Measuring heterogeneity in meta-analysis

Steve Simon


While browsing through the archives of the British Medical Journal, I noticed an excellent article on measuring heterogeneity in meta-analysis. There is a new measure, I-squared, that measures the proportion of inconsistency in individual studies that cannot be explained by chance. It ranges between 0% and 100% with lower values representing less heterogeneity.

This measure is preferred to the traditional test statistic, Cochran’s Q. The problem with Cochran’s Q, the authors claim, is that it tends to have too little power with a collection of studies with small sample sizes and too much power with a collection of studies with large sample sizes.

They also provide an informal categorization of I-squared, with values of 25%, 50%, and 75% representing low, moderate, and high heterogeneity.

Measuring inconsistency in meta-analyses. J. P. Higgins, S. G. Thompson, J. J. Deeks, D. G. Altman. Bmj 2003: 327(7414); 557-60. [Medline] [Full text] [PDF]

You can find an earlier version of this page on my original website.