BMI Seminar with Guanhua Chen

Current literature focuses on deriving individualized treatment rules (ITRs) from a single source population. We consider the setting when the source population may differ from the target population of interest. This problem is also related to transfer learning in the machine learning community. We assume subject covariates are available from both populations, but treatment and outcome data are only available from the source population.