统计与管理学院2015年学术报告第35期
【主 题】 Accelerated Failure Time Intensity Frailty Model for Recurrent Events Data
【报告人】 Zhang Jiajia 博士
Department of Epidemiology and Biostatistics, University of South Carolina
【时 间】 2015年7月9日（星期四）14:30－15:30
【地 点】 上海财经大学统计与管理学院大楼1208室
【语 言】 英文
【摘 要】 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.
