An Extended ANOVA F-Test with Applications to the Heterogeneity Problem in Meta-Analysis

The classical F‐test in the one‐way random effects ANOVA model is extended to solve the long outstanding problem of testing the between‐group variance on values also different from zero. This is done first for homoscedastic and heteroscedastic cases in not necessarily balanced models and secondly fo...

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Published inBiometrical journal Vol. 43; no. 2; pp. 135 - 146
Main Authors Hartung, Joachim, Makambi, Kepher Henry, Argaç, Dog̃an
Format Journal Article
LanguageEnglish
Published Berlin WILEY-VCH Verlag Berlin GmbH 01.05.2001
WILEY‐VCH Verlag Berlin GmbH
Wiley-VCH
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Abstract The classical F‐test in the one‐way random effects ANOVA model is extended to solve the long outstanding problem of testing the between‐group variance on values also different from zero. This is done first for homoscedastic and heteroscedastic cases in not necessarily balanced models and secondly for balanced homoscedastic models. By simulation, the tests are shown to attain acceptable significance levels and high power even in data that do not follow the usual ANOVA model. An important application of the tests is given by the heterogeneity questions concerning the treatment effects across studies in meta‐analysis.
AbstractList The classical F‐test in the one‐way random effects ANOVA model is extended to solve the long outstanding problem of testing the between‐group variance on values also different from zero. This is done first for homoscedastic and heteroscedastic cases in not necessarily balanced models and secondly for balanced homoscedastic models. By simulation, the tests are shown to attain acceptable significance levels and high power even in data that do not follow the usual ANOVA model. An important application of the tests is given by the heterogeneity questions concerning the treatment effects across studies in meta‐analysis.
Author Makambi, Kepher Henry
Hartung, Joachim
Argaç, Dog̃an
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Cites_doi 10.1214/aoms/1177706077
10.1016/0197-2456(86)90046-2
10.1002/(SICI)1097-0258(19990215)18:3<321::AID-SIM28>3.0.CO;2-P
10.1002/(SICI)1097-0258(19960330)15:6<619::AID-SIM188>3.0.CO;2-A
10.1080/01621459.1986.10478322
10.1002/sim.4780101105
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Issue 2
Keywords F test
Data analysis
Covariance analysis
Meta analysis
Risk
Statistical estimation
Multivariate analysis
Variance analysis
Heteroscedasticity
Hypothesis test
Heterogeneity
One way analysis of variance
Random effect
Linear estimation
Sampling
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Snippet The classical F‐test in the one‐way random effects ANOVA model is extended to solve the long outstanding problem of testing the between‐group variance on...
The classical F-test in the one-way random effects ANOVA model is extended to solve the long outstanding problem of testing the between-group variance on...
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SubjectTerms ANOVA F-test
Attained power
Attained significance level
Between-group variance
Exact sciences and technology
Linear inference, regression
Mathematics
Meta-analysis
Multivariate analysis
Probability and statistics
Random effects model
Risk difference
Sciences and techniques of general use
Statistics
Title An Extended ANOVA F-Test with Applications to the Heterogeneity Problem in Meta-Analysis
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