BMJ  2003;327:557-560 (6 September), doi:10.1136/bmj.327.7414.557

Education and debate

Measuring inconsistency in meta-analyses

Julian P T Higgins, statistician1, Simon G Thompson, director1, Jonathan J Deeks, senior medical statistician2, Douglas G Altman, professor of statistics in medicine2

1 MRC Biostatistics Unit, Institute of Public Health, Cambridge CB2 2SR, 2 Cancer Research UK/NHS Centre for Statistics in Medicine, Institute of Health Sciences, Oxford OX3 7LF

Correspondence to: J P T Higgins julian.higgins@mrc-bsu.cam.ac.uk

Cochrane Reviews have recently started including the quantity I2 to help readers assess the consistency of the results of studies in meta-analyses. What does this new quantity mean, and why is assessment of heterogeneity so important to clinical practice?

The first 150 words of the full text of this article appear below.

Systematic reviews and meta-analyses can provide convincing and reliable evidence relevant to many aspects of medicine and health care.1 Their value is especially clear when the results of the studies they include show clinically important effects of similar magnitude. However, the conclusions are less clear when the included studies have differing results. In an attempt to establish whether studies are consistent, reports of meta-analyses commonly present a statistical test of heterogeneity. The test seeks to determine whether there are genuine differences underlying the results of the studies (heterogeneity), or whether the variation in findings is compatible with chance alone (homogeneity). However, the test is susceptible to the number of trials included in the meta-analysis. We have developed a new quantity, I2, which we believe gives a better measure of the consistency between trials in a meta-analysis.

Need for consistency

Assessment of the consistency of effects across studies is an essential part of . . . [Full text of this article]

Testing for heterogeneity


Quantifying heterogeneity: a better approach


Examples of values of I2


Further applications of I2


Methodological subgroups
Heterogeneity related to choice of effect measure
Clinically important subgroups

How much is too much heterogeneity?



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Rapid Responses:

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I2 Is Subject to the Same Statistical Power Problems as Cochran's Q
Tania Huedo-Medina, et al.
bmj.com, 4 Jan 2007 [Full text]
A better method of dealing with inconsistency in meta-analyses
Suhail Doi
bmj.com, 4 Jan 2008 [Full text]



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