A general parametric approach to the meta‐analysis of randomized clinical trials

TLDR

Meta‑analysis offers a systematic, quantitative synthesis of randomized trial results, yet comprehensive methodological guidance remains limited. The article introduces a general parametric approach for meta‑analysis that uses efficient score statistics and Fisher's information to unify previous methods. The method applies to normally distributed, binary, ordinal, and survival data, and describes both fixed‑effects and random‑effects treatment models.

Abstract

Abstract Meta‐analysis provides a systematic and quantitative approach to the summary of results from randomized studies. Whilst many authors have published actual meta‐analyses concerning specific therapeutic questions, less has been published about comprehensive methodology. This article presents a general parametric approach, which utilizes efficient score statistics and Fisher's information, and relates this to different methods suggested by previous authors. Normally distributed, binary, ordinal and survival data are considered. Both the fixed effects and random effects model for treatments are described.