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 …

In the analysis of survival data, it is usually assumed that any unit will experience the event
of interest if it is observed for a sufficiently long time. However, it can be explicitly assumed …

Background When the mortality among a cancer patient group returns to the same level as
in the general population, that is, the patients no longer experience excess mortality, the …

In this study, we consider a general, flexible, parametric hazard-based regression model for
censored lifetime data with covariates and term it the “general hazard (GH)” regression …

Bayesian methods for flexible time-to-event models usually rely on the theory of Markov
chain Monte Carlo (MCMC) to sample from posterior distributions and perform statistical …

We propose maximum likelihood methods for parameter estimation for a novel class of semi‐
parametric survival models with a cure fraction, in which the covariates are allowed to be …

We develop a dependent Dirichlet process model for survival analysis data. A major feature
of the proposed approach is that there is no necessity for resulting survival curve estimates …

A cure model is a useful approach for analysing failure time data in which some subjects
could eventually experience, and others never experience, the event of interest. A cure …

In this paper, we extend the vertical modeling approach for the analysis of survival data with
competing risks to incorporate a cure fraction in the population, that is, a proportion of the …

We propose a new survival model for lifetime data in the presence of surviving fraction and
obtain some of its properties. Its genesis is based on extensions of the promotion time cure …