Semiparametric efficient estimation for additive hazards regression with case II interval-censored survival data.

Lifetime Data Analysis
Baihua HeXingqiu Zhao

Abstract

Interval-censored data often arise naturally in medical, biological, and demographical studies. As a matter of routine, the Cox proportional hazards regression is employed to fit such censored data. The related work in the framework of additive hazards regression, which is always considered as a promising alternative, remains to be investigated. We propose a sieve maximum likelihood method for estimating regression parameters in the additive hazards regression with case II interval-censored data, which consists of right-, left- and interval-censored observations. We establish the consistency and the asymptotic normality of the proposed estimator and show that it attains the semiparametric efficiency bound. The finite-sample performance of the proposed method is assessed via comprehensive simulation studies, which is further illustrated by a real clinical example for patients with hemophilia.

References

Sep 14, 2000·Biometrics·W B Goggins, D M Finkelstein
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Jan 17, 2003·Statistics in Medicine·Guadalupe GómezStephen W Lagakos
Feb 27, 2003·Lifetime Data Analysis·Linxiong Li, Zongwei Pu
Sep 28, 2007·Lifetime Data Analysis·Lianming WangXingwei Tong
Nov 28, 2007·Statistics in Medicine·Xiao Song, Shuangge Ma
Oct 1, 2009·Journal of Statistical Computation and Simulation·Wei ZhangJack T Stapleton

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