Simple heterogeneity variance estimation for meta-analysis
AbstractA simple method of estimating the heterogeneity variance in a random-effects model for meta-analysis is proposed. The estimator that is presented is simple and easy to calculate and has improved bias compared with the most common estimator used in random-effects meta-analysis, particularly when the heterogeneity variance is moderate to large. In addition, it always yields a non-negative estimate of the heterogeneity variance, unlike some existing estimators. We find that random-effects inference about the overall effect based on this heterogeneity variance estimator is more reliable than inference using the common estimator, in terms of coverage probability for an interval estimate. Copyright 2005 Royal Statistical Society.
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Bibliographic InfoArticle provided by Royal Statistical Society in its journal Journal of the Royal Statistical Society Series C.
Volume (Year): 54 (2005)
Issue (Month): 2 ()
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- Heinz Holling & Walailuck Böhning & Dankmar Böhning, 2012. "Likelihood-Based Clustering of Meta-Analytic SROC Curves," Psychometrika, Springer, vol. 77(1), pages 106-126, January.
- Sidik, Kurex & Jonkman, Jeffrey N., 2006. "Robust variance estimation for random effects meta-analysis," Computational Statistics & Data Analysis, Elsevier, vol. 50(12), pages 3681-3701, August.
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