Investigating between-study variability in individual participant data meta-analysis (IPD-MA) is an important step in interpreting findings. Although heterogeneity can be quantified by conventional I2 through a two-stage approach, it does not take full advantage of the individual level data. A one-stage approach has been proposed to obtain a simulation-based I2, which showed better performance than the conventional approaches in a simulation study. To compare the different methods of quantifying heterogeneity, we present a IPD-MA study of determining drug efficacy with binary outcomes in the treatment of multidrug-resistant tuberculosis. Both one- and two-stage approaches were performed to estimate various measures of heterogeneity including τ2, R, the prediction interval, and I2. The advantages and disadvantages of each approach are discussed.