Multiple imputation methods for nonparametric inference on cumulative incidence with missing cause of failure.
Stat Med
; 33(26): 4605-26, 2014 Nov 20.
Article
en En
| MEDLINE
| ID: mdl-25043107
ABSTRACT
We propose a nonparametric approach for cumulative incidence estimation when causes of failure are unknown or missing for some subjects. Under the missing at random assumption, we estimate the cumulative incidence function using multiple imputation methods. We develop asymptotic theory for the cumulative incidence estimators obtained from multiple imputation methods. We also discuss how to construct confidence intervals for the cumulative incidence function and perform a test for comparing the cumulative incidence functions in two samples with missing cause of failure. Through simulation studies, we show that the proposed methods perform well. The methods are illustrated with data from a randomized clinical trial in early stage breast cancer.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Intervalos de Confianza
/
Funciones de Verosimilitud
/
Modelos de Riesgos Proporcionales
/
Incidencia
/
Interpretación Estadística de Datos
Tipo de estudio:
Clinical_trials
/
Incidence_studies
/
Prognostic_studies
/
Risk_factors_studies
Límite:
Female
/
Humans
Idioma:
En
Revista:
Stat Med
Año:
2014
Tipo del documento:
Article
País de afiliación:
Corea del Sur