chop_css: chop_css

In 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

multifear documentation built on Sept. 24, 2023, 1:06 a.m.