A review of applications of the Bayes factor in psychological research

Daniel W. Heck, Udo Boehm, Florian Böing-Messing, P Bürkner, K Derks, Z Dienes, Q Fu, X Gu, Diana Karimova, H Kiers, I Klugkist, R. M. Kuiper, M.D. Lee, Roger Leenders, H.J. Leplaa, M Linde, A Ly, Marlyne Meijerink, M. Moerbeek, Joris MulderB Palfi, F Schönbrodt, J Tendeiro, D van den Bergh, C.J. van Lissa, D van Ravenzwaaij, W Vanpaemel, E Wagenmakers, D.R. Williams, M Zondervan-Zwijnenburg, H. Hoijtink

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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 paper is concluded with a discussion of the opportunities and pitfalls of Bayes factor applications and a sketch of corresponding future research lines.
Original languageEnglish
JournalPsychological Methods
Publication statusE-pub ahead of print - 2022

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