chop_cs

Function for separating the conditioned responses into multiple pieces

A suite of functions for performing analyses, based on a multiverse approach, for conditioning data. Specifically, given the appropriate data, the functions are able to perform t-tests, analyses of variance, and mixed models for the provided data and return summary statistics and plots. The function is also able to return for all those tests p-values, confidence intervals, and Bayes factors. The methods are described in Lonsdorf, Gerlicher, Klingelhofer-Jens, & Krypotos (2022) <doi:10.1016/j.brat.2022.104072>. Since November 2025, this package contains code from the 'ez' R package (Copyright (c) 2016-11-01, Michael A. Lawrence <mike.lwrnc@gmail.com>), originally distributed under the 'GPL' (equal and above 2) license.

Angelos-Miltiadis Krypotos

multifear

Multiverse Analyses for Conditioning Data

chop_cs function

<dl><dt>cs</dt>
<dd>The column name(s) of the conditioned responses</dd>
<dt>data</dt>
<dd>A data frame containing all the relevant columns for the analyses</dd>
<dt>subj</dt>
<dd>The name of the column including the participant numbers. Unique numbers are expected</dd>
<dt>group</dt>
<dd>default to <code>NULL</code></dd>
<dt>prefix</dt>
<dd>prefix to be included in the end data frame</dd>
<dt>na.rm</dt>
<dd>Whether NAs should be removed, default to <code>FALSE</code></dd></dl>

Arguments

chop_cs — chop_cs

<dl>

<dt>cs</dt>
<dd>The column name(s) of the conditioned responses</dd>


<dt>data</dt>
<dd>A data frame containing all the relevant columns for the analyses</dd>


<dt>subj</dt>
<dd>The name of the column including the participant numbers. Unique numbers are expected</dd>


<dt>group</dt>
<dd>default to <code>NULL</code></dd>


<dt>prefix</dt>
<dd>prefix to be included in the end data frame</dd>


<dt>na.rm</dt>
<dd>Whether NAs should be removed, default to <code>FALSE</code></dd>

</dl>

chop_cs: chop_cs

Description

Usage

Value

Arguments

Examples