A practical guide to random-effects Bayesian meta-analyses with application to the psychological trauma and suicide literature.

OBJECTIVE: Bayesian meta-analyses offer several advantages over traditional approaches, including improved accuracy when using a small number of studies and enhanced estimation of heterogeneity. However, psychological trauma research has yet to see widespread adoption of these statistical methods, potentially due to researchers' unfamiliarity with the processes involved. The purpose of this article is to provide a practical tutorial for conducting random-effects Bayesian meta-analyses. METHOD: Explanations and recommendations are provided for completing the primary steps of a Bayesian meta-analysis, ranging from model specification to interpretation of results. Furthermore, an illustrative example is used to demonstrate the application of each step. In the example, results are synthesized from six studies included in a previously published systematic review (Holliday et al., 2020), with a combined sample size of 21,244,109, examining the association between posttraumatic stress disorder and risk of suicide in veterans and military personnel. RESULTS: The posterior distributions for each model estimate, such as the pooled effect size and the heterogeneity parameter, are discussed and interpreted with regard to the probability of increased suicide risk. CONCLUSIONS: Our hope is that this tutorial, along with the provided data and code, facilitate the use of Bayesian meta-analyses in the study of psychological trauma. (PsycInfo Database Record (c) 2023 APA, all rights reserved).