Publications by authors named "Marcos Vinicius de Oliveira Peres"
Article Synopsis
- The study presents a new multivariate mixture cure rate model using the Chen probability distribution, aimed at analyzing recurrent event data with a cure fraction.
- This model offers an alternative to traditional methods like the semiparametric Cox proportional hazards model, focusing on bivariate lifetime data influenced by covariates and censored observations.
- The methodology was applied to real medical datasets concerning leukemia and diabetic retinopathy, with model validation conducted through Cox-Snell residuals to assess its effectiveness.
In time-to-event studies it is common the presence of a fraction of individuals not expecting to experience the event of interest; these individuals who are immune to the event or cured for the disease during the study are known as long-term survivors. In addition, in many studies it is observed two lifetimes associated to the same individual, and in some cases there exists a dependence structure between them. In these situations, the usual existing lifetime distributions are not appropriate to model data sets with long-term survivors and dependent bivariate lifetimes.
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