis.title.y = element_markdown(color = l.color$ambiguous),
-
legend.position = "right") +
-
guides(fill = guide_legend(override.aes = list(shape = 21,
-
size = 3),
+
mutate(age_group = floor(age_continuous)) %>%
+
group_by(age_group) %>%
+
summarize(age_mean = mean(age_continuous),
+
n = str_c("n = ", n())) %>%
+
ungroup()
+
+
df.plot.means = df.exp2.infer %>%
+
mutate(condition_disagree = as.character(condition_disagree)) %>%
+
group_by(participant, age_group, condition_disagree) %>%
+
summarize(pct_amb = sum(ambiguous_yes)/n()) %>%
+
group_by(age_group, condition_disagree) %>%
+
reframe(response = smean.cl.boot(pct_amb),
+
name = c("mean", "low", "high")) %>%
+
left_join(df.age.means,
+
by = "age_group") %>%
+
pivot_wider(names_from = name,
+
values_from = response) %>%
+
mutate(age_mean = ifelse(condition_disagree == 0, age_mean - 0.05, age_mean + 0.05))
+
+
df.plot.text = df.plot.means %>%
+
distinct(age_group, n)
+
+
df.model = df.model.posterior %>%
+
mutate(name = "posterior") %>%
+
select(-c(utterance, probability, prior)) %>%
+
bind_rows(df.model.softmax %>%
+
mutate(name = "softmax")) %>%
+
bind_rows(df.model.softmax.linear %>%
+
mutate(name = "softmax increase")) %>%
+
mutate(condition_disagree = factor(condition,
+
levels = c("Agreement Trials",
+
"Disagreement Trials"),
+
labels = c(0,
+
1))) %>%
+
left_join(df.age.means %>%
+
select(-n),
+
by = "age_group") %>%
+
mutate(age_mean = ifelse(condition_disagree == 0,
+
age_mean - 0.05,
+
age_mean + 0.05))
+
+
ggplot() +
+
geom_hline(yintercept = 0.5,
+
linetype = 2,
+
alpha = 0.1) +
+
geom_point(data = df.plot.individual,
+
mapping = aes(x = age_continuous,
+
y = pct_amb,
+
color = condition_disagree),
+
alpha = 0.5,
+
show.legend = T,
+
shape = 16,
+
size = 1.5) +
+
geom_linerange(data = df.plot.means,
+
mapping = aes(x = age_mean,
+
y = mean,
+
ymin = low,
+
ymax = high),
+
color = "gray40",
+
show.legend = F) +
+
geom_point(data = df.plot.means,
+
mapping = aes(x = age_mean,
+
y = mean,
+
fill = condition_disagree),
+
shape = 21,
+
size = 3,
+
show.legend = F) +
+
geom_point(data = df.model,
+
mapping = aes(x = age_mean,
+
y = posterior,
+
shape = name,
+
fill = condition_disagree),
+
size = 1.5,
+
alpha = 0.5,
+
show.legend = T) +
+
geom_text(data = df.plot.text,
+
mapping = aes(x = age_group + 0.5,
+
y = 1.05,
+
label = n),
+
hjust = 0.5) +
+
scale_y_continuous(labels = percent) +
+
labs(x = "Age (in years)",
+
y = "% Infer Ambiguous Utterance",
+
title = "Experiment 2: Inference") +
+
coord_cartesian(xlim = c(7, 12),
+
ylim = c(0, 1),
+
clip = "off") +
+
scale_color_manual(name = "Trial Type",
+
labels = c("Agreement", "Disagreement"),
+
values = c(l.color$agreement, l.color$disagreement)) +
+
scale_fill_manual(name = "Trial Type",
+
labels = c("Agreement", "Disagreement"),
+
values = c(l.color$agreement, l.color$disagreement)) +
+
scale_shape_manual(name = "Model",
+
labels = c("posterior", "softmax", "softmax increase"),
+
values = c(21, 22, 23)) +
+
theme(plot.title = element_text(hjust = 0.5,
+
vjust = 2,
+
size = 18,
+
face = "bold"),
+
axis.title.y = element_markdown(color = l.color$ambiguous),
+
legend.position = "right") +
+
guides(fill = guide_legend(override.aes = list(shape = 21,
+
size = 3,
+
alpha = 1),
reverse = T,
order = 1),
-
shape = guide_legend(override.aes = list(fill = "white", alpha = 1)),
-
color = "none")
-
-
ggsave(filename = "../figures/plots/exp2_inference.pdf",
-
width = 8,
-
height = 4)
+ shape = guide_legend(override.aes = list(fill = "white",
+ alpha = 1)),
+ color = "none")
+
+ggsave(filename = "../figures/plots/exp2_inference.pdf",
+ width = 8,
+ height = 4)
+
@@ -5343,7 +5352,7 @@ Session info
R version 4.3.2 (2023-10-31)
Platform: aarch64-apple-darwin20 (64-bit)
-Running under: macOS Sonoma 14.1.2
+Running under: macOS Sonoma 14.4.1
Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/lib/libRblas.0.dylib
diff --git a/docs/index.html b/docs/index.html
index ff96a15..6e01027 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -11,7 +11,7 @@
-
+
Children use disagreement to infer what happened
@@ -1803,7 +1803,7 @@
Children use disagreement to infer what happened
Jamie Amemiya, Gail D. Heyman & Tobias Gerstenberg
-April 01, 2024
+April 03, 2024
@@ -1893,8 +1893,15 @@ EXPERIMENT 1
DATA
Read in data
-
df.exp1 = read_csv("../data/data1_infer.csv") %>%
- rename(trial_order = trial_order_dada)
+
# fixed rounding issue; one participant was actually 11 and turned 12 the next day
+# participant reported they were 9 despite birth year indicating they were 8;
+# recoded to 9.69 given reported age likely more reliable
+
+df.exp1 = read_csv("../data/data1_infer.csv") %>%
+ rename(trial_order = trial_order_dada) %>%
+ mutate(age_continuous = ifelse(age_continuous == 12, 11.99,
+ ifelse(age_continuous == 8.69, 9.69,
+ age_continuous)))
@@ -2703,16 +2710,16 @@
Trial type by age interac
participant)
Data: data
AIC BIC logLik deviance df.resid
- 237.8463 254.5340 -113.9231 227.8463 203
+ 237.4681 254.1558 -113.7340 227.4681 203
Random effects:
Groups Name Std.Dev.
- participant (Intercept) 1.543
+ participant (Intercept) 1.546
Number of obs: 208, groups: participant, 52
Fixed Effects:
(Intercept) condition_disagree
- 2.3556 -5.8141
+ 2.5127 -6.0120
age_continuous condition_disagree:age_continuous
- -0.4584 0.8275
+ -0.4749 0.8474
@@ -2749,19 +2756,19 @@ Trial type by age interac
(Intercept)
|
-2.36
+2.51
|
2.55
|
-0.93
+0.98
|
--2.63
+-2.49
|
-7.34
+7.52
|
@@ -2772,19 +2779,19 @@ Trial type by age interac
condition_disagree
|
--5.81
+-6.01
|
-2.73
+2.74
|
--2.13
+-2.20
|
--11.16
+-11.38
|
--0.47
+-0.65
|
@@ -2795,19 +2802,19 @@ Trial type by age interac
age_continuous
|
--0.46
+-0.47
|
0.28
|
--1.66
+-1.71
|
--1.00
+-1.02
|
-0.08
+0.07
|
@@ -2818,19 +2825,19 @@ Trial type by age interac
condition_disagree:age_continuous
|
-0.83
+0.85
|
0.30
|
-2.77
+2.83
|
-0.24
+0.26
|
-1.41
+1.43
|
@@ -2942,85 +2949,84 @@ Inference
df.age.means = df.plot.individual %>%
distinct(participant, age_continuous) %>%
- mutate(age_continuous = ifelse(age_continuous == 12, 11.99, age_continuous),
- age_group = floor(age_continuous)) %>%
- group_by(age_group) %>%
- summarize(age_mean = mean(age_continuous),
- n = str_c("n = ", n())) %>%
- ungroup()
-
-df.plot.means = df.exp1 %>%
- mutate(condition_disagree = as.character(condition_disagree)) %>%
- group_by(participant, age_group, condition_disagree) %>%
- summarize(pct_amb = sum(ambiguous_yes)/n()) %>%
- group_by(age_group, condition_disagree) %>%
- reframe(response = smean.cl.boot(pct_amb),
- name = c("mean", "low", "high")) %>%
- left_join(df.age.means,
- by = "age_group") %>%
- pivot_wider(names_from = name,
- values_from = response) %>%
- mutate(age_mean = ifelse(condition_disagree == 0, age_mean - 0.05, age_mean + 0.05))
-
-df.plot.text = df.plot.means %>%
- distinct(age_group, n)
-
-ggplot() +
- geom_hline(yintercept = 0.5,
- linetype = 2,
- alpha = 0.1) +
- geom_point(data = df.plot.individual,
- mapping = aes(x = age_continuous,
- y = pct_amb,
- color = condition_disagree),
- alpha = 0.5,
- show.legend = T,
- shape = 16,
- size = 1.5) +
- geom_linerange(data = df.plot.means,
- mapping = aes(x = age_mean,
- y = mean,
- ymin = low,
- ymax = high),
- color = "gray40") +
- geom_point(data = df.plot.means,
- mapping = aes(x = age_mean,
- y = mean,
- fill = condition_disagree),
- shape = 21,
- size = 3,
- show.legend = T) +
- geom_text(data = df.plot.text,
- mapping = aes(x = age_group + 0.5,
- y = 1.05,
- label = n),
- hjust = 0.5) +
- scale_y_continuous(labels = percent) +
- labs(x = "Age (in years)",
- y = "% Infer Ambiguous Utterance",
- title = "Experiment 1: Inference") +
- coord_cartesian(xlim = c(7, 12),
- ylim = c(0, 1),
- clip = "off") +
- scale_color_manual(name = "Trial Type",
- labels = c("Agreement", "Disagreement"),
- values = c(l.color$agreement, l.color$disagreement),
- guide = guide_legend(reverse = T)) +
- scale_fill_manual(name = "Trial Type",
- labels = c("Agreement", "Disagreement"),
- values = c(l.color$agreement, l.color$disagreement),
- guide = guide_legend(reverse = T)) +
- theme(plot.title = element_text(hjust = 0.5,
- vjust = 2,
- size = 18,
- face = "bold"),
- axis.title.y = element_markdown(color = l.color$ambiguous),
- legend.position = "right")
-
-ggsave(filename = "../figures/plots/exp1_inference.pdf",
- width = 8,
- height = 4)
-
+ mutate(age_group = floor(age_continuous)) %>%
+ group_by(age_group) %>%
+ summarize(age_mean = mean(age_continuous),
+ n = str_c("n = ", n())) %>%
+ ungroup()
+
+df.plot.means = df.exp1 %>%
+ mutate(condition_disagree = as.character(condition_disagree)) %>%
+ group_by(participant, age_group, condition_disagree) %>%
+ summarize(pct_amb = sum(ambiguous_yes)/n()) %>%
+ group_by(age_group, condition_disagree) %>%
+ reframe(response = smean.cl.boot(pct_amb),
+ name = c("mean", "low", "high")) %>%
+ left_join(df.age.means,
+ by = "age_group") %>%
+ pivot_wider(names_from = name,
+ values_from = response) %>%
+ mutate(age_mean = ifelse(condition_disagree == 0, age_mean - 0.05, age_mean + 0.05))
+
+df.plot.text = df.plot.means %>%
+ distinct(age_group, n)
+
+ggplot() +
+ geom_hline(yintercept = 0.5,
+ linetype = 2,
+ alpha = 0.1) +
+ geom_point(data = df.plot.individual,
+ mapping = aes(x = age_continuous,
+ y = pct_amb,
+ color = condition_disagree),
+ alpha = 0.5,
+ show.legend = T,
+ shape = 16,
+ size = 1.5) +
+ geom_linerange(data = df.plot.means,
+ mapping = aes(x = age_mean,
+ y = mean,
+ ymin = low,
+ ymax = high),
+ color = "gray40") +
+ geom_point(data = df.plot.means,
+ mapping = aes(x = age_mean,
+ y = mean,
+ fill = condition_disagree),
+ shape = 21,
+ size = 3,
+ show.legend = T) +
+ geom_text(data = df.plot.text,
+ mapping = aes(x = age_group + 0.5,
+ y = 1.05,
+ label = n),
+ hjust = 0.5) +
+ scale_y_continuous(labels = percent) +
+ labs(x = "Age (in years)",
+ y = "% Infer Ambiguous Utterance",
+ title = "Experiment 1: Inference") +
+ coord_cartesian(xlim = c(7, 12),
+ ylim = c(0, 1),
+ clip = "off") +
+ scale_color_manual(name = "Trial Type",
+ labels = c("Agreement", "Disagreement"),
+ values = c(l.color$agreement, l.color$disagreement),
+ guide = guide_legend(reverse = T)) +
+ scale_fill_manual(name = "Trial Type",
+ labels = c("Agreement", "Disagreement"),
+ values = c(l.color$agreement, l.color$disagreement),
+ guide = guide_legend(reverse = T)) +
+ theme(plot.title = element_text(hjust = 0.5,
+ vjust = 2,
+ size = 18,
+ face = "bold"),
+ axis.title.y = element_markdown(color = l.color$ambiguous),
+ legend.position = "right")
+
+ggsave(filename = "../figures/plots/exp1_inference.pdf",
+ width = 8,
+ height = 4)
+
@@ -4049,7 +4055,8 @@ Inference condition
-prop.table(table(df.exp2.infer$condition_disagree, df.exp2.infer$ambiguous_yes), margin=1)
prop.table(table(df.exp2.infer$condition_disagree, df.exp2.infer$ambiguous_yes),
+ margin = 1)
0 1
0 0.91071429 0.08928571
@@ -4650,7 +4657,8 @@ Inference condition: Fi
(Intercept) condition_disagree
-0.6931 -0.4055
optimizer (Nelder_Mead) convergence code: 0 (OK) ; 0 optimizer warnings; 1 lme4 warnings
-prop.table(table(df.exp2.infer.7.1$condition_disagree, df.exp2.infer.7.1$ambiguous_yes), margin=1)
prop.table(table(df.exp2.infer.7.1$condition_disagree, df.exp2.infer.7.1$ambiguous_yes),
+ margin = 1)
0 1
0 0.6666667 0.3333333
@@ -4764,7 +4772,8 @@ Inference condition: Fi
(Intercept) condition_disagree
-1.099 1.435
optimizer (Nelder_Mead) convergence code: 0 (OK) ; 0 optimizer warnings; 1 lme4 warnings
-prop.table(table(df.exp2.infer.7.4$condition_disagree, df.exp2.infer.7.4$ambiguous_yes), margin=1)
prop.table(table(df.exp2.infer.7.4$condition_disagree, df.exp2.infer.7.4$ambiguous_yes),
+ margin = 1)
0 1
0 0.7500000 0.2500000
@@ -5125,85 +5134,84 @@ Prediction
df.age.means = df.plot.individual %>%
distinct(participant, age_continuous) %>%
- mutate(age_continuous = ifelse(age_continuous == 12, 11.99, age_continuous),
- age_group = floor(age_continuous)) %>%
- group_by(age_group) %>%
- summarize(age_mean = mean(age_continuous),
- n = str_c("n = ", n())) %>%
- ungroup()
-
-df.plot.means = df.exp2.predict %>%
- mutate(condition_amb = as.character(condition_amb)) %>%
- group_by(participant, age_group, condition_amb) %>%
- summarize(pct_dis = sum(dis_yes)/n()) %>%
- group_by(age_group, condition_amb) %>%
- reframe(response = smean.cl.boot(pct_dis),
- name = c("mean", "low", "high")) %>%
- left_join(df.age.means,
- by = "age_group") %>%
- pivot_wider(names_from = name,
- values_from = response) %>%
- mutate(age_mean = ifelse(condition_amb == 0, age_mean - 0.05, age_mean + 0.05))
-
-df.plot.text = df.plot.means %>%
- distinct(age_group, n)
+ mutate(age_group = floor(age_continuous)) %>%
+ group_by(age_group) %>%
+ summarize(age_mean = mean(age_continuous),
+ n = str_c("n = ", n())) %>%
+ ungroup()
+
+df.plot.means = df.exp2.predict %>%
+ mutate(condition_amb = as.character(condition_amb)) %>%
+ group_by(participant, age_group, condition_amb) %>%
+ summarize(pct_dis = sum(dis_yes)/n()) %>%
+ group_by(age_group, condition_amb) %>%
+ reframe(response = smean.cl.boot(pct_dis),
+ name = c("mean", "low", "high")) %>%
+ left_join(df.age.means,
+ by = "age_group") %>%
+ pivot_wider(names_from = name,
+ values_from = response) %>%
+ mutate(age_mean = ifelse(condition_amb == 0, age_mean - 0.05, age_mean + 0.05))
+
+df.plot.text = df.plot.means %>%
+ distinct(age_group, n)
+
-
-ggplot() +
- geom_hline(yintercept = 0.5,
- linetype = 2,
- alpha = 0.1) +
- geom_point(data = df.plot.individual,
- mapping = aes(x = age_continuous,
- y = pct_dis,
- color = condition_amb),
- alpha = 0.5,
- show.legend = T,
- shape = 16,
- size = 1.5) +
- geom_linerange(data = df.plot.means,
- mapping = aes(x = age_mean,
- y = mean,
- ymin = low,
- ymax = high),
- color = "gray40") +
- geom_point(data = df.plot.means,
- mapping = aes(x = age_mean,
- y = mean,
- fill = condition_amb),
- shape = 21,
- size = 3,
- show.legend = T) +
- geom_text(data = df.plot.text,
- mapping = aes(x = age_group + 0.5,
- y = 1.05,
- label = n),
- hjust = 0.5) +
- scale_y_continuous(labels = percent) +
- labs(x = "Age (in years)",
- y = "% Predict Disagreement",
- title = "Experiment 2: Prediction") +
- coord_cartesian(xlim = c(7, 12),
- ylim = c(0, 1),
- clip = "off") +
- scale_color_manual(name = "Trial Type",
- labels = c("Unambiguous", "Ambiguous"),
- values = c(l.color$unambiguous, l.color$ambiguous),
- guide = guide_legend(reverse = T)) +
- scale_fill_manual(name = "Trial Type",
- labels = c("Unambiguous", "Ambiguous"),
- values = c(l.color$unambiguous, l.color$ambiguous),
- guide = guide_legend(reverse = T)) +
- theme(plot.title = element_text(hjust = 0.5,
- vjust = 2,
- size = 18,
- face = "bold"),
- axis.title.y = element_markdown(color = l.color$disagreement),
- legend.position = "right")
-
-ggsave(filename = "../figures/plots/exp2_prediction.pdf",
- width = 8,
- height = 4)
+ggplot() +
+ geom_hline(yintercept = 0.5,
+ linetype = 2,
+ alpha = 0.1) +
+ geom_point(data = df.plot.individual,
+ mapping = aes(x = age_continuous,
+ y = pct_dis,
+ color = condition_amb),
+ alpha = 0.5,
+ show.legend = T,
+ shape = 16,
+ size = 1.5) +
+ geom_linerange(data = df.plot.means,
+ mapping = aes(x = age_mean,
+ y = mean,
+ ymin = low,
+ ymax = high),
+ color = "gray40") +
+ geom_point(data = df.plot.means,
+ mapping = aes(x = age_mean,
+ y = mean,
+ fill = condition_amb),
+ shape = 21,
+ size = 3,
+ show.legend = T) +
+ geom_text(data = df.plot.text,
+ mapping = aes(x = age_group + 0.5,
+ y = 1.05,
+ label = n),
+ hjust = 0.5) +
+ scale_y_continuous(labels = percent) +
+ labs(x = "Age (in years)",
+ y = "% Predict Disagreement",
+ title = "Experiment 2: Prediction") +
+ coord_cartesian(xlim = c(7, 12),
+ ylim = c(0, 1),
+ clip = "off") +
+ scale_color_manual(name = "Trial Type",
+ labels = c("Unambiguous", "Ambiguous"),
+ values = c(l.color$unambiguous, l.color$ambiguous),
+ guide = guide_legend(reverse = T)) +
+ scale_fill_manual(name = "Trial Type",
+ labels = c("Unambiguous", "Ambiguous"),
+ values = c(l.color$unambiguous, l.color$ambiguous),
+ guide = guide_legend(reverse = T)) +
+ theme(plot.title = element_text(hjust = 0.5,
+ vjust = 2,
+ size = 18,
+ face = "bold"),
+ axis.title.y = element_markdown(color = l.color$disagreement),
+ legend.position = "right")
+
+ggsave(filename = "../figures/plots/exp2_prediction.pdf",
+ width = 8,
+ height = 4)
@@ -5217,120 +5225,121 @@
Inference
df.age.means = df.plot.individual %>%
distinct(participant, age_continuous) %>%
-
mutate(age_continuous = ifelse(age_continuous == 12, 11.99, age_continuous),
-
age_group = floor(age_continuous)) %>%
-
group_by(age_group) %>%
-
summarize(age_mean = mean(age_continuous),
-
n = str_c("n = ", n())) %>%
-
ungroup()
-
-
df.plot.means = df.exp2.infer %>%
-
mutate(condition_disagree = as.character(condition_disagree)) %>%
-
group_by(participant, age_group, condition_disagree) %>%
-
summarize(pct_amb = sum(ambiguous_yes)/n()) %>%
-
group_by(age_group, condition_disagree) %>%
-
reframe(response = smean.cl.boot(pct_amb),
-
name = c("mean", "low", "high")) %>%
-
left_join(df.age.means,
-
by = "age_group") %>%
-
pivot_wider(names_from = name,
-
values_from = response) %>%
-
mutate(age_mean = ifelse(condition_disagree == 0, age_mean - 0.05, age_mean + 0.05))
-
-
df.plot.text = df.plot.means %>%
-
distinct(age_group, n)
-
-
df.model = df.model.posterior %>%
-
mutate(name = "posterior") %>%
-
select(-c(utterance, probability, prior)) %>%
-
bind_rows(df.model.softmax %>%
-
mutate(name = "softmax")) %>%
-
bind_rows(df.model.softmax.linear %>%
-
mutate(name = "softmax increase")) %>%
-
mutate(condition_disagree = factor(condition,
-
levels = c("Agreement Trials",
-
"Disagreement Trials"),
-
labels = c(0,
-
1))) %>%
-
left_join(df.age.means %>%
-
select(-n),
-
by = "age_group") %>%
-
mutate(age_mean = ifelse(condition_disagree == 0,
-
age_mean - 0.05,
-
age_mean + 0.05))
-
-
ggplot() +
-
geom_hline(yintercept = 0.5,
-
linetype = 2,
-
alpha = 0.1) +
-
geom_point(data = df.plot.individual,
-
mapping = aes(x = age_continuous,
-
y = pct_amb,
-
color = condition_disagree),
-
alpha = 0.5,
-
show.legend = T,
-
shape = 16,
-
size = 1.5) +
-
geom_linerange(data = df.plot.means,
-
mapping = aes(x = age_mean,
-
y = mean,
-
ymin = low,
-
ymax = high),
-
color = "gray40",
-
show.legend = F) +
-
geom_point(data = df.plot.means,
-
mapping = aes(x = age_mean,
-
y = mean,
-
fill = condition_disagree),
-
shape = 21,
-
size = 3,
-
show.legend = F) +
-
geom_point(data = df.model,
-
mapping = aes(x = age_mean,
-
y = posterior,
-
shape = name,
-
fill = condition_disagree),
-
size = 1.5,
-
alpha = 0.5,
-
show.legend = T) +
-
geom_text(data = df.plot.text,
-
mapping = aes(x = age_group + 0.5,
-
y = 1.05,
-
label = n),
-
hjust = 0.5) +
-
scale_y_continuous(labels = percent) +
-
labs(x = "Age (in years)",
-
y = "% Infer Ambiguous Utterance",
-
title = "Experiment 2: Inference") +
-
coord_cartesian(xlim = c(7, 12),
-
ylim = c(0, 1),
-
clip = "off") +
-
scale_color_manual(name = "Trial Type",
-
labels = c("Agreement", "Disagreement"),
-
values = c(l.color$agreement, l.color$disagreement)) +
-
scale_fill_manual(name = "Trial Type",
-
labels = c("Agreement", "Disagreement"),
-
values = c(l.color$agreement, l.color$disagreement)) +
-
scale_shape_manual(name = "Model",
-
labels = c("posterior", "softmax", "softmax increase"),
-
values = c(21, 22, 23)) +
-
theme(plot.title = element_text(hjust = 0.5,
-
vjust = 2,
-
size = 18,
-
face = "bold"),
-
axis.title.y = element_markdown(color = l.color$ambiguous),
-
legend.position = "right") +
-
guides(fill = guide_legend(override.aes = list(shape = 21,
-
size = 3),
+
mutate(age_group = floor(age_continuous)) %>%
+
group_by(age_group) %>%
+
summarize(age_mean = mean(age_continuous),
+
n = str_c("n = ", n())) %>%
+
ungroup()
+
+
df.plot.means = df.exp2.infer %>%
+
mutate(condition_disagree = as.character(condition_disagree)) %>%
+
group_by(participant, age_group, condition_disagree) %>%
+
summarize(pct_amb = sum(ambiguous_yes)/n()) %>%
+
group_by(age_group, condition_disagree) %>%
+
reframe(response = smean.cl.boot(pct_amb),
+
name = c("mean", "low", "high")) %>%
+
left_join(df.age.means,
+
by = "age_group") %>%
+
pivot_wider(names_from = name,
+
values_from = response) %>%
+
mutate(age_mean = ifelse(condition_disagree == 0, age_mean - 0.05, age_mean + 0.05))
+
+
df.plot.text = df.plot.means %>%
+
distinct(age_group, n)
+
+
df.model = df.model.posterior %>%
+
mutate(name = "posterior") %>%
+
select(-c(utterance, probability, prior)) %>%
+
bind_rows(df.model.softmax %>%
+
mutate(name = "softmax")) %>%
+
bind_rows(df.model.softmax.linear %>%
+
mutate(name = "softmax increase")) %>%
+
mutate(condition_disagree = factor(condition,
+
levels = c("Agreement Trials",
+
"Disagreement Trials"),
+
labels = c(0,
+
1))) %>%
+
left_join(df.age.means %>%
+
select(-n),
+
by = "age_group") %>%
+
mutate(age_mean = ifelse(condition_disagree == 0,
+
age_mean - 0.05,
+
age_mean + 0.05))
+
+
ggplot() +
+
geom_hline(yintercept = 0.5,
+
linetype = 2,
+
alpha = 0.1) +
+
geom_point(data = df.plot.individual,
+
mapping = aes(x = age_continuous,
+
y = pct_amb,
+
color = condition_disagree),
+
alpha = 0.5,
+
show.legend = T,
+
shape = 16,
+
size = 1.5) +
+
geom_linerange(data = df.plot.means,
+
mapping = aes(x = age_mean,
+
y = mean,
+
ymin = low,
+
ymax = high),
+
color = "gray40",
+
show.legend = F) +
+
geom_point(data = df.plot.means,
+
mapping = aes(x = age_mean,
+
y = mean,
+
fill = condition_disagree),
+
shape = 21,
+
size = 3,
+
show.legend = F) +
+
geom_point(data = df.model,
+
mapping = aes(x = age_mean,
+
y = posterior,
+
shape = name,
+
fill = condition_disagree),
+
size = 1.5,
+
alpha = 0.5,
+
show.legend = T) +
+
geom_text(data = df.plot.text,
+
mapping = aes(x = age_group + 0.5,
+
y = 1.05,
+
label = n),
+
hjust = 0.5) +
+
scale_y_continuous(labels = percent) +
+
labs(x = "Age (in years)",
+
y = "% Infer Ambiguous Utterance",
+
title = "Experiment 2: Inference") +
+
coord_cartesian(xlim = c(7, 12),
+
ylim = c(0, 1),
+
clip = "off") +
+
scale_color_manual(name = "Trial Type",
+
labels = c("Agreement", "Disagreement"),
+
values = c(l.color$agreement, l.color$disagreement)) +
+
scale_fill_manual(name = "Trial Type",
+
labels = c("Agreement", "Disagreement"),
+
values = c(l.color$agreement, l.color$disagreement)) +
+
scale_shape_manual(name = "Model",
+
labels = c("posterior", "softmax", "softmax increase"),
+
values = c(21, 22, 23)) +
+
theme(plot.title = element_text(hjust = 0.5,
+
vjust = 2,
+
size = 18,
+
face = "bold"),
+
axis.title.y = element_markdown(color = l.color$ambiguous),
+
legend.position = "right") +
+
guides(fill = guide_legend(override.aes = list(shape = 21,
+
size = 3,
+
alpha = 1),
reverse = T,
order = 1),
-
shape = guide_legend(override.aes = list(fill = "white", alpha = 1)),
-
color = "none")
-
-
ggsave(filename = "../figures/plots/exp2_inference.pdf",
-
width = 8,
-
height = 4)
+ shape = guide_legend(override.aes = list(fill = "white",
+ alpha = 1)),
+ color = "none")
+
+ggsave(filename = "../figures/plots/exp2_inference.pdf",
+ width = 8,
+ height = 4)
+
@@ -5343,7 +5352,7 @@ Session info
R version 4.3.2 (2023-10-31)
Platform: aarch64-apple-darwin20 (64-bit)
-Running under: macOS Sonoma 14.1.2
+Running under: macOS Sonoma 14.4.1
Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/lib/libRblas.0.dylib
diff --git a/figures/plots/exp1_inference.pdf b/figures/plots/exp1_inference.pdf
index 86c25a6..ebb343f 100644
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diff --git a/figures/plots/exp2_inference.pdf b/figures/plots/exp2_inference.pdf
index 9ba5e6a..51b4030 100644
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diff --git a/figures/plots/exp2_prediction.pdf b/figures/plots/exp2_prediction.pdf
index f8a87a1..c050df8 100644
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