A Primer on Bayesian Analysis for Experimental Psychopathologists

The principal goals of experimental psychopathology (EPP) research are to offer insights into the pathogenic mechanisms of mental disorders and to provide a stable ground for the development of clinical interventions. The main message of the present article is that those goals are better served by t...

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Bibliographic Details
Published in:Journal of experimental psychopathology 2017-06, Vol.8 (2), p.140-157
Main Authors: Krypotos, Angelos-Miltiadis, Blanken, Tessa F., Arnaudova, Inna, Matzke, Dora, Beckers, Tom
Format: Article
Language:English
Subjects:
Bayesian analysis
Mental disorders
Psychopathology
Statistical analysis
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Summary:The principal goals of experimental psychopathology (EPP) research are to offer insights into the pathogenic mechanisms of mental disorders and to provide a stable ground for the development of clinical interventions. The main message of the present article is that those goals are better served by the adoption of Bayesian statistics than by the continued use of null-hypothesis significance testing (NHST). In the first part of the article we list the main disadvantages of NHST and explain why those disadvantages limit the conclusions that can be drawn from EPP research. Next, we highlight the advantages of Bayesian statistics. To illustrate, we then pit NHST and Bayesian analysis against each other using an experimental data set from our lab. Finally, we discuss some challenges when adopting Bayesian statistics. We hope that the present article will encourage experimental psychopathologists to embrace Bayesian statistics, which could strengthen the conclusions drawn from EPP research.
ISSN:2043-8087
2043-8087
DOI:10.5127/jep.057316