A class of semiparametric models for bivariate survival data.

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MetadadosDescriçãoIdioma
Autor(es): dc.creatorMiranda Filho, Walmir dos Reis-
Autor(es): dc.creatorDemarqui, Fábio Nogueira-
Data de aceite: dc.date.accessioned2025-08-21T15:44:48Z-
Data de disponibilização: dc.date.available2025-08-21T15:44:48Z-
Data de envio: dc.date.issued2025-08-13-
Data de envio: dc.date.issued2024-
Fonte completa do material: dc.identifierhttps://www.repositorio.ufop.br/handle/123456789/20841-
Fonte completa do material: dc.identifierhttps://link.springer.com/article/10.1007/s10985-024-09642-x-
Fonte completa do material: dc.identifierhttps://doi.org/10.1007/s10985-024-09642-x-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/1023126-
Descrição: dc.descriptionWe propose a new class of bivariate survival models based on the family of Archi- medean copulas with margins modeled by the Yang and Prentice (YP) model. The Ali-Mikhail-Haq (AMH), Clayton, Frank, Gumbel-Hougaard (GH), and Joe copu- las are employed to accommodate the dependency among marginal distributions. Baseline distributions are modeled semiparametrically by the Piecewise Exponential (PE) distribution and the Bernstein polynomials (BP). Inference procedures for the proposed class of models are based on the maximum likelihood (ML) approach. The new class of models possesses some attractive features: i) the ability to take into account survival data with crossing survival curves; ii) the inclusion of the well- known proportional hazards (PH) and proportional odds (PO) models as particular cases; iii) greater flexibility provided by the semiparametric modeling of the mar- ginal baseline distributions; iv) the availability of closed-form expressions for the likelihood functions, leading to more straightforward inferential procedures. The properties of the proposed class are numerically investigated through an extensive simulation study. Finally, we demonstrate the versatility of our new class of mod- els through the analysis of survival data involving patients diagnosed with ovarian cancer.-
Formato: dc.formatapplication/pdf-
Idioma: dc.languageen-
Direitos: dc.rightsrestrito-
Palavras-chave: dc.subjectArchimedean copulas-
Palavras-chave: dc.subjectMarginal survival functions-
Palavras-chave: dc.subjectBaseline distributions-
Palavras-chave: dc.subjectRegression structures-
Título: dc.titleA class of semiparametric models for bivariate survival data.-
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