#Change to your own directory (where you keep the data file)
dir = 'C:\\Users\\yoav\\Documents\\bigfiles\\qualtrics.iat\\gal.elinor\\raw'
# Copied from Elad Zlotnick (from here: https://github.com/eladzlot/minnojs-qiat/blob/master/qiat.R)
# Parse csv generated by minnoJS
#
# @param df a data frame
# @param id the column name holding the ids
# @param data the column name holding the data (we assume the data holds an array of unnested objects)
#
# @example
# qiat.parse.quoted(df, 'ResponseId', 'Q_47')
# qiat.parse(df, ResponseId, Q_47)
#
# @returns data frame with parsed data, rows with NA or '' are omitted.
qiat.parse.quoted = function(df, id, data){
# @TODO does not work?
# if (is.factor(df[id])) stop(paste0(data, ' column must not be a factor'))
filteredDF = df[df[,data]!='' & !is.na(df[,data]) ,]
# parse data -> list of data data frames
csvList = lapply(filteredDF[,data], function(str) tryCatch({
read.csv(text=str,stringsAsFactors = FALSE)
},
error = function(err){
message('woa there is a malformed csv here')
return(NA)
}
))
#browser()
# add id to each data DF
mask = which(sapply(csvList,nrow)>0)
dataPages = mapply(
function(id, df) cbind(id,df),
filteredDF[mask,id],
csvList[mask],
SIMPLIFY = FALSE
)
if (!length(dataPages)) { return(data.frame()) }
# concat pages
do.call(rbind,dataPages)
}
qiat.parse = function(df, id, data){
qiat.parse.quoted(df, deparse(substitute(id)), deparse(substitute(data)))
}
df = read.csv(paste(dir, 'examplePriming-update.csv',sep = '\\'))
df <- df[which(grepl('block', df$Q2)),]
library(kutils)
df$ep <- mgsub(df$Q2, pattern = c('""'), replacement = c('"'))
df2 <- qiat.parse.quoted(df = df, id='ResponseId', data = 'ep')
nrow(df2)
names(df2)
table(df2$block, exclude=NULL)
table(df2$cond, exclude=NULL)
df2$prime <- ifelse(grepl('Black', df2$cond), 'black',
ifelse(grepl('White', df2$cond), 'white', NA))
table(df2$prime)
df2$target <- ifelse(grepl('Unpleasant', df2$cond), 'bad',
ifelse(grepl('Pleasant', df2$cond), 'good', NA))
table(df2$target)
df2.correct <- df2[which(df2$err==0),]
library(doBy)
ep.means <- summaryBy(formula = rt ~ id + prime + target, data = df2.correct)
summaryBy(formula = rt.mean ~ prime + target, data = ep.means, FUN = c(mean, sd, median))