AI Article Synopsis
- The article discusses the growing use of Bayes factors in psychological research and emphasizes the need for researchers to understand how to interpret them.
- It outlines the basic principles of Bayesian statistics, including how to calculate Bayes factors and set appropriate priors in statistical software.
- The article also offers practical guidelines and warnings for correctly interpreting Bayes factors to ensure accurate research outcomes.
Article Abstract
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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| http://dx.doi.org/10.1037/met0000421 | DOI Listing |
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