Testing for Homogeneity in Meta-Analysis I. The One-Parameter Case: Standardized Mean Difference

DOI10.1111/j.1541-0420.2010.01442.xzbMath1217.62173arXiv0906.2999OpenAlexW2158339716WikidataQ44829398 ScholiaQ44829398MaRDI QIDQ3008879

Elena Kulinskaya, Kirsten Bjørkestøl, Michael B. Dollinger

Publication date: 22 June 2011

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/0906.2999

zbMATH Keywords

\(Q\) statisticCohen's \(d\)-statisticfractional degrees of freedomheterogeneity testweighted ANOVAweighted sum of squares

Mathematics Subject Classification ID

Related Items (7)

Plug-in tests for nonequivalence of means of independent normal populations ⋮ On the Q statistic with constant weights for standardized mean difference ⋮ When should meta‐analysis avoid making hidden normality assumptions? ⋮ Testing for Homogeneity in Meta-Analysis I. The One-Parameter Case: Standardized Mean Difference ⋮ Testing homogeneity of effect sizes in pooling 2x2 contingency tables from multiple studies: a comparison of methods ⋮ An overdispersion model in meta-analysis ⋮ Investigating heterogeneity in meta-analysis of studies with rare events. Estimating the amount of heterogeneity

Cites Work

• Robust weighted one-way ANOVA: improved approximation and efficiency
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• Testing for Homogeneity in Meta-Analysis I. The One-Parameter Case: Standardized Mean Difference
• Bias reduction of maximum likelihood estimates
• THE COMPARISON OF SEVERAL GROUPS OF OBSERVATIONS WHEN THE RATIOS OF THE POPULATION VARIANCES ARE UNKNOWN
• ON THE COMPARISON OF SEVERAL MEAN VALUES: AN ALTERNATIVE APPROACH
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