主题：Regression analysis of doubly truncated data
主讲人：郁文教授（复旦大学）
主持人：刘晓玉（暨南大学）
会议工具：腾讯会议（ID：399-071-720，密码：202208）
会议时间：2022年10月26日（周三）下午2：30—3：30
摘要
Doubly truncated data are found in astronomy, econometrics, and survival analysis literature. They arise when each observation is confined to an interval, that is, only those which fall within their respective intervals are observed along with the intervals. Unlike the one-sided truncation that can be handled by counting process-based approach, doubly truncated data are much more difficult to handle. In their analysis of an astronomical dataset, Efron and Petrosian (1999) proposed some nonparametric methods for doubly truncated data. Motivated by their approach, as well as by the work of Bhattacharya et al. (1983) for right truncated data, we propose a general method for estimating the regression parameter when the dependent variable is subject to the double truncation. It extends the Mann–Whitney-type rank estimator and can be computed easily by existing software packages. Weighted rank estimation is also considered for improving estimation efficiency. We show that the resulting estimators are consistent and asymptotically normal. Resampling schemes are proposed with large sample justification for approximating the limiting distributions. The quasar data in Efron and Petrosian (1999) and an AIDS incubation data are analyzed by the new method. Simulation results show that the proposed method works well.
主讲人简介
郁文，现任复旦大学管理学院、统计与数据科学系教授、系主任、博士生导师。主要从事生存分析、半参数模型、两阶段抽样设计、半监督推断等研究，在Journal of the American Statistical Association、Journal of the Royal Statistical Society B 、Scandinavian Journal of Statistics 、Statistica Sinica等国内外学术期刊发表论文三十余篇，主持多项国家自然科学基金、教育部博士点基金研究工作。担任中国现场统计研究会、全国工业统计学教学研究会、上海市质量技术应用统计学会理事。
