In this paper, we present some distributional properties of the survival and frailty distribution involved in the proportional odds (PO) frailty model. Stochastic orderings are studied for this proportional odds frailtymodel. It is showed that negative dependence arises in the PO frailty model as opposed to the proportional hazard frailty model.

In clinical and observational studies, the event of interest can often recur on the same subject. In a more complicated situation, there exists a terminal event (e.g., death) which stops the recurrent event process. In many such instances, the terminal event is strongly correlated with the recurrent event process. We consider the recurrent/terminal event setting and model the dependence through...

We adopt the total time on test procedure to investigate monotone time trends in the intensity in a repeated event setting. The correct model is assumed to be a proportional hazards model, with a random effect to account for dependence within subjects. The method offers a simple routine for testing relevant hypotheses for recurrent event processes, without making distributional assumptions abou...

This talk gives an overview about the analysis of twin data on diseases, aging and longevity. One goal of our research in this area is the evaluation of the genetic contribution to life span and mortality from different causes. Such evaluation is performed using the idea of correlated frailty. We apply different correlated frailty models to the analysis of bivariate survival data from Danish, F...

Frailty models are often used in survival analysis to model multivariate time-to-event data. In infectious disease epidemiology, frailty models have been proposed to model heterogeneity in the acquisition of infection and to accommodate association in the occurrence of multiple types of infection. Although traditional frailty models rely on the assumption of lifelong immunity after recovery, re...

Many biomedical studies collect data on times of occurrence for a health event that can occur repeatedly, such as infection, hospitalization, recurrence of disease, or tumor onset. To analyze such data, it is necessary to account for within-subject dependency in the multiple event times. Motivated by data from studies of palpable tumors, this article proposes a dynamic frailty model and Bayesia...

BACKGROUND Sickness absence (SA) is an important social, economic and public health issue. Identifying and understanding the determinants, whether biological, regulatory or, health services-related, of variability in SA duration is essential for better management of SA. The conditional frailty model (CFM) is useful when repeated SA events occur within the same individual, as it allows simultane...

We extend a recently published multivariate Bayesian cure rate model to handle interval censoring and a varying number of measurements per individual. The model assumes an unknown number of latent causes of the event in question at each repeated measurement. This number is assumed to be distributed Poisson, with rate a function of covariates multiplied by a subject-specific frailty term. The ob...

Estimators within the Cox family are often used to estimate models for repeated events. Yet, there is much we still do not know about the performance of these estimators. In particular, we do not know how they perform given time dependence, different censoring rates, and a varying number of events and sample sizes. We use Monte Carlo simulations to demonstrate the performance of a variety of po...