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A Bayes Factor for Replications of ANOVA Results

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  • Christopher Harms

Abstract

With an increasing number of replication studies performed in psychological science, the question of how to evaluate the outcome of a replication attempt deserves careful consideration. Bayesian approaches allow to incorporate uncertainty and prior information into the analysis of the replication attempt by their design. The Replication Bayes factor, introduced by Verhagen and Wagenmakers (2014), provides quantitative, relative evidence in favor or against a successful replication. In previous work by Verhagen and Wagenmakers (2014), it was limited to the case of t-tests. In this article, the Replication Bayes factor is extended to F-tests in multigroup, fixed-effect ANOVA designs. Simulations and examples are presented to facilitate the understanding and to demonstrate the usefulness of this approach. Finally, the Replication Bayes factor is compared to other Bayesian and frequentist approaches and discussed in the context of replication attempts. R code to calculate Replication Bayes factors and to reproduce the examples in the article is available at https://osf.io/jv39h/.

Suggested Citation

  • Christopher Harms, 2019. "A Bayes Factor for Replications of ANOVA Results," The American Statistician, Taylor & Francis Journals, vol. 73(4), pages 327-339, October.
    • Handle: RePEc:taf:amstat:v:73:y:2019:i:4:p:327-339
    DOI: 10.1080/00031305.2018.1518787
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    Cited by:

    1. Samuel Pawel & Leonhard Held, 2022. "The sceptical Bayes factor for the assessment of replication success," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(3), pages 879-911, July.

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