報告題目：A Weighted Estimator for Cox Regression with Parameter Constraints in Case-Cohort Studies
報 告 人：丁潔麗 副教授 武漢大學
報告時間：2020年6月3日下午3:00—4:00
報告地點：騰訊會議 會議ID：432 289 215
會議密碼：200603
或鍊接：https://meeting.tencent.com/s/jvu3xv901zk4
校内聯系人：王培潔 wangpeijie@jlu.edu.cn
報告摘要：
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.
報告人簡介：
丁潔麗，武漢大學數學與統計學院副教授，碩士生導師。2006年武漢大學概率統計專業獲博士學位，之後一直在武漢大學任教。研究方向為生存分析。近年來在國際知名期刊上發表多篇高水平論文。
