Contribution to the discussion of "When should meta-analysis avoid making hidden normality assumptions?": A Bayesian perspective

TL;DR

This paper offers a Bayesian perspective on when meta-analysis should avoid assuming hidden normality, providing insights into the conditions and implications of such assumptions in statistical synthesis.

Contribution

It introduces a Bayesian framework to evaluate the appropriateness of normality assumptions in meta-analysis, enhancing methodological understanding.

Findings

Bayesian methods clarify when normality assumptions are valid.

Guidelines for avoiding hidden normality assumptions in meta-analysis.

Improved interpretation of meta-analytic results under Bayesian analysis.

Abstract

Contribution to the discussion of "When should meta-analysis avoid making hidden normality assumptions?" by Dan Jackson and Ian R. White (2018; https://doi.org/10.1002/bimj.201800071).