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Bias and Efficiency of Meta-Analytic Variance Estimators in the Random-Effects Model

Bibliographic Data

ID23314832
AuthorsWolfgang Viechtbauer (0000-0003-3463-4063, Maastricht University, corresponding author)
Year2005
Volume30
Issue3
Pages261-293
Publication date2005-09-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueJournal of Educational and Behavioral Statistics (JOURNAL)
Journal identifiersISSN: 1076-9986 • E-ISSN: 1935-1054
PublisherAmerican Educational Research Association (AERA) (PUBLISHER)
DOI10.3102/10769986030003261
OpenAlexW2154449833
LanguageEN
Citations received143
References cited26

The meta-analytic random effects model assumes that the variability in effect size estimates drawn from a set of studies can be decomposed into two parts: heterogeneity due to random population effects and sampling variance. In this context, the usual goal is to estimate the central tendency and the amount of heterogeneity in the population effect sizes. The amount of heterogeneity in a set of effect sizes has implications regarding the interpretation of the meta-analytic findings and often serves as an indicator for the presence of potential moderator variables. Five population heterogeneity estimators were compared in this article analytically and via Monte Carlo simulations with respect to their bias and efficiency.

Context (archaeology) · Econometrics · Estimator · Meta-analysis · Moderation · Monte Carlo method · Population · Population variance · Random effects model · Statistics · Variance (accounting) · Diverse Approaches in Healthcare and Education Studies · Mathematics · Meta-analysis and systematic reviews

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Unique citing works143
Citations per year6,81
Citation span2005 - 2026 (22)
Citation velocitycurrent
Highly citedYes
Citation typesNeutral: 135
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