Competing risks data is often grouped into clusters, such as geographic regions. Shared
frailty models can be used to model the correlation between individuals within each cluster …

The frailty model, an extension of the proportional hazards model, is often used to model
clustered survival data. However, some extension of the ordinary frailty model is required …

In some biomedical cohort studies, recurrent or repeated events can be terminated by a
dependent terminal event like death. In this case, the process of recurrent events may …

Multi-type recurrent event data arise in many situations when two or more different event
types may occur repeatedly over an observation period. For example, in a randomized …

In the semi-competing risks situation where only a terminal event censors a non-terminal
event, observed event times can be correlated. Recently, frailty models with an arbitrary …

The inclusion of geographically-based information in many epidemiological studies has led
to the development of statistical and estimation methods that account for spatially dependent …

In this work, we provide a new class of frailty-based competing risks models for clustered
failure times data. This class is based on expanding the competing risks model of (1978 …

In recent years substantial research has been devoted to developing failure-time
methodology which accounts for possible dependency between observations. An example …

Understanding the factors that explain differences in survival times is an important issue for
establishing policies to improve national health systems. Motivated by breast cancer data …

Frailty models are becoming more and more popular in multivariate survival analysis.
Shared frailty models in particular are often used despite their limitations. To overcome their …