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Confidence intervals for the between‐study variance in random effects meta‐analysis using generalised Cochran heterogeneity statistics
Author(s) -
Jackson Dan
Publication year - 2013
Publication title -
research synthesis methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.376
H-Index - 35
eISSN - 1759-2887
pISSN - 1759-2879
DOI - 10.1002/jrsm.1081
Subject(s) - confidence interval , statistics , random effects model , coverage probability , inference , meta analysis , confidence distribution , bayesian probability , statistic , mathematics , variance (accounting) , delta method , statistical inference , computer science , artificial intelligence , medicine , accounting , estimator , business
Statistical inference is problematic in the common situation in meta‐analysis where the random effects model is fitted to just a handful of studies. In particular, the asymptotic theory of maximum likelihood provides a poor approximation, and Bayesian methods are sensitive to the prior specification. Hence, less efficient, but easily computed and exact, methods are an attractive alternative. Here, methodology is developed to compute exact confidence intervals for the between‐study variance using generalised versions of Cochran's heterogeneity statistic. If some between‐study is anticipated, but it is unclear how much, then a pragmatic approach is to use the reciprocals of the within‐study standard errors as weights when computing the confidence interval. © 2013 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd.