报告题目：A Weighted Estimator for Cox Regression with Parameter Constraints in Case-Cohort Studies
报 告 人：丁洁丽 副教授 武汉大学
报告时间：2020年6月3日下午3:00—4:00
报告地点：腾讯会议 会议ID：432 289 215
会议密码：200603
或链接：https://meeting.tencent.com/s/jvu3xv901zk4
校内联系人：王培洁 wangpeijie@jlu.edu.cn
报告摘要：
A case-cohort design is proposed as a means of reducing cost in large cohort studies. In modeling process, case-cohort studies can acquire more efficiency from taking parameter constraints into consideration. In this paper, we fit the Cox model with constraints to case-cohort data and develop an inverse probability weighted approach for regression analysis. We establish asymptotic properties by applying a Lagrangian approach based on Karush-Kuhn-Tucker conditions. We develop a constrained minorization-maximization algorithm for the implementation of the proposed estimator. Simulation studies are conducted to assess the finite-sample performance. A data example from a Wilms tumor study is analyzed to demonstrate the application of the proposed method.
报告人简介：
丁洁丽，武汉大学数学与统计学院副教授，硕士生导师。2006年武汉大学概率统计专业获博士学位，之后一直在武汉大学任教。研究方向为生存分析。近年来在国际知名期刊上发表多篇高水平论文。
