diff --git a/iat-analysis.R b/iat-analysis.R index 901cb5ca9377c59aca563148616d2ca1995c8502..1ebae64d16eb15f7ae54a3c27de54e070d48a162 100755 --- a/iat-analysis.R +++ b/iat-analysis.R @@ -91,6 +91,55 @@ data %>% geom_density(aes(x= reactionTime, color=trial), size =1.5) + ggsave("per-trial-reaction-times.pdf") +alldata <- read.table("alldata-expe-lem.csv", + sep=",", + dec= ".", + header = T) %>% + tbl_df() + +iat_scores <- alldata %>% + filter(reactionTime < 3000) %>% + filter(reactionTime > 300) %>% + filter(trial == 4 | (trial ==6)) %>% + group_by(id) %>% + mutate(full.sd = sd(reactionTime)) %>% + group_by(id, trial, full.sd) %>% + summarise(mRT = mean(reactionTime), sdRT = sd(reactionTime)) %>% + gather(variable,value, -id, -full.sd, -trial) %>% + unite(block, trial, variable) %>% + spread(block,value, sep = "") %>% + mutate(d = round((block6_mRT - block4_mRT) / full.sd, digits=5)) + +alldata %>% + filter(reactionTime < 3000) %>% + filter(reactionTime > 300) %>% + filter(trial == 4 | (trial ==6)) %>% + mutate(category = recode_factor(category, + "A"= "Appropriation", + "P"= "Partage", + "1"= "Moi", + "2"= "PasMoi")) %>% + mutate(trial=as.factor(trial)) %>% + left_join(iat_scores, by='id') %>% + mutate(lab = paste0("id: ", as.numeric(as.factor(id)),"(d=",d,")")) %>% + ggplot() + + geom_histogram(aes(x= reactionTime, fill=trial), position = "dodge") + + facet_wrap(~lab, scales ="free_x") + + ggsave("per-trial-reaction-times-alldata.pdf", + height = 21, + width = 29.7, + units = "cm") + +iat_scores %>% + arrange(d) %>% + mutate(lab = paste0(as.numeric(as.factor(id)))) %>% + ggplot() + + geom_bar(aes(x=lab, y=d), stat="identity") + + ggsave("scores-alldata.pdf", + height = 21 / 2, + width = 29.7 /2, + units = "cm") + items <- list(c("compétition", "gain", "profit", diff --git a/organise-iat-data.R b/organise-iat-data.R index ae5c0a667e1f4cceb15dba10e8cd49e5d7909c3c..9fafb022a8abb56f84dfedc3f7d9681a1330b5bd 100644 --- a/organise-iat-data.R +++ b/organise-iat-data.R @@ -86,19 +86,3 @@ setwd(paste(base.dir,"data",sep="")) write.csv(alldata, paste0("alldata-", expe.name,".csv"), row.names = F) - -alldata %>% - filter(reactionTime < 2000) %>% - mutate(category = recode_factor(category, - "A"= "Appropriation", - "P"= "Partage", - "1"= "Moi", - "2"= "PasMoi")) %>% - mutate(trial=as.factor(trial)) %>% - ggplot() + - geom_density(aes(x= reactionTime, color=trial), size =1.5) + - facet_wrap(~id, scales ="free_x") + - ggsave("per-trial-reaction-times-alldata.pdf") - -summarized %>% tbl_df() -