Fixed-effect versus random-effect model in meta-analysis: How to decide?

Abstract

Interpretation of meta-analysis requires an appropriate understanding of its statistical methods. Data synthesis methods are the basis of the meta-analytic process, and a thorough knowledge of the models used is essential. The two most widely used methods for data synthesis are the 'fixed-effect method' and the 'random-effect method'. The latter is commonly used when a 'significant heterogeneity' exists. This narrative review explains fixed- and random-effect models, the two most commonly used data synthesis models.