library(plyr) library(dplyr) library(MPDiR) library(quickpsy) library(fitdistrplus) library(ggplot2) library(rstudioapi) defaultpath <- dirname(rstudioapi::getActiveDocumentContext()$path) setwd(defaultpath) file <-"user_answers_ms.csv" if (exists ("aggregated_data")) { rm(aggregated_data) } dataFile <- read.csv(file, stringsAsFactors=FALSE) # collect all trials in order to calculate average error rate and time per question per participant, keep non training trials (isTraining = "False") tmp <- dataFile tmp <- dataFile [ which (dataFile$is_training == "False"),] # keep trials that are not training # FIX: I GET AN ERROR HERE, ALTHOUGH IT WORKS tmp$error <- tmp$is_correct tmp$error[tmp$is_correct == "False"] <- 1 tmp$error[tmp$is_correct == "True"] <- 0 tmp$error <- as.numeric(as.character(tmp$error)) aggregated_table <- ddply(tmp, c("user","vis", "question_code", "question_internal_id" ), summarise, mean_error = mean(error)*100, # turn [0,1] values to percentages mean_time = mean(time) / 1000, # turn milliseconds to seconds mean_confidence = mean(confidence) ) write.csv(aggregated_table, file="aggregated_data.csv")