The impact of multiple endpoint dependency on Q and I(2) in meta-analysis.

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Computing Multivariate Effect Sizes and Their Sampling Covariance Matrices With Structural Equation Modeling: Theory, Examples, and Computer Simulations

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The impact of multiple endpoint dependency on Q and I(2) in meta-analysis.

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The impact of multiple endpoint dependency on Q and I(2) in meta-analysis.

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The impact of multiple endpoint dependency on Q and I(2) in meta-analysis.

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The impact of multiple endpoint dependency on Q and I(2) in meta-analysis.

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P1476

The impact of multiple endpoint dependency on Q and I(2) in meta-analysis.

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Christopher Glen Thompson

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Hypothesis tests for population heterogeneity in meta-analysis

Measuring inconsistency in meta-analyses

Quantifying heterogeneity in a meta-analysis

Improving the quality of reports of meta-analyses of randomised controlled trials: the QUOROM statement. Quality of Reporting of Meta-analyses

Quantifying the impact of between-study heterogeneity in multivariate meta-analyses

Assessing heterogeneity in meta-analysis: Q statistic or I2 index?

Reporting standards for research in psychology: why do we need them? What might they be?

A practical introduction to multivariate meta-analysis.

Meta-analysis of effect sizes reported at multiple time points: a multivariate approach.

Critical interpretation of Cochran's Q test depends on power and prior assumptions about heterogeneity.

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235-253

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scholarly article

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10.1002/JRSM.1110

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Betsy J. Becker

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2014-02-14T00:00:00Z

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26052849

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The impact of multiple endpoint dependency on Q and I(2) in meta-analysis.

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P2860

P2860

The impact of multiple endpoint dependency on Q and I(2) in meta-analysis.

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P1476

P2093

P2860

P304

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P356

P433

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P698

P356

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P1476

P2093

P2860

P304

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P356

P433

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P698