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
|PDF - Published Version |
Available under License Creative Commons Attribution Non-commercial No Derivatives.
Download (380Kb) | Preview
: 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/>
|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|
|Web of Science ID:||311402800003|
Item downloaded times since 25 Jul 2012 18:21.
Actions (login required)