报告题目：A rank-based approach to estimating monotone individualized two treatment regimes
报 告 人：张海祥 副教授 天津大学
报告时间：2020年7月3日 08:30-09:30
报告地点：腾讯会议
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校内联系人：程建华 chengjh@jlu.edu.cn
会议ID：792 829 153
会议密码：0703
报告摘要：
Developing effective individualized treatment rules (ITRs) for diseases is an important goal of clinical research. Much effort has been devoted to estimating individualized treatment effects in the recent literature. However, there have not been systematic studies on the robust inference for individualized treatment effects when there exist potential outliers. We propose a monotone ITR in the framework of a semiparametric generalized regression with two treatments and estimate the treatment effects via a smoothed maximum rank correlation procedure. We provide sufficient conditions under which the proposed estimator has an asymptotically normal distribution whose variance can be consistently estimated based on a resampling procedure. We evaluate the finite-sample properties of our proposed approach via simulation studies. We also illustrate the proposed method by applying it to a data set from an AIDS clinical trials study
报告人简介：
张海祥，天津大学应用数学中心副教授，硕士生导师。2012年于吉林大学获得博士学位，中国科学院和美国西北大学博士后。主要研究方向包括；中介分析、精准医学、微生物组数据分析、时间序列分析等。已经在Statistica Sinica、Bioinformatics、Computational Statistics and Data Analysis、Journal of Time Series Analysis、Journal of Multivariate Analysis等国际期刊上发表学术论文24篇。
