Bayesian method in psychology: a bibliometric analysis

Resumen

The research presented in this article was aimed to explore knowledge domain related to the application of Bayesian method in psychological research. The analysis was based on metadata from 7.054 Bayesian-related psychological articles published from 1962 till 2023 and indexed in Scopus. Trends in publishing Bayesian-related articles were analyzed for different psychology subfields and estimated by the number of published Bayesian articles and their proportions within the total number of articles for each subfield in each particular year. Main research topics were analyzed using the visualization of keywords co-occurrence, and journal co-citation network. Results revealed general increasing trend in publishing Bayesian-related articles in psychology, but also illustrated differences among the subfields both in the pace of growth and relative diversity of research themes. Cognitive and experimental psychology and neurosciences stand out with a high proportion and steep increase of articles related to Bayesian method. Accordingly, most of the psychological research outside of cognitive psychology that use Bayesian method are also very saturated by topics related to cognitive processes. Statistical and methodological issues are well represented, mainly in the form of discussing Bayesian statistics in psychology as an alternative to classical statistics, but also as a method to promote open science principles, having the potential to overcome replication crisis and improve transparency of psychological research. The content of the more recent papers indicate that Bayesian networks have emerged as a useful method to explore psychopathological phenomena, while Bayesian modelling is becoming popular in developmental and educational psychology.

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Cómo citar (APA 7)

Jevremov, T., & Pajić, D. (2023). Bayesian method in psychology: a bibliometric analysis. https://doi.org/10.31234/osf.io/ybn9h