setwd("/Dropbox/ContextProsodyAnalysis/")
setwd("~/Dropbox/ContextProsodyAnalysis/")
setwd("~/Dropbox/ContextProsodyAnalysis/draft/rating-study")
setwd("/Users/Kate/Documents/EMCL/thesis/norm-stim-v3/reresults")
subjects = read.csv("context-norm-subject-info.csv")
nums = subjects$subject.number[grepl('[d|D][e|E][u|U][t|T][s|S][c|C][h|H]',subjects$native.lang)&!duplicated(subjects$name)]
results = read.csv("context-norm.csv")
results$item = as.factor(as.character(results$item))
results = results[results$subj%in%nums,]
results = results[results$RT<3*sd(results$RT),]
results$c.t.cond = interaction(results$context.condition,results$item.condition)
results$c.t.cond = factor(results$c.t.cond, levels=c("CA.C", "CC.C", "T.T",  "CA.T", "CC.T", "T.C"))
results$match = ifelse(results$c.t.cond=="CC.C"|results$c.t.cond=="CA.C"|results$c.t.cond=="T.T",1,0)
tapply(results$response,results$c.t.cond,mean)
summary(results)
results$match.contr = ifelse(results$match==1,1,-1)
results$item.contr = ifelse(results$item.condition=="T",1,-1)
length(results)
results = results[results$context.condition!="CC",]
results$context.condition = results$context.condition[,drop=TRUE]
results$c.t.cond = results$c.t.cond[,drop=TRUE]
summary(results)
setwd("~/Dropbox/ContextProsodyAnalysis/draft/rating-study")
save("ratings-processed.rda")
save(results, "ratings-processed.rda")
save(results, file="ratings-processed.rda")
with(results, tapply(response,interaction(context.condition,match),mean))
results = results[results$RT<3*sd(results$RT),]
summary(results)
summary(results[results$item.contr==-1,])
item.count = length(unique(results$item))
match.advantage = vector(length=item.count)
for (i in 1:item.count){
match.advantage[i] = mean(results$response[results$item==i&results$match==0) - mean(results$response[results$item==i&results$match==1])
}
item.count = length(unique(results$item))
match.advantage = vector(length=item.count)
for (i in 1:item.count){
match.advantage[i] = mean(results$response[results$item==i&results$match==0]) - mean(results$response[results$item==i&results$match==1])
}
median(match.advantage)
match.med = median(match.advantage)
test.items = c(1:36)[match.advantage>match.med]
test.items
(response = lmer(response ~ match*item.condition + (1|subj) + (1|item),results[results$context.condition!="CC",]))
library(lme4)
(response = lmer(response ~ match*item.condition + (1|subj) + (1|item),results[results$context.condition!="CC",]))
(response = lmer(response ~ match.contr*item.contr + (1|subj) + (1|item),results[results$context.condition!="CC",]))
boxplot(response ~ match, results[results$context.condition!="CC"&results$item.condition=="C",], at=0:1+1,xlim=c(0,6),ylim=range(results$response),xaxt="n",col=c("white","gray80"),xlab="Disambiguation",main="Ratings")
boxplot(response ~ match, results[results$context.condition!="CC"&results$item.condition=="T",], at=0:1+4,xaxt="n",col=c("white","gray80"),add=T)
axis(1, at = c(1.5,4.5), labels = c("comparative","temporal"), tick = TRUE)
legend(2.3,6.5,c("consistent","inconsistent"),fill=c("gray80","white"),title="Context")
boxplot(response ~ match, results[results$item.condition=="C",], at=0:1+1,xlim=c(0,6),ylim=range(results$response),xaxt="n",col=c("white","gray80"),xlab="Disambiguation",main="Ratings")
boxplot(response ~ match, results[results$item.condition=="T",], at=0:1+4,xaxt="n",col=c("white","gray80"),add=T)
axis(1, at = c(1.5,4.5), labels = c("comparative","temporal"), tick = TRUE)
legend(2.3,6.5,c("consistent","inconsistent"),fill=c("gray80","white"),title="Context")
