主 题：a semiparametrically effcient estimator of the time-varying effects for survivaldata with time-dependent treatment
主讲人：费哲博士
主持人：林华珍教授
时 间：2015年7月14日下午3点-4点
地 点：通博楼B212学术会议室
主办单位：统计研究中心 统计学院 科研处
主讲人简介：
费哲博士,2012年毕业于北京大学,现为密歇根大学博士.2013年在密歇根大学获得Richard H. Cornell Scholarship.
内容提要：
The timing of time-dependent treatment |e.g., when to perform kidney transplantation|is an important factor for evaluating treatment effcacy. A naive comparison between the treatment and nontreatment groups, while ignoring the timing of treatment, typically yields results that might biasedly favor the treatment group, as only patients who survive long enough will get treated. On the other hand, studying the effect of time-dependent treatment is often complex, as it involves modeling treatment history and accounting for the possible time-varying nature of the treatment effect. We propose a varying-coeffcient Cox model that investigates the effcacy of time-dependent treatment by utilizing a global partial likelihood, which renders appealing statistical properties, including consistency, asymptotic normality and semiparametric effciency. Extensive simulations verify the ffnite sample performance, and we apply the proposed method to study the effcacy of kidney transplantation for end-stage renal disease patients in the U.S. Scientiffc Registry of
Transplant Recipients (SRTR).
