Optimal individualized treatment rules try to assign the best treatment to every individual, but it may be very sensitive to unmeasured confounding bias for groups of people exhibiting small treatment effect in the observational study. We give a …
In a special workshop in ACIC 2018, we were invited to analyze a simulated dataset to detect treatment effect heterogeneity. This article reports our results presented in the workshop. We also tried out more recent selective inference methods based …
We approach the heterogeneous treatment effect problem in a novel way. Instead of trying to obtain the optimal treatment regime, we seek an interpretable model for effect modification using the recently developed selective inference framework.