Regression analysis of doubly censored failure time data with frailty.
Biometrics
; 62(2): 458-64, 2006 Jun.
Article
em En
| MEDLINE
| ID: mdl-16918909
ABSTRACT
In doubly censored failure time data, the survival time of interest is defined as the elapsed time between an initial event and a subsequent event, and the occurrences of both events cannot be observed exactly. Instead, only right- or interval-censored observations on the occurrence times are available. For the analysis of such data, a number of methods have been proposed under the assumption that the survival time of interest is independent of the occurrence time of the initial event. This article investigates a different situation where the independence may not be true with the focus on regression analysis of doubly censored data. Cox frailty models are applied to describe the effects of covariates and an EM algorithm is developed for estimation. Simulation studies are performed to investigate finite sample properties of the proposed method and an illustrative example from an acquired immune deficiency syndrome (AIDS) cohort study is provided.
Buscar no Google
Base de dados:
MEDLINE
Assunto principal:
Análise de Regressão
/
Biometria
Tipo de estudo:
Diagnostic_studies
/
Etiology_studies
/
Observational_studies
/
Prognostic_studies
/
Risk_factors_studies
Limite:
Humans
/
Male
Idioma:
En
Ano de publicação:
2006
Tipo de documento:
Article