| Volume 8, Issue 2, 140-157, 2017 |
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|A Primer on Bayesian Analysis for Experimental Psychopathologists|
| Angelos-Miltiadis Krypotos - Department of Clinical Psychology, Utrecht Univers|
| Tessa Blanken - Department of Sleep and Cognition, Netherlands Ins|
| Inna Arnaudova - Department of Clinical Psychology, University of A|
| Dora Matzke - Department of Psychological Methods and Statistics|
| Tom Beckers - Department of Clinical Psychology, University of A|
|Volume 8, Issue 2, 2017, Pages 140-157|
The principal goals of experimental psychopathology (EPP) 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.
|Table of Contents|
Why NHST is ill-suited for EPP research
Bayesian analysis as an alternative to NHST or How I learned to stop worrying and love the data
Bayesian parameter estimation
Bayesian hypothesis testing
Advantages of Bayesian analysis over NHST
Pitting inferences from NHST and Bayesian hypothesis testing against each other: An example from the field of EPP
Exit Interview and Questionnaires.
Questionnaires and Evaluations.
|Dr. Angelos-Miltiadis Krypotos, Department of Clinical Psychology, Utrecht University, Utrecht, the Netherlands. |
|p-values, Bayesian inference, statistical analysis, mental disorders, fear learning |
|Received 26 Mar 2016; Revised 1 Dec 2016; Accepted 1 Dec 2016; In Press 19 Feb 2017 |