Within-study covariance estimators for network meta-analysis with contrast-based approach

The contrast-based approach is one of the primary approaches in network meta-analysis. For statistical modeling in network meta-analysis and meta-regression models, within-study covariance estimates are needed to adequately address the correlations among the multivariate outcomes. In this computatio...

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Bibliographic Details
Published inJapanese Journal of Biometrics Vol. 44; no. 2; pp. 119 - 126
Main Author Noma, Hisashi
Format Journal Article
LanguageJapanese
Published The Biometric Society of Japan 01.03.2024
Subjects
contrast-based approach
multivariate randomeffects model
network meta-analysis
network meta-regression
within-study covariance matrix
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ISSN0918-4430
2185-6494
DOI10.5691/jjb.44.119

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Summary:The contrast-based approach is one of the primary approaches in network meta-analysis. For statistical modeling in network meta-analysis and meta-regression models, within-study covariance estimates are needed to adequately address the correlations among the multivariate outcomes. In this computational note, we present the formulas of covariance estimators for standard effect measures used in modern meta-analysis practice: risk difference, risk ratio, odds ratio, mean difference, and standardized mean difference (Cohen’s d and Hedge’s g).
ISSN:0918-4430
2185-6494
DOI:10.5691/jjb.44.119