Journal article
A copula model for bivariate hybrid censored survival data with application to the MACS study
Lifetime data analysis, Vol.16(2), pp.231-249
04/2010
DOI: 10.1007/s10985-009-9139-z
PMCID: PMC3567926
PMID: 19921432
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.
Details
- Title: Subtitle
- A copula model for bivariate hybrid censored survival data with application to the MACS study
- Creators
- Suhong Zhang - Division of Biostatistics Edwards Lifesciences One Edwards Way Irvine CA 92612 USAYing Zhang - Department of Biostatistics University of Iowa C22 GH, 200 Hawkins Drive Iowa City IA 52242 USAKathryn Chaloner - Department of Biostatistics University of Iowa C22 GH, 200 Hawkins Drive Iowa City IA 52242 USAJack Stapleton - Department of Internal Medicine University of Iowa and Iowa City VA Medical Center SW54-15 GH, 200 Hawkins Drive Iowa City IA 52242 USA
- Resource Type
- Journal article
- Publication Details
- Lifetime data analysis, Vol.16(2), pp.231-249
- Publisher
- Springer US
- DOI
- 10.1007/s10985-009-9139-z
- PMID
- 19921432
- PMCID
- PMC3567926
- ISSN
- 1380-7870
- eISSN
- 1572-9249
- Language
- English
- Date published
- 04/2010
- Academic Unit
- Microbiology and Immunology; Infectious Diseases; Internal Medicine
- Record Identifier
- 9984094543602771
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