Systematic search of Bayesian statistics in the field of psychotraumatology
In many different disciplines there is a recent increase in interest of Bayesian analysis. Bayesian methods implement Bayes' theorem, which states that prior beliefs are updated with data, and this process produces updated beliefs about model parameters. The prior is based on how much information we believe we have preceding data collection, as well as how accurate we believe that information to be. To further encourage the use of Bayesian statistics in the field of Psychotraumatology we initiated a special issue on the use of Bayesian statistics.
We first introduce briefly how and why Bayesian statistics are already being applied by means of describing the results of a systematic search in the psychotrauma field. Reasons mentioned were: Flexible hypothesis testing, Updating probabilities, No need for large data sets, Imputation of missing data, Allows to deal with technical complexities. Thereafter we describe the papers submitted as part of this special issue on Bayesian statistics. There is a recent increase in interest of Bayesian analysis.
van de Schoot, R., Schalken, N., & Olff, M. (2017). Systematic search of Bayesian statistics in the field of psychotraumatology. European Journal of Psychotraumatology, 8(sup1): 1375339. http://dx.doi.org/10.1080/20008198.2017.1375339
See the online supplementary materials published on the Open Science Framework for more information: our logbook, Endnote file with all the references, the exclusion decisions, and an overview of the included papers.
This paper is part of a special issue on Bayesian statistics in the field of psychotraumatology.