題 目：Accelerated Failure Time Intensity Frailty Model for Recurrent Events Data
時 間：2015年7月6日（周一）14:00
地 點：6號樓415教室
主講人：張佳佳博士
主辦單位：數學與統計學院
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.
主講人簡介
張佳佳， 2007年畢業于加拿大紀念大學(Memorial University)，獲博士學位（生物統計），現任美國南卡羅來納大學流行病與生物統計系終身副教授。主要從事生存分析、半參數估計方法等方面的理論與應用研究。研究方向包括生存模型、空間生存模型、混合治愈模型、脆弱模型、樣本容量計算等。張佳佳博士在國際核心統計學學術期刊上發表論文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。主持美國衛生研究院(National Institutes of Health)項目5項。多次在國際學術會議作邀請報告及擔任國際會議分會主席。擔任國際學術期刊Journal of Biometrics & Biostatistics, Neurosurgery編委，多種國際核心學術期刊的審稿人，美國統計學會、中國國際統計學會、加拿大統計協會會員。
