Takkouche, BahiKhudyakov, PolynaCosta-Bouzas, JuliánSpiegelman, Donna2019-09-212013Takkouche, B., P. Khudyakov, J. Costa-Bouzas, and D. Spiegelman. 2013. “Confidence Intervals for Heterogeneity Measures in Meta-Analysis.” American Journal of Epidemiology 178 (6): 993–1004. https://doi.org/10.1093/aje/kwt060.0002-92621476-6256http://nrs.harvard.edu/urn-3:HUL.InstRepos:41384717Two methods of quantifying heterogeneity between studies in meta-analysis were studied. One method quantified the proportion of the total variance of the effect estimate due to variation between studies (R-I), and the other calibrated the variance between studies to the size of the effect itself through a between-study coefficient of variation (CVB). Bootstrap and asymptotic confidence intervals for R-I and CVB were derived and evaluated in an extensive simulation study that covered a wide range of scenarios likely to be encountered in practice. The best performance was given by asymptotic Wald confidence intervals developed for R-I and CVB. The use of these heterogeneity measures together with their confidence intervals was illustrated in 5 typical meta-analyses. A new user-friendly SAS macro (SAS Institute, Inc., Cary, North Carolina) is provided to implement these methods for routine use and can be downloaded at the last author's website.en-USConfidence Intervals for Heterogeneity Measures in Meta-analysisJournal Article2019-09-2110.1093/aje/kwt060