数学与统计学院学术报告[2020] 141号

(高水平大学建设系列报告494号)

报告题目: Regression analysis of informatively interval-censored failure time data with semiparametric linear transformation model

报告人：赵世舜 教授  （吉林大学）

报告时间：12月9日21:20-22:20

报告地点：腾讯会议 763 553 089　　　　　　　　　　　　　　　　　　　　　

报告内容：

Regression analysis of interval-censored failure time data with noninformative censoring has been widely investigated and many methods have been proposed. Sometimes the mechanism behind the interval censoring may be informative and several approaches have also been developed for this latter situation. However, all of these existing methods are for single models and it is well known that in many situations, one may prefer more flexible models. Corresponding to this, the linear transformation model is considered and a maximum likelihood estimation method is established. In the proposed method, the association between the failure time of interest and the censoring time is modelled by the copula model, and the involved nonparametric functions are approximated by spline functions. The large sample properties of the proposed estimators are derived. Numerical results show that the proposed method performs well in practical application. Besides, a real data example is presented for the illustration.

报告人简历：

赵世舜 吉林大学数学学院教授。毕业于吉林大学数学学院，获概率论与数理统计专业博士学位，2013-2014美国University of Missouri 统计系访问。主持或参与多项国家项目，在国内外高水平杂志上发表论文20余篇。

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　　　　　　 　　　　　　　　　　　　　　　数学与统计学院

             　　　　　　　　　　　　　2020年12月9日