Another useful metric is the I2. This metric is independent of the number of studies and can be compared across meta-analyses with different number of studies and metrics [16], [17]. I2 is given by the formula and it is a measure of the percentage of total variation across studies due to heterogeneity beyond chance. Therefore, I2 takes values between 0–100%. Values over 50% indicate large heterogeneity. I2 can be estimated along with its confidence intervals and the confidence intervals are wider when a meta-analysis includes few studies [20]. The confidence intervals for I2 can be calculated with different methods (described in detail in [17]). Confidence intervals usually can be very large, unless many studies are available, and this is another indication that one has to be cautious about claiming homogeneity (even when I2 is zero). Overall, there can be large uncertainty in a meta-analysis about the presence or not and the extent of between-study heterogeneity. Strong inferences about heterogeneity or lack thereof may be a common misconception when limited data are available.
