Bayesian hypothesis testing: Editorial to the special issue on Bayesian data analysis

Publication date

2017-06-01

Authors

Hoijtink, HerbertISNI 0000000389542756
Chow, Sy Miin

Editors

Advisors

Supervisors

Document Type

Editorial
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Abstract

In the past 20 years, there has been a steadily increasing attention and demand for Bayesian data analysis across multiple scientific disciplines, including psychology. Bayesian methods and the related Markov chain Monte Carlo sampling techniques offered renewed ways of handling old and challenging new problems that may be difficult or impossible to handle using classical approaches. Yet, such opportunities and potential improvements have not been sufficiently explored and investigated. This is 1 of 2 special issues in Psychological Methods dedicated to the topic of Bayesian data analysis, with an emphasis on Bayesian hypothesis testing, model comparison, and general guidelines for applications in psychology. In this editorial, we provide an overview of the use of Bayesian methods in psychological research and a brief history of the Bayes factor and the posterior predictive p value. Translational abstracts that summarize the articles in this issue in very clear and understandable terms are included in the Appendix.

Keywords

Bayes Factor, Bayesian data analysis, Bayesian estimation, Bayesian modeling, Posterior predictive p value, Psychology (miscellaneous)

Citation

Hoijtink, H & Chow, S M 2017, 'Bayesian hypothesis testing : Editorial to the special issue on Bayesian data analysis', Psychological Methods, vol. 22, no. 2, pp. 211-216. https://doi.org/10.1037/met0000143