Introduces partial identification bounds and a double-robust SurvB-learner meta-learner for estimating robust CATE in survival analysis under informative censoring.
Sharp sensitivity analysis for inverse propensity weighting via quantile balancing.Journal of the American Statistical Association, 118(544):2645–2657, 2023
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Assessing the robustness of heterogeneous treatment effects in survival analysis under informative censoring
Introduces partial identification bounds and a double-robust SurvB-learner meta-learner for estimating robust CATE in survival analysis under informative censoring.