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Multivariate meta-analysis: Potential and promise
The multivariate random effects model is a generalization of the standard univariate model. Multivariate meta-analysis is becoming more commonly used and the techniques and related computer software, although continually under development, are now in place. In order to raise awareness of the multiva...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons, Ltd
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3470931/ https://www.ncbi.nlm.nih.gov/pubmed/21268052 http://dx.doi.org/10.1002/sim.4172 |
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author | Jackson, Dan Riley, Richard White, Ian R |
author_facet | Jackson, Dan Riley, Richard White, Ian R |
author_sort | Jackson, Dan |
collection | PubMed |
description | The multivariate random effects model is a generalization of the standard univariate model. Multivariate meta-analysis is becoming more commonly used and the techniques and related computer software, although continually under development, are now in place. In order to raise awareness of the multivariate methods, and discuss their advantages and disadvantages, we organized a one day ‘Multivariate meta-analysis’ event at the Royal Statistical Society. In addition to disseminating the most recent developments, we also received an abundance of comments, concerns, insights, critiques and encouragement. This article provides a balanced account of the day's discourse. By giving others the opportunity to respond to our assessment, we hope to ensure that the various view points and opinions are aired before multivariate meta-analysis simply becomes another widely used de facto method without any proper consideration of it by the medical statistics community. We describe the areas of application that multivariate meta-analysis has found, the methods available, the difficulties typically encountered and the arguments for and against the multivariate methods, using four representative but contrasting examples. We conclude that the multivariate methods can be useful, and in particular can provide estimates with better statistical properties, but also that these benefits come at the price of making more assumptions which do not result in better inference in every case. Although there is evidence that multivariate meta-analysis has considerable potential, it must be even more carefully applied than its univariate counterpart in practice. Copyright © 2011 John Wiley & Sons, Ltd. |
format | Online Article Text |
id | pubmed-3470931 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | John Wiley & Sons, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-34709312012-10-18 Multivariate meta-analysis: Potential and promise Jackson, Dan Riley, Richard White, Ian R Stat Med Research Articles The multivariate random effects model is a generalization of the standard univariate model. Multivariate meta-analysis is becoming more commonly used and the techniques and related computer software, although continually under development, are now in place. In order to raise awareness of the multivariate methods, and discuss their advantages and disadvantages, we organized a one day ‘Multivariate meta-analysis’ event at the Royal Statistical Society. In addition to disseminating the most recent developments, we also received an abundance of comments, concerns, insights, critiques and encouragement. This article provides a balanced account of the day's discourse. By giving others the opportunity to respond to our assessment, we hope to ensure that the various view points and opinions are aired before multivariate meta-analysis simply becomes another widely used de facto method without any proper consideration of it by the medical statistics community. We describe the areas of application that multivariate meta-analysis has found, the methods available, the difficulties typically encountered and the arguments for and against the multivariate methods, using four representative but contrasting examples. We conclude that the multivariate methods can be useful, and in particular can provide estimates with better statistical properties, but also that these benefits come at the price of making more assumptions which do not result in better inference in every case. Although there is evidence that multivariate meta-analysis has considerable potential, it must be even more carefully applied than its univariate counterpart in practice. Copyright © 2011 John Wiley & Sons, Ltd. John Wiley & Sons, Ltd 2011-09-10 2011-01-26 /pmc/articles/PMC3470931/ /pubmed/21268052 http://dx.doi.org/10.1002/sim.4172 Text en Copyright © 2012 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 Jackson, Dan Riley, Richard White, Ian R Multivariate meta-analysis: Potential and promise |
title | Multivariate meta-analysis: Potential and promise |
title_full | Multivariate meta-analysis: Potential and promise |
title_fullStr | Multivariate meta-analysis: Potential and promise |
title_full_unstemmed | Multivariate meta-analysis: Potential and promise |
title_short | Multivariate meta-analysis: Potential and promise |
title_sort | multivariate meta-analysis: potential and promise |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3470931/ https://www.ncbi.nlm.nih.gov/pubmed/21268052 http://dx.doi.org/10.1002/sim.4172 |
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