title: An illustrated guide to the methods of meta-analysis.
abstract: Meta-analysis is now accepted as a necessary tool for the evaluation of health care. Such analyses have been carried out in virtually every area of medicine to evaluate a wide spectrum of health care interventions and policies. This paper has three broad aims: (1) to describe the basic principles of meta-analysis, using a meta-analysis of interventions intended to reduce hospital re-admission rates for illustration; (2) to consider threats to the internal validity of meta-analysis, and the measures which can be taken to minimize their impact; and (3) to present an overview of more specialist and developing methods for synthesizing data, with the intention of outlining the directions meta-analysis may take in the future. The methods used to synthesize studies, which take 'weighted averages' of effect sizes have been refined to a high degree, while the methods for dealing with threats to the validity of meta-analyses such as publication bias, and variations in quality of the primary studies, are at a less advanced stage. However, many consider this standard 'weighted average' approach to meta-analysis not to be 'state of the art' in at least some situations, where the use of more sophisticated methods, generally to explain variation in estimates from different studies and synthesize a broader base of evidence, would be advantageous. Currently, approaches which attempt to do this are mainly still in the experimental stage and, unfortunately, ideas which sound natural and appealing are often difficult to implement in practice. Clearly, it will be some time before they are used routinely, but significant steps have been made.
authors.affiliation: Department of Epidemiology and Public Health, University of Leicester, UK.
authors.forename: A J
authors.initials: AJ
authors.lastname: Sutton
authors.forename: K R
authors.initials: KR
authors.lastname: Abrams
authors.forename: D R
authors.initials: DR
authors.lastname: Jones
mesh_terms: D001499:Bayes Theorem; D006801:Humans; D015201:Meta-Analysis as Topic; D010359:Patient Readmission / Q000706:statistics & numerical data; D015203:Reproducibility of Results