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Estimating heterogeneity variance in meta‐analysis
Author(s) -
Rukhin Andrew L.
Publication year - 2013
Publication title -
journal of the royal statistical society: series b (statistical methodology)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.523
H-Index - 137
eISSN - 1467-9868
pISSN - 1369-7412
DOI - 10.1111/j.1467-9868.2012.01047.x
Subject(s) - estimator , statistic , statistics , mathematics , confidence interval , bayes' theorem , u statistic , monte carlo method , econometrics , variance (accounting) , meta analysis , minimum variance unbiased estimator , bayesian probability , medicine , economics , accounting
Summary. Several new estimators of the between‐study variability in a heterogeneous random effects meta‐analysis model are derived. One is the unbiased statistic which is locally optimal for small values of the parameter. Others are Bayes procedures within a class of quadratic statistics for a diffuse prior with different choices of the prior mean. These estimators are compared with the DerSimonian–Laird procedure and the Hedges statistic in particular via the quadratic risk of the treatment effect estimator. A Monte Carlo study supports the usage of confidence intervals derived from the new estimators.