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用于双变量混合删失生存数据的一个copula模型及其在MACS研究中的应用

A copula model for bivariate hybrid censored survival data with application to the MACS study.

作者信息

Zhang Suhong, Zhang Ying, Chaloner Kathryn, Stapleton Jack T

机构信息

Division of Biostatistics, Edwards Lifesciences, One Edwards Way, Irvine, CA 92612, USA.

出版信息

Lifetime Data Anal. 2010 Apr;16(2):231-49. doi: 10.1007/s10985-009-9139-z.

Abstract

A copula model for bivariate survival data with hybrid censoring is proposed to study the association between survival time of individuals infected with HIV and persistence time of infection with an additional virus. Survival with HIV is right censored and the persistence time of the additional virus is subject to interval censoring case 1. A pseudo-likelihood method is developed to study the association between the two event times under such hybrid censoring. Asymptotic consistency and normality of the pseudo-likelihood estimator are established based on empirical process theory. Simulation studies indicate good performance of the estimator with moderate sample size. The method is applied to a motivating HIV study which investigates the effect of GB virus type C (GBV-C) co-infection on survival time of HIV infected individuals.

摘要

提出了一种用于具有混合删失的双变量生存数据的Copula模型,以研究感染HIV个体的生存时间与另一种病毒感染持续时间之间的关联。HIV生存情况为右删失,另一种病毒的持续时间属于区间删失情况1。开发了一种伪似然方法来研究这种混合删失下两个事件时间之间的关联。基于经验过程理论建立了伪似然估计量的渐近一致性和正态性。模拟研究表明,在中等样本量下该估计量具有良好的性能。该方法应用于一项具有启发性的HIV研究,该研究调查了丙型肝炎病毒(GBV-C)合并感染对HIV感染个体生存时间的影响。

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引用本文的文献

本文引用的文献

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Effect of early and late GB virus C viraemia on survival of HIV-infected individuals: a meta-analysis.
HIV Med. 2006 Apr;7(3):173-80. doi: 10.1111/j.1468-1293.2006.00366.x.
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