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Default "Gunel and Dickey" Bayes factors for contingency tables

Jamil, Tahira, Ly, Alexander, Morey, Richard D. ORCID:, Love, Jonathon, Marsman, Maarten and Wagenmakers, Eric-Jan 2017. Default "Gunel and Dickey" Bayes factors for contingency tables. Behavior Research Methods 49 (2) , pp. 638-652. 10.3758/s13428-016-0739-8

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The analysis of R×C contingency tables usually features a test for independence between row and column counts. Throughout the social sciences, the adequacy of the independence hypothesis is generally evaluated by the outcome of a classical p-value null-hypothesis significance test. Unfortunately, however, the classical p-value comes with a number of well-documented drawbacks. Here we outline an alternative, Bayes factor method to quantify the evidence for and against the hypothesis of independence in R×C contingency tables. First we describe different sampling models for contingency tables and provide the corresponding default Bayes factors as originally developed by Gunel and Dickey (Biometrika, 61(3):545–557 (1974)). We then illustrate the properties and advantages of a Bayes factor analysis of contingency tables through simulations and practical examples. Computer code is available online and has been incorporated in the “BayesFactor” R package and the JASP program (

Item Type: Article
Date Type: Publication
Status: Published
Schools: Psychology
Subjects: B Philosophy. Psychology. Religion > BF Psychology
Uncontrolled Keywords: Bayes factors; Contingency table; Sampling models; p-value
Publisher: Springer
ISSN: 1554-3528
Date of First Compliant Deposit: 21 July 2017
Date of Acceptance: 13 April 2016
Last Modified: 02 Nov 2022 11:41

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