Random-effects meta-analysis of inconsistent effects: A time for change

John E. Cornell, Cynthia D. Mulrow, Russell Localio, Catharine B. Stack, Anne R. Meibohm, Eliseo Guallar, Steven N. Goodman

Research output: Contribution to journalArticle

212 Scopus citations

Abstract

A primary goal of meta-analysis is to improve the estimation of treatment effects by pooling results of similar studies. This article explains how the most widely used method for pooling heterogeneous studies-the DerSimonian-Laird (DL) estimator-can produce biased estimates with falsely high precision. A classic example is presented to show that use of the DL estimator can lead to erroneous conclusions. Particular problems with the DL estimator are discussed, and several alternative methods for summarizing heterogeneous evidence are presented. The authors support replacing universal use of the DL estimator with analyses based on a critical synthesis that recognizes the uncertainty in the evidence, focuses on describing and explaining the probable sources of variation in the evidence, and uses random-effects estimates that provide more accurate confidence limits than the DL estimator.

Original languageEnglish (US)
Pages (from-to)267-270
Number of pages4
JournalAnnals of internal medicine
Volume160
Issue number4
DOIs
StatePublished - Feb 18 2014

ASJC Scopus subject areas

  • Internal Medicine

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  • Cite this

    Cornell, J. E., Mulrow, C. D., Localio, R., Stack, C. B., Meibohm, A. R., Guallar, E., & Goodman, S. N. (2014). Random-effects meta-analysis of inconsistent effects: A time for change. Annals of internal medicine, 160(4), 267-270. https://doi.org/10.7326/m13-2886