题  目：Accelerated Failure Time Intensity Frailty Model for Recurrent Events Data

时  间：2015年7月6日（周一）14:00

地  点：6号楼415教室

主讲人：张佳佳博士

主办单位：数学与统计学院

Abastract：In this article we propose an accelerated failure time (AFT) intensity frailty model for recurrent events data and develop a kernel-smoothing-based EM algorithm for estimating the regression coefficients and the baseline intensity function. The variance of the resulting estimator for regression parameters is obtained by a numerical differentiation method. The asymptotic properties of our estimators, including consistency, asymptotic normality and semiparametric efficiency can be established using empirical process theory. Simulation studies are conducted to evaluate the finite sample performance of the proposed estimator under practical settings and demonstrate the efficiency gain over the Gehan rank estimator based on the AFT model for counting process. Our method is further illustrated with an application to a bladder tumor recurrence data.

主讲人简介

张佳佳， 2007年毕业于加拿大纪念大学(Memorial University)，获博士学位（生物统计），现任美国南卡罗来纳大学流行病与生物统计系终身副教授。主要从事生存分析、半参数估计方法等方面的理论与应用研究。研究方向包括生存模型、空间生存模型、混合治愈模型、脆弱模型、样本容量计算等。张佳佳博士在国际核心统计学学术期刊上发表论文30余篇，如Biometrka, Biometrics, Journal of Applied Statistics, Biometrical Journal, Lifetime Data Analysis, Statistical Methods in Medical Research，Communication in Statistics, Computational Statistics and Data Analysis，Statistics in Medicine， Statistics and Probability Letters等。主持美国卫生研究院(National Institutes of Health)项目5项。多次在国际学术会议作邀请报告及担任国际会议分会主席。担任国际学术期刊Journal of Biometrics & Biostatistics, Neurosurgery编委，多种国际核心学术期刊的审稿人，美国统计学会、中国国际统计学会、加拿大统计协会会员。