The supplementary material provides a comprehensive overview of research articles that describe or compare methods for estimating the between-study variance and its uncertainty in meta-analyses. The search strategy used to identify these articles is detailed, focusing on terms related to heterogeneity, consistency, between-study variance, meta-analysis, and various estimation methods. The material includes a summary table (Appendix Table 1) that outlines different scenarios and estimation methods used in simulation and empirical studies. These methods include the DerSimonian and Laird (DL), Hedges and Olkin (HO), restricted maximum likelihood (REML), shrinkage (SJ), penalized likelihood (PM), and others. The table specifies the number of studies ($k$), effect sizes ($logOR$, $logRR$, $MD$, $SMD$, $HR$), and between-study variance ($\tau^2$) used in each study. Additional tables (Appendix Table 2 and Appendix Table 3) compare the properties of different estimators for between-study variance and confidence interval (CI) estimation methods, respectively. These tables provide a detailed comparison of bias, mean squared error (MSE), and coverage probability, with references to the studies that conducted these comparisons. The references section lists the key studies that were used to develop and evaluate these estimation methods, providing a comprehensive resource for further research and application.The supplementary material provides a comprehensive overview of research articles that describe or compare methods for estimating the between-study variance and its uncertainty in meta-analyses. The search strategy used to identify these articles is detailed, focusing on terms related to heterogeneity, consistency, between-study variance, meta-analysis, and various estimation methods. The material includes a summary table (Appendix Table 1) that outlines different scenarios and estimation methods used in simulation and empirical studies. These methods include the DerSimonian and Laird (DL), Hedges and Olkin (HO), restricted maximum likelihood (REML), shrinkage (SJ), penalized likelihood (PM), and others. The table specifies the number of studies ($k$), effect sizes ($logOR$, $logRR$, $MD$, $SMD$, $HR$), and between-study variance ($\tau^2$) used in each study. Additional tables (Appendix Table 2 and Appendix Table 3) compare the properties of different estimators for between-study variance and confidence interval (CI) estimation methods, respectively. These tables provide a detailed comparison of bias, mean squared error (MSE), and coverage probability, with references to the studies that conducted these comparisons. The references section lists the key studies that were used to develop and evaluate these estimation methods, providing a comprehensive resource for further research and application.