XTmem1
Molly Lewis
2016-12-06
Replication of Xu and Tenenbaum 2007a, Experiment 1. N = 50 participants (original: N = 22).
Read in raw data and anonymize
files = dir("../production-results/")
d = data.frame()
for (i in 1:length(files)[1]) {
s <- fromJSON(paste("../production-results/", files[i], sep = ""))
s$answers$asses = ifelse (is.null(s$answers$asses), "NA", s$answers$asses)
d = rbind(d, data.frame(s))
}
names(d) <- str_replace(names(d), "answers.", "")
d.anonymized <- anonymize.sids(d, "WorkerId")
write.csv(d.anonymized, "exp1_A.csv")Munge
d = read.csv("exp1_A.csv")
d.long = d %>%
gather(variable, value, contains("_")) %>%
mutate(trial_num = unlist(lapply(strsplit(as.character(variable),
"_T"),function(x) x[2])),
variable = unlist(lapply(strsplit(as.character(variable),
"_"),function(x) x[1]))) %>%
spread(variable, value) %>%
mutate(trial_num = as.numeric(trial_num)) %>%
mutate_if(is.character, funs(as.factor))
d.munged = d.long %>%
select(subids, trial_num, category, condition, selected) %>%
mutate(selected = lapply(str_split(selected, ","),
function(x) {str_sub(x, 4, 6)})) %>%
mutate(prop_sub = lapply(selected, function(x){sum(x == "sub")/2}),
prop_bas = lapply(selected, function(x){sum(x == "bas")/2}),
prop_sup = lapply(selected, function(x){sum(x == "sup")/4})) %>%
select(-selected)Reproduce XT2007a Figure 5.
ms = d.munged %>%
gather(variable, value, c(prop_sub, prop_bas, prop_sup)) %>%
group_by(condition,variable) %>%
mutate(value = as.numeric(value)) %>%
multi_boot_standard(column = "value") %>%
mutate(variable = as.factor(variable))
ms$variable = factor(ms$variable,levels(ms$variable)[c(2,1,3)])
ms$condition = factor(ms$condition,levels(ms$condition)[c(1,3,2,4)])
ms$condition = plyr::mapvalues(ms$condition,
from = c("one", "three_basic",
"three_subordinate",
"three_superordinate"),
to = c("1", "3 basic", "3 sub.", "3 super."))
ggplot(ms, aes(x = condition, y = mean, group = variable, fill = variable)) +
geom_bar(position = "dodge", stat = "identity") +
geom_linerange(aes(ymin = ci_lower,
ymax = ci_upper),
position=position_dodge(width = .9)) +
ylab("Proportion of \ntest objects chosen") +
xlab("Examples") +
theme_bw() +
theme(legend.title = element_blank())
XT 2007a, Figure 5 (for reference)
By category
ms = d.munged %>%
gather(variable, value, c(prop_sub, prop_bas, prop_sup)) %>%
mutate(variable = as.factor(variable)) %>%
group_by(condition,variable,category) %>%
mutate(value = as.numeric(value)) %>%
multi_boot_standard(column = "value")
ms$variable = factor(ms$variable,levels(ms$variable)[c(2,1,3)])
ms$condition = factor(ms$condition,levels(ms$condition)[c(1,3,2,4)])
ms$condition = plyr::mapvalues(ms$condition,
from = c("one", "three_basic",
"three_subordinate", "three_superordinate"),
to = c("1", "3 basic", "3 sub.", "3 super."))
ggplot(ms, aes(x = condition, y = mean, group = variable, fill = variable)) +
facet_grid(~category) +
geom_bar(position = "dodge", stat = "identity") +
geom_linerange(aes(ymin = ci_lower,
ymax = ci_upper),
position=position_dodge(width = .9)) +
ylab("Proportion of \ntest objects chosen") +
xlab("Examples") +
theme_bw() +
theme(legend.title = element_blank())
Post-task questions
d %>%
group_by(education) %>%
summarise(n = n()) %>%
kable()| education | n |
|---|---|
| 0 | 1 |
| 1 | 6 |
| 2 | 14 |
| 3 | 27 |
| 4 | 2 |
d %>%
group_by(enjoyment) %>%
summarise(n = n()) %>%
kable()| enjoyment | n |
|---|---|
| 1 | 16 |
| 2 | 34 |
d %>%
mutate(language = tolower(language)) %>%
group_by(language) %>%
summarise(n = n()) %>%
kable()| language | n |
|---|---|
| english | 49 |
| italian | 1 |
d %>%
group_by(gender) %>%
summarise(n = n()) %>%
kable()| gender | n |
|---|---|
| 22 | |
| Female | 13 |
| Male | 15 |
d %>%
group_by(asses) %>%
summarise(n = n()) %>%
kable()| asses | n |
|---|---|
| Confused | 1 |
| No | 1 |
| Yes | 26 |
| NA | 22 |
d %>%
mutate(age = as.numeric(as.character(age))) %>%
ggplot(aes(x= age)) +
geom_histogram() +
theme_bw() +
ggtitle("Age distribution")
unique(d$comments)## [1]
## [2] It was interesting and I will probably wonder if I did it correctly or not. I don't think I did in the beginning.
## [3] It has been funny, I hope I understood correctly what I had to do
## [4] None
## [5] Thanks!
## [6] I had no clue what was happening... At one point it didn't tell me what to even do. Just had blank images, then it had school buses and jalapeno images. I have no idea what just happened...
## [7] quite confusing.
## [8] Not enough attention to cats, ha ha!
## [9] Thank you!
## [10] None thanks
## [11] Thanks!
## [12] Mr Frog is a demanding little guy.
## [13] Thank You
## [14] Enjoyed the hit, it was a fun challenge.
## [15] Thanks for letting me participate!
## [16] Thank you for the study it was fun : )
## [17] ty
## 17 Levels: ... ty