Article first published online: 25 JUN 2003
Copyright © 2003 John Wiley & Sons, Ltd.
Statistics in Medicine
Volume 22, Issue 14, pages 2309–2333, 30 July 2003
How to Cite
Nam, I.-S., Mengersen, K. and Garthwaite, P. (2003), Multivariate meta-analysis. Statist. Med., 22: 2309–2333. doi: 10.1002/sim.1410
- Issue published online: 25 JUN 2003
- Article first published online: 25 JUN 2003
- Manuscript Accepted: SEP 2002
- Manuscript Received: JAN 2001
- Australian Research Council
- multivariate models;
- passive smoking;
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. Copyright © 2003 John Wiley & Sons, Ltd.