How to understand and report heterogeneity in a meta-analysis: The difference between I-squared and prediction intervals

In any meta-analysis it is important to report not only the mean effect size but also how the effect size varies across studies. A treatment that has a moderate clinical impact in all studies is very different than a treatment where the impact is moderate on average, but in some studies is large and in others is trivial (or even harmful). A treatment that has no impact in any studies is very different than a treatment that has no impact on average because it is helpful in some studies but harmful in others. The majority of meta-analyses use the I-squared index to quantify heterogeneity. While this practice is common it is nevertheless incorrect. I-squared does not tell us how much the effect size varies…