What is a Bayes factor?
Open accessAbstract
The use of Bayes factors is becoming increasingly common in psychological sciences. Thus, it is important that researchers understand the logic behind the Bayes factor in order to correctly interpret it, and the strengths of weaknesses of the Bayesian approach. As education for psychological scientists focuses on frequentist statistics, resources are needed for researchers and students who want to learn more about this alternative approach. The aim of the current article is to provide such an overview to a psychological researcher. We cover the general logic behind Bayesian statistics, explain how the Bayes factor is calculated, how to set the priors in popular software packages to reflect the prior beliefs of the researcher, and finally provide a set of recommendations and caveats for interpreting Bayes factors. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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Across the models, Bayes factors indicated either strong support of the null hypothesis or equivocal support, and none approached the threshold for even anecdotal evidence for iatrogenic effects (BF > 1).
“Across the models, BFs indicated either strong support of the null hypothesis (eg, models testing screen completion at 1 month/week predicting positive screens at the next month/week) or equivocal support (eg, models predicting increases in positive screens across the study).34 Notably, none of the models approached the threshold for what would be considered even anecdotal evidence for iatrogenic”
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- Authors
- Schmalz, X., Biurrun Manresa, J., & Zhang, L.
- Affiliations
- LMU Klinikum (DE)
- University of Vienna (AT)
- Venue
- Psychological Methods
- Published
- 2023-06
- Volume
- 28
- Issue
- 3
- Pages
- 705-718
- ISSN
- 1082-989X (ISSN-L)
- 1939-1463
- OpenAlex
- W3095440346
- Cited by
- 138
- References
- 0
- Citations by year
- 2026: 21 · 2025: 42 · 2024: 29 · 2023: 24 · 2022: 16 · 2021: 5 · 2020: 1
- FWCI
- 13.80
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- cc-by
- Locations
- Psychological Methods (publishedVersion)
- PubMed (publishedVersion)
- University of Birmingham Research Portal (University of Birmingham) (submittedVersion)
- CONICET Digital (CONICET) (submittedVersion, cc-by-nc-sa)
- OSF Preprints (OSF Preprints) (submittedVersion, cc-by)
- OSF Preprints (OSF Preprints) (submittedVersion)
- Funders
- Deutsche Forschungsgemeinschaft (SCHM3450/1-1)
- Stifterverband
- Wikimedia
- Volkswagenstiftung (H190 5909 5096 32135)
- Vienna Science and Technology Fund (VRG13-007)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Physical Sciences › Computer Science › Artificial Intelligence › Bayesian Modeling and Causal Inference
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Keywords
- Bayes factor, Bayesian analysis, prior specification, Bayesian hypothesis testing, frequentist statistics
- MeSH terms
- Bayes Theorem, Humans
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