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 …

In many biomedical studies, subjects may experience the outcome of interest more than
once over a period of observation; outcomes of this sort have been termed recurrent events …

Survival data stand out as a special statistical field. This paper tries to describe what survival
data is and what makes it so special. Survival data concern times to some events. A key …

We introduce a general, flexible, parametric survival modelling framework which
encompasses key shapes of hazard functions (constant; increasing; decreasing; up then …

In this article, we have presented a review of existing methods and trends in survival
analysis and frailty models. The background has been presented for each topic discussed …

Survival data is a special form of time to event data that is often encountered while modelling
risk. The classical Cox proportional hazard model, that is popularly used to analyse survival …

Critically acclaimed and resoundingly popular in its first edition, Modelling Survival Data in
Medical Research has been thoroughly revised and updated to reflect the many …

In this paper we extend the long-term survival model proposed by Chen et al.[Chen, M.-H.,
Ibrahim, JG, Sinha, D., 1999. A new Bayesian model for survival data with a surviving …

In chronic diseases, such as cancer, recurrent events (such as relapses) are commonly
observed; these could be interrupted by death. With such data, a joint analysis of recurrence …

The Survival Kit is a Fortran 90 Software intended for survival analysis using proportional
hazards models and their extension to frailty models with a single response time. The …