A Bayesian long-term survival model parametrized in the cured fraction.
The main goal of this paper is to investigate a cure rate model that comprehends some well-known proposals found in the literature. In our work the number of competing causes of the event of interest follows the negative binomial distribution. The model is conveniently reparametrized through the cured fraction, which is then linked to covariates by means of the logistic link. We explore the use of Markov chain Monte Carlo methods to develop a Bayesian analysis in the proposed model. The procedure is illustrated with a numerical example.
de Castro
Mário
M
Universidade de São Paulo, Instituto de Ciências Matemáticas e de Computação, Caixa Postal 668, 13560-970 São Carlos-SP, Brazil. mcastro@icmc.usp.br
Cancho
Vicente G
VG
Rodrigues
Josemar
J
D000465:Algorithms; D001499:Bayes Theorem; D001699:Biometry / Q000379:methods; D017063:Outcome Assessment, Health Care / Q000379:methods*; D016016:Proportional Hazards Models; D016019:Survival Analysis; D015996:Survival Rate; D017741:Survivors / Q000706:statistics & numerical data*