Citation

Krypotos AM, Klugkist I, Engelhard IM. Eur. J. Psychotraumatol. 2017; 8(Suppl 1): e1314782.

Affiliation

Department of Clinical Psychology, Faculty of Social and Behavioural Sciences, Utrecht University, Utrecht, The Netherlands.

Copyright

(Copyright © 2017, The Author(s), Publisher Co-action Publishing)

DOI

10.1080/20008198.2017.1314782

PMID

29038683

PMCID

PMC5632775

Abstract

Threat conditioning procedures have allowed the experimental investigation of the pathogenesis of Post-Traumatic Stress Disorder. The findings of these procedures have also provided stable foundations for the development of relevant intervention programs (e.g. exposure therapy). Statistical inference of threat conditioning procedures is commonly based on p-values and Null Hypothesis Significance Testing (NHST). Nowadays, however, there is a growing concern about this statistical approach, as many scientists point to the various limitations of p-values and NHST. As an alternative, the use of Bayes factors and Bayesian hypothesis testing has been suggested. In this article, we apply this statistical approach to threat conditioning data. In order to enable the easy computation of Bayes factors for threat conditioning data we present a new R package named condir, which can be used either via the R console or via a Shiny application. This article provides both a non-technical introduction to Bayesian analysis for researchers using the threat conditioning paradigm, and the necessary tools for computing Bayes factors easily.

Language: en

Keywords

Bayes factor; Post-Traumatic Stress Disorder; experimental psychopathology; fear; treatment