报告题目：Inference for mark-specific causal effects
主讲人：曲连强副教授（华中师范大学）
时间：2026年6月18日（周四）10:00 a.m.
形式：线上讲座
腾讯会议：739-642-115
主办单位：统计与数学学院
摘要：
This paper presents a framework for causal inference in the presence of censored data, where the failure time is marked by a continuous variable referred to as a mark. The mark is observed after treatment and is not meaningful when the failure time is censored. In addition, due to the continuous nature of the marks, observations at each given mark are sparse. These facts make the identification and estimation of causality a challenging task. To address these issues, we define a new mark-specific treatment effect within the potential outcomes framework and characterize its identifying conditions. We then propose a local smoothing estimator for the causal effects and establish its asymptotic properties. We further develop testing methods to evaluate whether the treatment has an effect on the failure time when controlling the values of the mark at certain points or within a defined interval, and develop a Gaussian approximation method to obtain the critical values. We evaluate our method using simulation studies as well as a real dataset from the Antibody Mediated Prevention trials.
主讲人简介：
曲连强，华中师范大学数学与统计学学院副教授，国家级青年人才。主要研究方向为生存分析和大规模复杂数据统计推断。现已发表学术论文18篇，包括JASA、Biometrika，JMLR 以及JBES等。主持国家自然科学基金面上项目和青年项目各1项。
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