Pragmatic Apparatus – A Primer on Bayesian Model-Averaged Meta-Analysis

Cited by Lee Sonogan

Bayesian model-averaged meta-analysis for the subset of participants... |  Download Scientific Diagram

Abstract by Quentin F. Gronau, Daniel W. Heck, Sophie W. Berkhout, …

Meta-analysis is the predominant approach for quantitatively synthesizing a set of studies. If the studies themselves are of high quality, meta-analysis can provide valuable insights into the current scientific state of knowledge about a particular phenomenon. In psychological science, the most common approach is to conduct frequentist meta-analysis. In this primer, we discuss an alternative method, Bayesian model-averaged meta-analysis. This procedure combines the results of four Bayesian meta-analysis models: (a) fixed-effect null hypothesis, (b) fixed-effect alternative hypothesis, (c) random-effects null hypothesis, and (d) random-effects alternative hypothesis. These models are combined according to their plausibilities given the observed data to address the two key questions “Is the overall effect nonzero?” and “Is there between-study variability in effect size?” Bayesian model-averaged meta-analysis therefore avoids the need to select either a fixed-effect or random-effects model and instead takes into account model uncertainty in a principled manner.

Publication: Advances in Methods and Practices in Psychological Science (Peer-Reviewed Journal)

Pub Date: Jul 26, 2021 Doi:

Keywords: Bayes factor, hypothesis test, posterior probability, evidence synthesis, open materials (Plenty more

Leave a Reply

This site uses Akismet to reduce spam. Learn how your comment data is processed.