Journal
STATISTICS IN MEDICINE
Volume 29, Issue 12, Pages 1340-1356Publisher
WILEY
DOI: 10.1002/sim.3869
Keywords
evidence synthesis; ecologic bias; meta-analysis; mixed treatment comparisons
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Funding
- Chest, Heart and Stroke Scotland Research Studentship
- University of Bristol
- MRC [G0802413, G0800800] Funding Source: UKRI
- Medical Research Council [G0800800, G0802413] Funding Source: researchfish
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Meta-analysis of randomized controlled trials based on aggregated data is vulnerable to ecological bias if trial results are pooled over covariates that influence the outcome variable, even when the covariate does not modify the treatment effect, or is not associated with the treatment. This paper shows how, when trial results are aggregated over different levels of covariates, the within-study covariate distribution, and the effects of both covariates and treatments can be simultaneously estimated, and ecological bias reduced. Bayesian Markov chain Monte Carlo methods are used. The method is applied to a mixed treatment comparison evidence synthesis of six alternative approaches to post-stroke inpatient care. Results are compared with a model using only the stratified covariate data available, where each stratum is treated as a separate trial, and a model using fully aggregated data, where no covariate data are used. Copyright (C) 2010 John Wiley & Sons, Ltd.
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