报告题目：Estimating the Quantile Medical Cost under Time-dependent Covariates and Right Censored Time-to-event Variable Based on a State Process

主 讲 人：刘 秀 芳

单 位：太原理工大学

时 间：9月5日16:30

腾 讯 ID：884 589 867

密 码：123456

摘 要：

Estimating the medical costs from disease diagnosis to a terminal event is of immense interest to researchers. However, most of existing literature on such research focused on the estimation of cumulative mean function (CMF) for history process. In this paper, the combined scheme of both inverse probability of censoring weighting (IPCW) technique and longitudinal quantile regression model is used to develop a novel procedure to the estimation of cumulative quantile function (CQF) based on history process with time-dependent covariates and right censored time-to-event variable. The consistency of proposed estimator is derived. The extensive simulation study is conducted to investigate the performance of the estimator given in this paper. A medical cost data from a multicenter automatic defibrillator implantation trial (MADIT) is analyzed to illustrate the application of developed method.

简 介：

刘秀芳，太原理工大学数学学院讲师。2020年6月毕业于吉林大学数学学院。师从王德辉教授从事于时间序列，保险精算等方向的研究。2018年在加拿大里贾纳大学访学一年。目前，主要研究方向为时间序列和生物统计。在国际SCI期刊上发表论文三篇。