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

Suhong Zhang; Ying Zhang; Kathryn Chaloner; Jack Stapleton

doi:10.1007/s10985-009-9139-z

Back

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

Journal article

Peer reviewed

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

Suhong Zhang, Ying Zhang, Kathryn Chaloner and Jack Stapleton

Lifetime data analysis, Vol.16(2), pp.231-249

04/2010

DOI: 10.1007/s10985-009-9139-z

PMCID: PMC3567926

PMID: 19921432

Files and links (1)

url

https://www.ncbi.nlm.nih.gov/pmc/articles/3567926View

Open Access

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.

Statistics

Current status data

Copula

Empirical process

Bivariate survival model

Statistics for Life Sciences, Medicine, Health Sciences

Kendall’s τ

Statistics, general

Association measure

Statistics for Business/Economics/Mathematical Finance/Insurance

Operations Research/Decision Theory

Right censored data

Quality Control, Reliability, Safety and Risk

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 USA
Ying Zhang - Department of Biostatistics University of Iowa C22 GH, 200 Hawkins Drive Iowa City IA 52242 USA
Kathryn Chaloner - Department of Biostatistics University of Iowa C22 GH, 200 Hawkins Drive Iowa City IA 52242 USA
Jack 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
DOI: 10.1007/s10985-009-9139-z
PMID: 19921432
PMCID: PMC3567926
NLM abbreviation: Lifetime Data Anal
ISSN: 1380-7870
eISSN: 1572-9249
Publisher: Springer US
Language: English
Date published: 04/2010
Academic Unit: Microbiology and Immunology; Infectious Diseases; Internal Medicine
Record Identifier: 9984094543602771

Metrics

65 Record Views

7 Times Cited - Web of Science