Demystifying fixed and random effects meta-analysis

Abstract

Objective: Systematic reviewers often need to choose between two statistical methods when synthesising evidence in a meta-analysis: the fixed effect and the random effects models. The two approaches entail different assumptions about the treatment effect in the included studies. The aim of this paper was to explain the assumptions underlying each model and their implications in the interpretation of summary results.

Methods: We discussed the key assumptions underlying the two methods and the subsequent implications on interpreting results. We used two illustrative examples from a published meta-analysis and highlighted differences in results.

Results: The two meta-analytic approaches may yield similar or contradicting results. Even if results between the two models are similar, summary estimates should be interpreted in a different way.

Conclusions: Selection between fixed or random effects should be based on the clinical relevance of the assumptions that characterise each approach. Researchers should consider the implications of the analysis model in the interpretation of the findings and use prediction intervals in the random effects meta-analysis.