Published by Oxford University Press on behalf of the International Epidemiological Association © The Author 2008; all rights reserved.
Commentary: Heterogeneity in meta-analysis should be expected and appropriately quantified
MRC Biostatistics Unit, Institute of Public Health, Robinson Way, Cambridge CB2 0SR, UK.
E-mail: julian.higgins@mrc-bsu.cam.ac.uk
Accepted 28 August 2008
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It is generally accepted that meta-analyses should assess heterogeneity, which may be defined as the presence of variation in true effect sizes underlying the different studies. This assessment might be achieved by performing a statistical test for heterogeneity, by quantifying its magnitude, by quantifying its impact or by a combination of these. Patsopoulos, Evangelou and Ioannidis propose methods for examining the effect of excluding studies (or groups of studies) on an assessment of heterogeneity.1 Their methods offer benefits over the sometimes practiced ‘leave one out’ approach to sensitivity analysis, by recognizing that the overall effect (against which heterogeneity is measured) changes each time an influential study is excluded. The authors offer a sequential approach (in which the overall effect and heterogeneity measure
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