A class of semiparametric models for bivariate survival data

Walmir Reis Miranda Filho () and Fábio Nogueira Demarqui ()
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Walmir Reis Miranda Filho: Federal University of Ouro Preto
Fábio Nogueira Demarqui: Federal University of Minas Gerais

Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, 2025, vol. 31, issue 1, No 5, 102-125

Abstract: Abstract We propose a new class of bivariate survival models based on the family of Archimedean copulas with margins modeled by the Yang and Prentice (YP) model. The Ali-Mikhail-Haq (AMH), Clayton, Frank, Gumbel-Hougaard (GH), and Joe copulas 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 marginal 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 models through the analysis of survival data involving patients diagnosed with ovarian cancer.

Keywords: Archimedean copulas; Marginal survival functions; Baseline distributions; Regression structures (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10985-024-09642-x

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