Modeling categorical covariates for lifetime data in the presence of cure fraction by Bayesian partition structures (2014)
- Authors:
- USP affiliated authors: LOUZADA NETO, FRANCISCO - ICMC ; ANDRADE FILHO, MÁRIO DE CASTRO - ICMC
- Unidade: ICMC
- DOI: 10.1080/02664763.2013.847067
- Subjects: INFERÊNCIA BAYESIANA; MÉTODOS MCMC; ANÁLISE DE SOBREVIVÊNCIA; MELANOMA
- Keywords: Bayesian approach; cure fraction; survival data; tessellation; categorical variable; geometric
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Journal of Applied Statistics
- ISSN: 0266-4763
- Volume/Número/Paginação/Ano: v. 41, n. 3, p. 622-634, 2014
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
LOUZADA, Francisco et al. Modeling categorical covariates for lifetime data in the presence of cure fraction by Bayesian partition structures. Journal of Applied Statistics, v. 41, n. 3, p. 622-634, 2014Tradução . . Disponível em: https://doi.org/10.1080/02664763.2013.847067. Acesso em: 27 jan. 2026. -
APA
Louzada, F., Castro, M. de, Tomazella, V., & Gonzales, J. F. B. (2014). Modeling categorical covariates for lifetime data in the presence of cure fraction by Bayesian partition structures. Journal of Applied Statistics, 41( 3), 622-634. doi:10.1080/02664763.2013.847067 -
NLM
Louzada F, Castro M de, Tomazella V, Gonzales JFB. Modeling categorical covariates for lifetime data in the presence of cure fraction by Bayesian partition structures [Internet]. Journal of Applied Statistics. 2014 ; 41( 3): 622-634.[citado 2026 jan. 27 ] Available from: https://doi.org/10.1080/02664763.2013.847067 -
Vancouver
Louzada F, Castro M de, Tomazella V, Gonzales JFB. Modeling categorical covariates for lifetime data in the presence of cure fraction by Bayesian partition structures [Internet]. Journal of Applied Statistics. 2014 ; 41( 3): 622-634.[citado 2026 jan. 27 ] Available from: https://doi.org/10.1080/02664763.2013.847067 - Bayesian frailty models for multi-state survival data
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Informações sobre o DOI: 10.1080/02664763.2013.847067 (Fonte: oaDOI API)
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