Confidence Bands for the Survival Function Using a Weibull Regression Model in Presence of Arbitrary Censoring
Usually, the exact time at which an event occurs cannot be observed for several reasons; for instance, it is not possible to constantly monitor a characteristic of interest. This generates a phenomenon known as censoring that can be classified as having a left censor, right censor or interval censo...
- Autores:
-
Jaramilo Elorza, Mario César
Salazar Uribe, Juan Carlos
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2017
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/66507
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/66507
http://bdigital.unal.edu.co/67535/
- Palabra clave:
- 51 Matemáticas / Mathematics
31 Colecciones de estadística general / Statistics
Survival analysis
Biostatistical
Confidence bands
Goodness of fit
Regression models
Simulation
análisis de supervivencia
bandas de confianza
bioestadística
modelos de regresión
simulación.
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
Summary: | Usually, the exact time at which an event occurs cannot be observed for several reasons; for instance, it is not possible to constantly monitor a characteristic of interest. This generates a phenomenon known as censoring that can be classified as having a left censor, right censor or interval censor. When one is working with survival data in the presence of arbitrary censoring, the survival time of interest is defined as the elapsed time between an initial event and the next event that is generally unknown. This problem has been widely studied in the statistic literature and some progress has been made, toward resolving and the formulation of a bivariate likelihood to estimate parameters in a parametric regression model offers positive development opportunities. In this paper, we construct a bivariate likelihood for the Weibull regression model in the presence of interval censoring. Finally, its performance is illustrated by means of a simulation study. |
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