chop_css: chop_css

In AngelosPsy/multifear: Multiverse Analyses for Conditioning Data

chop_css

Description

Function for separating the conditioned responses into multiple pieces for two CSs.

Usage

chop_css(cs1, cs2, data, subj, cs_paired = NULL, group = NULL, na.rm = FALSE)

Arguments

cs1	The column name(s) of the conditioned responses for the first conditioned stimulus
cs2	The column name(s) of the conditioned responses for the second conditioned stimulus
data	A data frame containing all the relevant columns for the analyses
subj	The name of the column including the participant numbers. Unique numbers are expected
cs_paired	A character vector with the trials that were paired. Default is set to NULL, suggesting that there was full reinforcement @return A tibble with the following column names – separately forr cs1 and cs2: "id" = id column; "top10per" = mean of top 10 "bottom10per" = mean of bottom 10 "minfirst = all trials minus the first one; "all" = mean of all trials; "t33per = mean of top 33 "m33per" = mean of medium 33 "b33per" = mean of bottom 33 "fhalf" = mean of first half of the trials; "lhalf" = mean of last half of the trials; "ftrial" = first trial; "ltrial" = last trial; "t20per" = mean of top 20 "b20per" = mean of bottom 20 "f2trial" = mean of first two trials; "l2trial" = mean of last two trials; "per2_X" = mean per two trials (i.e., block), with X referring to the number of block.
group	the name of the group, if included, default to NULL
na.rm	Whether NAs should be removed, default to FALSE

AngelosPsy/multifear documentation built on Oct. 1, 2023, 2:07 p.m.