A0265
Title: An alternative measure for quantifying the heterogeneity in meta-analysis
Authors: Tiejun Tong - Hong Kong Baptist University (Hong Kong) [presenting]
Abstract: Quantifying the heterogeneity is an important issue in meta-analysis, and among the existing measures, the $I^2$ statistic is most commonly used. A simple example first illustrates that the $I^2$ statistic is heavily dependent on the study sample sizes, mainly because it is used to quantify the heterogeneity between the observed effect sizes. To reduce the influence of sample sizes, an alternative measure is introduced that aims to directly measure the heterogeneity between the study populations involved in the meta-analysis. A new estimator is further proposed, namely the $I_A^2$ statistic, to estimate the newly defined measure of heterogeneity. For practical implementation, the exact formulas of the $I_A^2$ statistic are also derived under two common scenarios with the effect size as the mean difference (MD) or the standardized mean difference (SMD). Simulations and real data analysis demonstrate that the $I_A^2$ statistic provides an asymptotically unbiased estimator for the absolute heterogeneity between the study populations, and it is also independent of the study sample sizes as expected.
