When analyzing time-to-event data, it often happens that a certain fraction of the data
corresponds to subjects who will never experience the event of interest. These event times …

Cure Models: Methods, Applications and Implementation is the first book in the last 25 years
that provides a comprehensive and systematic introduction to the basics of modern cure …

The mixture cure model is widely used to analyze survival data in the presence of a cured
subgroup. Standard logistic regression‐based approaches to model the incidence may lead …

We consider interval censored data with a cured subgroup that arises from longitudinal
followup studies with a heterogeneous population where a certain proportion of subjects is …

A completely nonparametric method for the estimation of mixture cure models is proposed. A
nonparametric estimator of the incidence is extensively studied and a nonparametric …

An estimator of the probability of default (PD) in credit risk is proposed. It is derived from a
nonparametric conditional survival function estimator based on cure models. Asymptotic …

In survival analysis it often happens that some subjects under study do not experience the
event of interest; they are considered to be “cured.” The population is thus a mixture of two …

Survival data analysis is a very broad field of statistics, encompassing a large variety of
methods used in a wide range of applications, and in particular in medical research. During …

Cure models are a class of time-to-event models where a proportion of individuals will never
experience the event of interest. The lifetimes of these so-called cured individuals are …

In survival analysis, it often happens that a certain fraction of the subjects under study never
experience the event of interest, that is, they are considered “cured.” In the presence of …