DSpace Repository

Testing for a Lack of Relationship Among Categorical Variables

Testing for a Lack of Relationship Among Categorical Variables

Show full item record

Title: Testing for a Lack of Relationship Among Categorical Variables
Author: Shishkina, Tanja
Farmus, Linda
Cribbie, Robert A.
Abstract: Determining a lack of association among two or more categorical variables is frequently necessary in psychological designs such as comparative outcome analyses, assessments of group equivalence at a baseline level, and therapy outcome evaluations. Despite this, the literature rarely offers information about, or technical recommendations concerning, the appropriate statistical methodology to be used to accomplish this task. This paper explores two equivalence tests for categorical variables, one introduced by Rogers, Howard, and Vessey (1993) and another by Wellek (2010), as well as a proposed strategy based on Cramer’s V. A simulation study was conducted to examine and compare the Type I error and power rates associated with these tests. The results indicate that an equivalence-based Cramer’s V procedure is the most appropriate method for determining a lack of relationship among categorical variables in two-way designs.
Sponsor: Social Sciences and Humanities Research Council
Subject: equivalence testing
categorical variables
frequency tables
Type: Article
URI: http://hdl.handle.net/10315/34630
Published: Open Access Scholarly Publishers Association
Citation: Shiskina, T., Farmus, L., & Cribbie, R. A. (in press). Testing for a lack of relationship among categorical variables. The Quantitative Methods for Psychology.
Date: 2018

Files in this item



This item appears in the following Collection(s)