top banner top banner

Search publications

Testing for a lack of relationship among categorical variables

Full text PDF
Bibliographic information: BibTEX format RIS format XML format APA style
Cited references information: BibTEX format APA style
Doi: 10.20982/tqmp.14.3.p167

Shishkina, Tanja , Farmus, Linda , Cribbie, Robert A.
Keywords: equivalence testing , categorical variables , frequency tables
(no sample data)   (no appendix)

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 \textcite {rhv93} and another by \textcite {w10}, as well as a proposed strategy based on Cramèr's $V$ (\citeyear {c46}). 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 Cramèr's $V$ procedure is the most appropriate method for determining a lack of relationship among categorical variables in two-way designs.

Pages © TQMP;
Template last modified: 2018-10-16.
Page consulted on .
Be informed of the upcoming issues with RSS feed: RSS icon RSS