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...

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Bibliographic Details
Published in:Revista Colombiana de Estadística 2017, Vol.40 (1), p.85-103
Main Authors: Jaramilo Elorza, Mario César, Salazar Uribe, Juan Carlos
Format: Article
Language:English
Subjects:
Biostatistics
Bivariate analysis
Censorship
Computer simulation
Confidence
Confidence Bands
Goodness of Fit
Parameter estimation
Regression analysis
Regression Models
Simulation
Survival
Survival Analysis
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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.
ISSN:0120-1751
2389-8976
DOI:10.15446/rce.v40n1.55807