trimr (version 1.0.1)

sdTrim: RT trimming with standard deviation criterion

Description

sdTrim takes a data frame of RT data and returns trimmed rt data that fall below a set set criterion (based on standard deviations above a particular mean). The criterion can be based on the mean of the whole set of data, based on the mean per experimental condition, based on the mean per participant, or based on the mean of each participant in each experimental condition.

Usage

sdTrim(data, minRT, sd, perCondition = TRUE, perParticipant = TRUE,
  omitErrors = TRUE, returnType = "mean", digits = 3)

Arguments

data

A data frame. It must contain columns named "participant", "condition", "rt", and "accuracy". The RT can be in seconds (e.g., 0.654) or milliseconds (e.g., 654). Condition will consist of strings. "accuracy" must be 1 for correct and 0 for error responses.

minRT

The lower criteria for acceptable response time. Must be in the same form as rt column in data frame (e.g., in seconds OR milliseconds). All RTs below this value are removed before proceeding with SD trimming.

sd

The upper criteria for standard deviation cut-off.

perCondition

Set to TRUE if the user wishes the trimming to occur per condition of the experimental design.

perParticipant

Set to TRUE if the user wishes the trimming to occur per participant.

omitErrors

If set to TRUE, error trials will be removed before conducting trimming procedure. Final data returned will not be influenced by errors in this case.

returnType

Request nature of returned data. "raw" returns trial- level data excluding trimmed data; "mean" returns mean response times per participant for each experimental condition identified; "median" returns median response times per participant for each experimental condition identified.

digits

How many decimal places to round to after trimming?

Details

By passing a data frame containing raw response time data, together with trimming criteria, the function will return trimmed data, either in the form of trial-level data or in the form of means/medians for each subject & condition.

Examples

# NOT RUN {
# load the example data that ships with trimr
data(exampleData)

# perform the trimming with SD trimming per condition, returning mean RT
trimmedData <- sdTrim(data = exampleData, minRT = 150, sd = 2.5,
perCondition = TRUE, perParticipant = FALSE, returnType = "mean")
# }