A review of applications of the Bayes factor in psychological research

Daniel W Heck, Udo Boehm, Florian Böing-Messing, Paul-Christian Bürkner, Koen Derks, Zoltan Dienes, Qianrao Fu, Xin Gu, Diana Karimova, Henk A L Kiers, Irene Klugkist, Rebecca M Kuiper, Michael D Lee, Roger Leenders, Hidde J Leplaa, Maximilian Linde, Alexander Ly, Marlyne Meijerink-Bosman, Mirjam Moerbeek, Joris MulderBence Palfi, Felix D Schönbrodt, Jorge N Tendeiro, Don van den Bergh, Caspar J Van Lissa, Don van Ravenzwaaij, Wolf Vanpaemel, Eric-Jan Wagenmakers, Donald R Williams, Mariëlle Zondervan-Zwijnenburg, Herbert Hoijtink

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

The last 25 years have shown a steady increase in attention for the Bayes factor as a tool for hypothesis evaluation and model selection. The present review highlights the potential of the Bayes factor in psychological research. We discuss six types of applications: Bayesian evaluation of point null, interval, and informative hypotheses, Bayesian evidence synthesis, Bayesian variable selection and model averaging, and Bayesian evaluation of cognitive models. We elaborate what each application entails, give illustrative examples, and provide an overview of key references and software with links to other applications. The article is concluded with a discussion of the opportunities and pitfalls of Bayes factor applications and a sketch of corresponding future research lines.

Original languageEnglish
Pages (from-to)558-579
Number of pages22
JournalPsychological Methods
Volume28
Issue number3
Early online date17 Mar 2022
DOIs
Publication statusPublished - 17 Mar 2022

Keywords

  • Bayes factor
  • Evidence
  • Hypothesis testing
  • Model selection
  • Theory evaluation

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