A new survival model with surviving fraction: an application to colorectal cancer data (2019)
- Authors:
- USP affiliated authors: CANCHO, VICENTE GARIBAY - ICMC ; ORTEGA, EDWIN MOISES MARCOS - ESALQ
- Unidades: ICMC; ESALQ
- DOI: 10.1177/0962280218786053
- Subjects: ALGORITMOS; ANÁLISE DE SOBREVIVÊNCIA; MODELOS MATEMÁTICOS; NEOPLASIAS COLORRETAIS; VEROSSIMILHANÇA
- Language: Inglês
- Imprenta:
- Publisher place: Thousand Oaks
- Date published: 2019
- Source:
- Título: Statistical Methods in Medical Research
- ISSN: 0962-2802
- Volume/Número/Paginação/Ano: v. 28, n. 9, p. 2665-2680, 2019
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
BARRIGA, Gladys Dorotea Cacsire et al. A new survival model with surviving fraction: an application to colorectal cancer data. Statistical Methods in Medical Research, v. 28, n. 9, p. 2665-2680, 2019Tradução . . Disponível em: https://doi.org/10.1177/0962280218786053. Acesso em: 14 maio 2025. -
APA
Barriga, G. D. C., Cancho, V. G., Garibay, D. V., Cordeiro, G. M., & Ortega, E. M. M. (2019). A new survival model with surviving fraction: an application to colorectal cancer data. Statistical Methods in Medical Research, 28( 9), 2665-2680. doi:10.1177/0962280218786053 -
NLM
Barriga GDC, Cancho VG, Garibay DV, Cordeiro GM, Ortega EMM. A new survival model with surviving fraction: an application to colorectal cancer data [Internet]. Statistical Methods in Medical Research. 2019 ; 28( 9): 2665-2680.[citado 2025 maio 14 ] Available from: https://doi.org/10.1177/0962280218786053 -
Vancouver
Barriga GDC, Cancho VG, Garibay DV, Cordeiro GM, Ortega EMM. A new survival model with surviving fraction: an application to colorectal cancer data [Internet]. Statistical Methods in Medical Research. 2019 ; 28( 9): 2665-2680.[citado 2025 maio 14 ] Available from: https://doi.org/10.1177/0962280218786053 - The Conway-Maxwell-Poisson-generalized gamma regression model with long-term survivors
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Informações sobre o DOI: 10.1177/0962280218786053 (Fonte: oaDOI API)
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