Frailty models power variance function with cure fraction and latent risk factors negative binomial |
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| Authors: | Vinicius Fernando Calsavara Agatha Sacramento Rodrigues Vera Lúcia Damasceno Tomazella Mário de Castro |
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| Institution: | 1. Departamento de Epidemiologia e Estatística, Centro Internacional de Pesquisa, A.C. Camargo Cancer Center, S?o Paulo-SP, Brazil;2. Instituto de Matemática e Estatística, Universidade de S?o Paulo, S?o Paulo-SP, Brazilvinicius.calsavara@cipe.accamargo.org.br;4. Instituto de Matemática e Estatística, Universidade de S?o Paulo, S?o Paulo-SP, Brazil;5. Departamento de Estatística, Universidade Federal de S?o Carlos, S?o Carlos-SP, Brazil;6. Instituto de Ciências Matemáticas e de Computa??o, Universidade de S?o Paulo, S?o Carlos-SP, Brazil |
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| Abstract: | In this article, we propose a flexible cure rate model, which is an extension of Cancho et al. (2011 Cancho, V.G., Rodrigues, J., de Castro, M. (2011). A flexible model for survival data with a cure rate: A Bayesian approach. J. Appl. Stat. 38:57–70.Taylor &; Francis Online], Web of Science ®] , Google Scholar]) model, by incorporating a power variance function (PVF) frailty term in latent risk. The model is more flexible in terms of dispersion and it also quantifies the unobservable heterogeneity. The parameter estimation is reached by maximum likelihood estimation procedure and Monte Carlo simulation studies are considered to evaluate the proposed model performance. The practical relevance of the model is illustrated in a real data set of preventing cancer recurrence. |
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| Keywords: | Cancer recurrence competing risks cure rate models frailty models power variance function (PVF) distribution |
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