Multivariate meta-analysis for non-linear and other multi-parameter associations.

Gasparrini, A; Armstrong, B; Kenward, MG; (2012) Multivariate meta-analysis for non-linear and other multi-parameter associations. Statistics in medicine, 31 (29). pp. 3821-39. ISSN 0277-6715 DOI: 10.1002/sim.5471

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Abstract

: In this paper, we formalize the application of multivariate meta-analysis and meta-regression to synthesize estimates of multi-parameter associations obtained from different studies. This modelling approach extends the standard two-stage analysis used to combine results across different sub-groups or populations. The most straightforward application is for the meta-analysis of non-linear relationships, described for example by regression coefficients of splines or other functions, but the methodology easily generalizes to any setting where complex associations are described by multiple correlated parameters. The modelling framework of multivariate meta-analysis is implemented in the package mvmeta within the statistical environment R. As an illustrative example, we propose a two-stage analysis for investigating the non-linear exposure-response relationship between temperature and non-accidental mortality using time-series data from multiple cities. Multivariate meta-analysis represents a useful analytical tool for studying complex associations through a two-stage procedure.<br/>

Item Type: Article
Faculty and Department: Faculty of Public Health and Policy > Dept of Social and Environmental Health Research
Faculty of Epidemiology and Population Health > Dept of Medical Statistics
Research Centre: Centre for Statistical Methodology
PubMed ID: 22807043
Web of Science ID: 311402800003
URI: http://researchonline.lshtm.ac.uk/id/eprint/99793

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