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Joint Analysis of Interval-censored failure Time Data and Panel Count Data
2018-06-04 00:00:00

报告题目:

Joint Analysis of Interval-censored failure Time Data and Panel Count Data

报 告 人:

孙建国 教授(美国密苏里大学统计系)

报告时间:

2018年06月07日 09:30--10:30

报告地点:

数学院二楼报告厅

报告摘要:

Interval-censored failure time data and panel count data are two types of incomplete data that commonly occur in event history studies and many methods have been developed for their analysis separately (Sun, 2006; Sun and Zhao, 2013). Sometimes one may be interested in or need to conduct their joint analysis such as in the clinical trials with composite endpoints, for which it does not seem to exist an established approach in the literature. In this paper , a sieve maximum likelihood approach is developed for the joint analysis and in the proposed method, Bernstein polynomials are used to approximate unknown functions. The asymptotic properties of the resulting estimators are established and in particular, the proposed estimators of regression parameters are shown to be semiparametrically efficient. In addition, an extensive simulation study was conducted and the proposed method is applied to a set of real data arising from a skin cancer study.