Basics of meta‐analysis: <i>I</i>² is not an absolute measure of heterogeneity

TLDR

In meta‑analysis, heterogeneity is typically examined to assess how effect sizes vary across populations, but the commonly used I² statistic does not actually convey the range of effects. The authors propose that researchers should directly report the predicted range of effects rather than relying on I². They demonstrate that I² offers no information about effect‑size ranges, whereas reporting the actual range provides concise, unambiguous insight. © 2017 John Wiley & Sons, Ltd.

Abstract

When we speak about heterogeneity in a meta‐analysis, our intent is usually to understand the substantive implications of the heterogeneity. If an intervention yields a mean effect size of 50 points, we want to know if the effect size in different populations varies from 40 to 60, or from 10 to 90, because this speaks to the potential utility of the intervention. While there is a common belief that the I 2 statistic provides this information, it actually does not. In this example, if we are told that I 2 is 50%, we have no way of knowing if the effects range from 40 to 60, or from 10 to 90, or across some other range. Rather, if we want to communicate the predicted range of effects, then we should simply report this range. This gives readers the information they think is being captured by I 2 and does so in a way that is concise and unambiguous. Copyright © 2017 John Wiley &amp; Sons, Ltd.