当前位置: 首页 > 学术活动 > 正文
Inference on Semiparametric Transformation Model with General Interval-censored Failure Time Data
时间:2019年01月18日 15:05 点击数:

报告人:王培洁

报告地点:数学与统计楼415室

报告时间:2019年01月17日星期四17:15-18:00

邀请人:

报告摘要:

Failure time data occur in many areas and in various censoring forms and many models have been proposed for their regression analysis such as the proportional hazards model and the proportional odds model. Another choice that has been discussed in the literature is a general class of semiparametric transformation models, which include the two models above and many others as special cases. In this paper, we consider this class of models when one faces a general type of censored data, case K informatively censored data, for which there does not seem to exist an established inference procedure. For the problem, we present a two-step estimation procedure that is quite flexible and can be easily implemented, and the consistency and asymptotic normality of the proposed estimators of regression parameters are established. In addition, an extensive simulation study is conducted and suggests that the proposed procedure works well for practical situations. An application is also provided.

主讲人简介:

王培洁,吉林大学讲师,上海财经大学博士后,2015年博士毕业,从事生存分析区间删失数据的研究,发表SCI论文十篇,主持国家青年基金一项。2016年2017年连续两年获得ICSA中国会议青年学者奖。

©2019 东北师范大学数学与统计学院 版权所有

地址:吉林省长春市人民大街5268号 邮编:130024 电话:0431-85099589 传真:0431-85098237