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A copula model for bivariate hybrid censored survival data with application to the MACS study
Authors:Suhong Zhang  Ying Zhang  Kathryn Chaloner  Jack T. Stapleton
Affiliation:1.Division of Biostatistics,Edwards Lifesciences,Irvine,USA;2.Department of Biostatistics,University of Iowa,Iowa City,USA;3.Department of Internal Medicine,University of Iowa and Iowa City VA Medical Center,Iowa City,USA
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.
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