The Open UniversitySkip to content

Multivariate meta-analysis

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

Full text available as:
Full text not publicly available (Version of Record)
Due to publisher licensing restrictions, this file is not available for public download
DOI (Digital Object Identifier) Link:
Google Scholar: Look up in Google Scholar


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 Item
Copyright Holders: 2003 John Wiley & Sons, Ltd
ISSN: 0277-6715
Keywords: meta-analysis; Bayesian; multivariate models; passive smoking; ETS;
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Mathematics and Statistics
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Item ID: 17982
Depositing User: Sara Griffin
Date Deposited: 25 Aug 2009 08:48
Last Modified: 08 Dec 2018 08:43
Share this page:


Altmetrics from Altmetric

Citations from Dimensions

Actions (login may be required)

Policies | Disclaimer

© The Open University   contact the OU