Abstract

Although the statistical tools most often used by researchers in the field of Psychology over the last 25 years are based on frequentist statistics, it is often claimed that the alternative Bayesian approach to statistics is gaining in popularity. In the current paper, we investigated this claim by performing the very first systematic review of Bayesian psychological papers published between 1990-2015 (n=1,579). We aim to provide a thorough presentation of the role Bayesian statistics plays in Psychology. This historical assessment allows us to identify trends and see how Bayesian methods have been integrated into psychological research in the context of different statistical frameworks (e.g., hypothesis testing, cognitive models, IRT, SEM, etc.). We also describe take-home messages and provide “big-picture” recommendations to the field as Bayesian statistics becomes more popular. Our review indicated that Bayesian statistics is used in a variety of contexts across subfields of Psychology and related disciplines. There are many different reasons why one might choose to use Bayes (e.g., the use of priors, estimating otherwise intractable models, modeling uncertainty, etc.). We found in this review that the use of Bayes has increased and broadened in the sense that this methodology can be used in a flexible manner to tackle many different forms of questions. We hope this presentation opens the door for a larger discussion regarding the current state of Bayesian statistics, as well as future trends.

 

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Figure 1. Bayes is growing in all disciplines! Initial search on Scopus with the search word “Bayesian” in the title, abstract or keywords (excluding “Bayesian Information Criterion”). Note STEM: Science, Technology, Engineering, and Mathematics.

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A.     Absolute growth of Psychology papers mentioning “Bayesian”

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B. Relative growth of Psychology papers mentioning “Bayesian”

 

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Figure 2. Number of published papers in the field of Psychology on regression type of papers per type of paper per year: the number of empirical applications is growing!

 

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Figure 4. Wordcloud showing terms used to describe the level of informativeness of the priors in the empirical regression-based papers. Many variations are used!

 

Reference

Van de Schoot, R., Winter, S., Ryan, O., Zondervan-Zwijnenburg, M., & Depaoli, S. (2016). A Systematic Review of Bayesian Papers in Psychology: The Last 25 Years. Psychological Methods, 21(4). http://dx.doi.org/10.1037/met0000100