Assessing the fit of parametric cure models.
Biostatistics
; 14(2): 340-50, 2013 Apr.
Article
em En
| MEDLINE
| ID: mdl-23197383
ABSTRACT
Survival data can contain an unknown fraction of subjects who are "cured" in the sense of not being at risk of failure. We describe such data with cure-mixture models, which separately model cure status and the hazard of failure among non-cured subjects. No diagnostic currently exists for evaluating the fit of such models; the popular Schoenfeld residual (Schoenfeld, 1982. Partial residuals for the proportional hazards regression-model. Biometrika 69, 239-241) is not applicable to data with cures. In this article, we propose a pseudo-residual, modeled on Schoenfeld's, to assess the fit of the survival regression in the non-cured fraction. Unlike Schoenfeld's approach, which tests the validity of the proportional hazards (PH) assumption, our method uses the full hazard and is thus also applicable to non-PH models. We derive the asymptotic distribution of the residuals and evaluate their performance by simulation in a range of parametric models. We apply our approach to data from a smoking cessation drug trial.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Análise de Sobrevida
/
Modelos Estatísticos
Tipo de estudo:
Clinical_trials
/
Risk_factors_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2013
Tipo de documento:
Article