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

*Corresponding author for this work

Research output: Contribution to journalReview Articlepeer-review

27 Citations (Scopus)

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
Article number0000454
Pages (from-to)558–579
Number of pages22
JournalPsychological Methods
Volume28
Issue number3
Early online date2022
DOIs
Publication statusPublished - 2023
MoE publication typeA2 Review article, Literature review, Systematic review

Keywords

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

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