Survival analysis has established itself as a major statistical technique in medical research.
Applications in hospital epidemiology, however, are only beginning to emerge. One reason …

Enterprise software systems are required to be highly reliable because they are central to
the business operations of most firms. However, configuring and maintaining these systems …

Background: Data types are recurrent events in studies in which each person may
experience an event at different times. One of the most popular approaches to analyze …

Background. Peritonitis-free survival is commonly reported in the peritoneal dialysis (PD)
literature. The Kaplan–Meier method appears to be the only technique used to date …

Nonparametric estimators of component and system life distributions are developed and
presented for situations where recurrent competing risks data from series systems are …

The focus of this article is on the analysis of repairable systems that are subject to multiple
sources of recurrence. The event of interest at the system level is assumed to be caused by …

HeIn this article, we use Bayesian reference analysis to consider the model of recurrent
events with competing risks, where the sampling distribution of the observations due to …

Recurrent competing risks data are common in survival studies. In such contexts the effects
of competing risks on lifetime outcomes are important problem of study. In this work we …

In this paper, we consider estimating the intensity of a recurrent event process observed
under a standard censoring scheme. We first propose a collection of kernel estimators for …

A resource-efficient approach to making inferences about the distributional properties of the
failure times in a competing risks setting is presented. Efficiency is gained by observing …