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304am永利集团、所2020年系列学术活动(第22场):丁洁丽 副教授 武汉大学

发表于: 2020-06-01   点击: 

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。