Testing for a Lack of Relationship Among Categorical Variables

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Date

2018

Authors

Shishkina, Tanja
Farmus, Linda
Cribbie, Robert

Journal Title

Journal ISSN

Volume Title

Publisher

Open Access Scholarly Publishers Association

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.

Description

Keywords

equivalence testing, categorical variables, frequency tables

Citation

Shiskina, T., Farmus, L., & Cribbie, R. A. (in press). Testing for a lack of relationship among categorical variables. The Quantitative Methods for Psychology.