On the Optimality of Inference on the Mean Outcome under Optimal Treatment Regime
报告专家：郭心舟（香港科技大学）
报告时间：2024年5月23日（星期四）下午16：00-17：00
报告地点：四川大学数学学院西202报告厅
报告摘要：When an optimal treatment regime (OTR) is considered, we need to address the question of how good the OTR is in a valid and efficient way. The classical statistical inference applied to the mean outcome under the OTR, assuming the OTR is the same as the estimated OTR, might be biased when the regularity assumption that the OTR is unique is violated. Although several methods have been proposed to allow nonregularity in inference on the mean outcome under the OTR, the optimality of such inference is unclear due to challenges in deriving semiparametric efficiency bounds under nonregularity. In this paper, we address the bias issue induced by nonregularity via adaptive smoothing over the estimated OTR and develop a valid inference procedure on the mean outcome under the OTR whenever the regularity assumption is satisfied or not. We establish the optimality of the proposed method by deriving a lower bound of the asymptotic variance for a general class of valid estimators to the mean outcome under the OTR and showing that our proposed estimator achieves the lower bound. The considered class of the estimator includes the regular estimator, the robust asymptotic linear unbiased estimator and the current state-of-the-art approach, and the derived lower bound of the asymptotic variance can be viewed as an extension of the classical semiparametric theory to a more general scenario allowing nonregularity. The merit of the proposed method is demonstrated by re-analyzing the ACTG 175 trial.
专家简介：Xinzhou Guo is an Assistant Professor in the Department of Mathematics at the Hong Kong University of Science and Technology. He received his B.S. in Applied Mathematics from Peking University and Ph.D. in Statistics from the University of Michigan. Prior to joining HKUST in 2021, he did a postdoc at Harvard University. His main research interests are subgroup analysis, resampling methods, precision medicine and regulatory decision-making.
邀请人：周杰
