Ensemble and calibration multiply robust estimation for quantile treatment effectXiaohong He & Lei Wang
Quantile treatment effects can be important causal estimands in the evaluation of biomedical treatments or interventions for health outcomes such as birthweight and medical cost. However, the existing estimators require either a propensity score model or a conditional density vector model is correctly specified, which is difficult to verify in practice. In this paper, we allow multiple models for propensity score and conditional density vector, then construct a class of calibration estimators based on multiple...
1 citation reported since publication in 2021.
This data repository is not currently reporting usage information. For information on how your repository can submit usage information, please see our documentation.