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

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

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)231-249
Number of pages19
JournalLifetime Data Analysis
Volume16
Issue number2
DOIs
StatePublished - Apr 2010
Externally publishedYes

ASJC Scopus subject areas

  • Applied Mathematics

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