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A semiparametrically efficient estimator of the time-varying effects for survival data with time-dependent treatment
澳门新葡8455最新网站:2015年08月02日 00:00 点击数:

报告人:林华珍

报告地点:澳门新葡8455最新网站501室

报告澳门新葡8455最新网站:2015年05月26日星期二16:00-17:00

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报告摘要:

The timing of time-dependent treatment---e.g., when to perform kidney transplantation---is an important factor for evaluating treatment efficacy. 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-coefficient Cox model that investigates the efficacy of time-dependent treatment by utilizing a global partial likelihood, which renders appealing statistical properties, including consistency, asymptotic normality and semiparametric efficiency. Extensive simulations verify the finite sample performance, and we apply the proposed method to study the efficacy of kidney transplantation for end-stage renal disease patients in the U.S. Scientific Registry of Transplant Recipients (SRTR).

主讲人概况:

林华珍,西南财经大学统计新葡京最新官网教授,美国华盛顿大学生物统计系博士后,四川大学学士、硕士、博士。 2011年获国家杰出青年科学基金资助,2010入选教育部新世纪优秀人才支撑计划, 第十一批四川省学术和技术带头人。 主要研究:转换模型、非参数方法、生存数据分析、ROC方法、偏态数据分析、捕获-再捕获数据分析、相关数据分析、联合模型。论文发表在包括《The Annals of Statistics》、《Journal of the Royal Statistical Society Series B》、《Biometrika》及《Biometrics》等学术刊物上。 目前为国际统计学期刊《Biometrics》、《Scandinavian Journal of Statistics》Associate Editor;国内核心学术期刊《应用概率统计》、《系统科学与数学》、《数理统计与管理》编委;国际概率论与数理统计学会中国分会(IMS-China)、国际生物统计中国分会(IBS-CHINA)、泛华统计协会(ICSA)常务委员及国内包括中国概率统计学会在内的六个学会常务理事。

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