Estimação clássica e Bayesiana em modelos de sobrevida com fração de cura
In Survival Analysis, long duration models allow for the estimation of the healing fraction, which represents a portion of the population immune to the event of interest. Here we address classical and Bayesian estimation based on mixture models and promotion time models, using different distribution...
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| Formato: | Dissertação |
| Idioma: | por |
| Publicado em: |
Universidade Federal do Rio Grande do Norte
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| Endereço do item: | https://repositorio.ufrn.br/jspui/handle/123456789/17012 |
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| Resumo: | In Survival Analysis, long duration models allow for the estimation of the healing
fraction, which represents a portion of the population immune to the event of
interest. Here we address classical and Bayesian estimation based on mixture models
and promotion time models, using different distributions (exponential, Weibull and
Pareto) to model failure time. The database used to illustrate the implementations
is described in Kersey et al. (1987) and it consists of a group of leukemia patients
who underwent a certain type of transplant. The specific implementations used were
numeric optimization by BFGS as implemented in R (base::optim), Laplace approximation
(own implementation) and Gibbs sampling as implemented in Winbugs.
We describe the main features of the models used, the estimation methods and the
computational aspects. We also discuss how different prior information can affect
the Bayesian estimates |
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