The time-to-event relationship for survival modeling is considered when designing a study in
clinical trials. However, because time-to-event data are mostly not normally distributed …

The cure fraction models are usually used to model lifetime time data with long-term
survivors. In the present article, we introduce a Bayesian analysis of the four-parameter …

The class of semiparametric or transformation models has been presented in the literature
as a promising alternative for the analysis of lifetime data in the presence of covariates and …

Aims Consistent improvements for overall survival (OS) have been reported for individuals
with metastatic cancer. Swedish population-based registers allow national coverage and …

This paper presents a novel approach for analyzing bivariate positive data, taking into
account a covariate vector and left-censored observations, by introducing a hierarchical …

The present study introduces a new multivariate mixture cure rate model based on the Chen
probability distribution to model recurrent event data in the presence of cure fraction. In this …

The modeling and analysis of lifetime data in which the main endpoints are the times when
an event of interest occurs is of great interest in medical studies. In these studies, it is …

In this paper, we introduce maximum likelihood and Bayesian parameter estimation for the
exponentiated discrete Weibull (EDW) distribution in presence of randomly right censored …

Background: Breast cancer is a top biomedical research priority, and it is a major health
problem. Therefore, the present study aimed to determine the prognostic factors of breast …

The cure fraction models have been widely used to analyze survival data in which a
proportion of the individuals is not susceptible to the event of interest. In this article, we …