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Estimating within-study covariances in multivariate meta-analysis with multiple outcomes

Multivariate meta-analysis allows the joint synthesis of effect estimates based on multiple outcomes from multiple studies, accounting for the potential correlations among them. However, standard methods for multivariate meta-analysis for multiple outcomes are restricted to problems where the within...

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Detalles Bibliográficos
Autores principales: Wei, Yinghui, Higgins, Julian PT
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Ltd 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3618374/
https://www.ncbi.nlm.nih.gov/pubmed/23208849
http://dx.doi.org/10.1002/sim.5679
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author Wei, Yinghui
Higgins, Julian PT
author_facet Wei, Yinghui
Higgins, Julian PT
author_sort Wei, Yinghui
collection PubMed
description Multivariate meta-analysis allows the joint synthesis of effect estimates based on multiple outcomes from multiple studies, accounting for the potential correlations among them. However, standard methods for multivariate meta-analysis for multiple outcomes are restricted to problems where the within-study correlation is known or where individual participant data are available. This paper proposes an approach to approximating the within-study covariances based on information about likely correlations between underlying outcomes. We developed methods for both continuous and dichotomous data and for combinations of the two types. An application to a meta-analysis of treatments for stroke illustrates the use of the approximated covariance in multivariate meta-analysis with correlated outcomes. Copyright © 2012 John Wiley & Sons, Ltd.
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spelling pubmed-36183742013-04-08 Estimating within-study covariances in multivariate meta-analysis with multiple outcomes Wei, Yinghui Higgins, Julian PT Stat Med Research Articles Multivariate meta-analysis allows the joint synthesis of effect estimates based on multiple outcomes from multiple studies, accounting for the potential correlations among them. However, standard methods for multivariate meta-analysis for multiple outcomes are restricted to problems where the within-study correlation is known or where individual participant data are available. This paper proposes an approach to approximating the within-study covariances based on information about likely correlations between underlying outcomes. We developed methods for both continuous and dichotomous data and for combinations of the two types. An application to a meta-analysis of treatments for stroke illustrates the use of the approximated covariance in multivariate meta-analysis with correlated outcomes. Copyright © 2012 John Wiley & Sons, Ltd. John Wiley & Sons, Ltd 2013-03-30 2012-12-03 /pmc/articles/PMC3618374/ /pubmed/23208849 http://dx.doi.org/10.1002/sim.5679 Text en Copyright © 2013 John Wiley & Sons, Ltd. http://creativecommons.org/licenses/by/2.5/ Re-use of this article is permitted in accordance with the Creative Commons Deed, Attribution 2.5, which does not permit commercial exploitation.
spellingShingle Research Articles
Wei, Yinghui
Higgins, Julian PT
Estimating within-study covariances in multivariate meta-analysis with multiple outcomes
title Estimating within-study covariances in multivariate meta-analysis with multiple outcomes
title_full Estimating within-study covariances in multivariate meta-analysis with multiple outcomes
title_fullStr Estimating within-study covariances in multivariate meta-analysis with multiple outcomes
title_full_unstemmed Estimating within-study covariances in multivariate meta-analysis with multiple outcomes
title_short Estimating within-study covariances in multivariate meta-analysis with multiple outcomes
title_sort estimating within-study covariances in multivariate meta-analysis with multiple outcomes
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3618374/
https://www.ncbi.nlm.nih.gov/pubmed/23208849
http://dx.doi.org/10.1002/sim.5679
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