Nothing
Pretreatment <- function(IATdata,
label_subject = "subject",
label_latency = "latency",
label_accuracy = "correct",
label_block = "blockcode",
block_pair1 = c("pair1_left", "pair1_right"),
block_pair2 = c("pair2_left", "pair2_right"),
label_trial = NA,
trial_left = NA,
trial_right = NA,
label_praccrit = NA,
block_prac = NA,
block_crit = NA,
label_stimulus = NA)
{
# determine which optional columns are desired
trials <- !any(is.na(c(label_trial, trial_left, trial_right)))
praccrit <- !any(is.na(c(label_praccrit, block_prac, block_crit)))
stimuli <- !is.na(label_stimulus)
#IAT1: subset of IATdata, only the relevant columns are kept, a subset
# of these: 1)subject, 2)latency, 3)accuracy, 4)block label, 5)trial label,
# 6) praccrit, 7) stimulus
cols <- c(label_subject, label_latency, label_accuracy, label_block)
# columns 5, 6, and 7 are optional
if(trials) cols <- c(cols, label_trial)
if(stimuli) cols <- c(cols, label_stimulus)
if(praccrit) cols <- c(cols, label_praccrit)
IAT1 <- IATdata[,cols]
rm(IATdata)
# Keep only critical blocks
IAT1 <- subset(IAT1, (IAT1[,label_block]%in%c(block_pair1, block_pair2)))
# Convert block names to simpler labels
IAT2 <- data.frame(matrix(ncol=0, nrow=nrow(IAT1)))
IAT2$subject <- IAT1[,label_subject]
IAT2$latency <- IAT1[,label_latency]
IAT2$correct <- IAT1[, label_accuracy]
IAT2[IAT1[,label_block] %in% block_pair1, "blockcode"] <- "pair1"
IAT2[IAT1[,label_block] %in% block_pair2, "blockcode"] <- "pair2"
IAT2$blockcode <- as.factor(IAT2$blockcode)
# optional: if trial codes are specified, convert them to simpler labels
if(trials)
{
IAT2[IAT1[,label_trial] %in% trial_right, "trialcode"] <- "right"
IAT2[IAT1[,label_trial] %in% trial_left, "trialcode"] <- "left"
IAT2$trialcode<-as.factor(IAT2$trialcode)
}
# optional: if practice / critical double categorization blocks must be
# distinguished, convert them to simpler labels
if(praccrit)
{
IAT2[IAT1[,label_praccrit] %in% block_prac,"praccrit"] <- "prac"
IAT2[IAT1[,label_praccrit] %in% block_crit,"praccrit"] <- "crit"
IAT2[IAT2$blockcode=="practice","praccrit"] <- "null"
IAT2$praccrit<-as.factor(IAT2$praccrit)
}
# optional: do you want to keep the stimuli column?
if(stimuli)
IAT2$stimulus <- str_trim(IAT1[,label_stimulus])
# clean the NA rows, if any
IAT2 <- remove.na.rows(IAT2)
# values that are not allowed are removed
# e.g., (negative latencies, correct != 0 or 1)
IAT2 <- IAT2 [IAT2$latency >= 0 & IAT2$correct %in% c(0,1), ]
IAT2
}
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