Testing for a Lack of Relationship Among Categorical Variables

dc.contributor.authorShishkina, Tanja
dc.contributor.authorFarmus, Linda
dc.contributor.authorCribbie, Robert
dc.date.accessioned2018-06-06T02:42:17Z
dc.date.available2018-06-06T02:42:17Z
dc.date.issued2018
dc.description.abstractDetermining 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.en_US
dc.description.sponsorshipSocial Sciences and Humanities Research Council
dc.identifier.citationShiskina, T., Farmus, L., & Cribbie, R. A. (in press). Testing for a lack of relationship among categorical variables. The Quantitative Methods for Psychology.
dc.identifier.urihttp://hdl.handle.net/10315/34630
dc.language.isoenen_US
dc.publisherOpen Access Scholarly Publishers Associationen_US
dc.subjectequivalence testingen_US
dc.subjectcategorical variablesen_US
dc.subjectfrequency tablesen_US
dc.titleTesting for a Lack of Relationship Among Categorical Variables
dc.typeArticleen_US

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