logratio: Log Ratio Analysis for the Implicit Association Test (IAT)

In intervcomp: Hypothesis Testing Using the Overlapping Interval Estimates

Description

Log ratio analysis for the IAT.

Usage

logratio(rt, subject, block_type, trial_num, group,
  block_order = c("original", "reverse"), min_limit = 400,
  max_limit = 10000, rt_min = 200, correctvec = NULL,
  trace = FALSE)

Arguments

rt	A vector specifying all the reaction times.
subject	A vector specifying the subject IDs for the rt vector.
block_type	A vector specifying the block type for the rt vector. There should be two blocks.
trial_num	A vector specifying the trial number for each observation in the rt vector.
group	A data frame with two columns specifying the subject IDs and corresponding group. There should be two groups.
block_order	A character string specifying the order of the two groups. There are two options: "original" puts the first group in the numerator of the ratio, and "reverse" puts the second group in the numerator of the ratio.
min_limit	A numeric specifying the lower limit for the reaction times to be included. The default option is 400.
max_limit	A numeric specifying the upper limit for the reaction times to be included. The default option is 10000.
rt_min	A numeric specifying the minimum time required for reaction. The default option is 200.
correctvec	A vector specifying whether or not the response is correct (0 for incorrect, 1 for correct). The default option is NULL, in which case, all the responses are assumed to be correct.
trace	A boolean specifying whether or not the progress should be displayed on the screen. The default option is FALSE.

Value

scores

A list containing the IAT scores using the log ratio analysis.

Examples

data(reactiontimes)
data(grouping)
rt <- reactiontimes$rt
subject <- reactiontimes$subId
block_type <- reactiontimes$block_type
trial_num <- reactiontimes$trial_num
block_order <- "reverse"

results <- logratio(rt=rt, subject=subject, block_type=block_type, trial_num=trial_num,
group=grouping, block_order=block_order, trace=TRUE)
femaleRatioLog<-results$`0`
maleRatioLog<-results$`1`
two.sample.var(femaleRatioLog,maleRatioLog,alternative="two.sided",
scale.option="Levene.Med.0",scale.adj=TRUE,paired=FALSE)
Bonett.Seier.test(femaleRatioLog,maleRatioLog,alternative="two.sided")

intervcomp documentation built on July 12, 2019, 5:04 p.m.