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A re-evaluation of random-effects meta-analysis
Version of Record online: 24 JUL 2008
Journal compilation © 2009 Royal Statistical Society
Journal of the Royal Statistical Society: Series A (Statistics in Society)
Volume 172, Issue 1, pages 137–159, January 2009
How to Cite
Higgins, J. P. T., Thompson, S. G. and Spiegelhalter, D. J. (2009), A re-evaluation of random-effects meta-analysis. Journal of the Royal Statistical Society: Series A (Statistics in Society), 172: 137–159. doi: 10.1111/j.1467-985X.2008.00552.x
- Issue online: 22 DEC 2008
- Version of Record online: 24 JUL 2008
- [Received March 2007. Revised March 2008]
- Random-effects models;
- Systematic reviews
Summary. Meta-analysis in the presence of unexplained heterogeneity is frequently undertaken by using a random-effects model, in which the effects underlying different studies are assumed to be drawn from a normal distribution. Here we discuss the justification and interpretation of such models, by addressing in turn the aims of estimation, prediction and hypothesis testing. A particular issue that we consider is the distinction between inference on the mean of the random-effects distribution and inference on the whole distribution. We suggest that random-effects meta-analyses as currently conducted often fail to provide the key results, and we investigate the extent to which distribution-free, classical and Bayesian approaches can provide satisfactory methods. We conclude that the Bayesian approach has the advantage of naturally allowing for full uncertainty, especially for prediction. However, it is not without problems, including computational intensity and sensitivity to a priori judgements. We propose a simple prediction interval for classical meta-analysis and offer extensions to standard practice of Bayesian meta-analysis, making use of an example of studies of ‘set shifting’ ability in people with eating disorders.