Simple Heterogeneity Variance Estimation for Meta-Analysis
Journal of the Royal Statistical Society Series C (Applied Statistics)Published 20 January 2005Open access
Kurex Sidik, Jeffrey N. Jonkman
Citations265
SJR quartileQ2
SJR score0.65
SNIP0.78
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Abstract
Summary A 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.
Keywords
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