We should stress that estimation of between-study heterogeneity carries considerable uncertainty and in the typical situation it would be impossible to have a large number of large studies to fully power detection and accurate estimation of heterogeneity. Moreover, breaking down populations to sub-studies may sometimes lead to loss of estimated between-study heterogeneity, if the sub-studies are small and their confidence intervals of effects are very large. However, this would offer misleading reassurance that no heterogeneity exists. While the number of datasets may increase by such splitting, each dataset would have very limited, inconclusive information about the magnitude of the effect and it would again be very difficult to show the between-study heterogeneity, even if present.
