This book begins with an introduction to the history of cure rate models and their significant role in survival analysis. A description of the real data sets used in the book for illustrative purposes is provided. Next, basic concepts and methods for modeling time-to-event data are covered. An introduction of the maximum likelihood method, the EM algorithm, the Kaplan-Meier estimator, NelsonAalen estimator are included, among others. A detailed study of the mixture cure rate model and the family of models generated by a competing cause scenario is discussed. Analysis of real data-sets using the cure rate models illustrate the theory presented in the book. Other aspects of cure rate modeling such as identifiability, the role of censoring mechanism, asymptotic properties of estimators, are examined. Finally, great attention is paid to the computational aspects of cure rate models.

Detailed guidelines on the necessary steps that must be followed for estimating the parameters of the models, or generating simulated data sets for testing and validation purposes, are provided.