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Multivariate meta-analysis

In-Sun, Nam; Mengersen, Kerrie and Garthwaite, Paul (2003). Multivariate meta-analysis. Statistics in Medicine, 22(14) pp. 2309–2333.

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DOI (Digital Object Identifier) Link: http://dx.doi.org/10.1002/sim.1410
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Abstract

Meta-analysis is now a standard statistical tool for assessing the overall strength and interesting features of a relationship, on the basis of multiple independent studies. There is, however, recent acknowledgement of the fact that in many applications responses are rarely uniquely determined. Hence there has been some change of focus from a single response to the analysis of multiple outcomes. In this paper we propose and evaluate three Bayesian multivariate meta-analysis models: two multivariate analogues of the traditional univariate random effects models which make different assumptions about the relationships between studies and estimates, and a multivariate random effects model which is a Bayesian adaptation of the mixed model approach. Our preferred method is then illustrated through an analysis of a new data set on parental smoking and two health outcomes (asthma and lower respiratory disease) in children.

Item Type: Journal Article
Copyright Holders: 2003 John Wiley & Sons, Ltd
ISSN: 0277-6715
Keywords: meta-analysis; Bayesian; multivariate models; passive smoking; ETS;
Academic Unit/Department: Mathematics, Computing and Technology > Mathematics and Statistics
Item ID: 17982
Depositing User: Sara Griffin
Date Deposited: 25 Aug 2009 08:48
Last Modified: 03 Dec 2010 21:26
URI: http://oro.open.ac.uk/id/eprint/17982
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