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 recurrences of the competing risks over a random monitoring period. The resulting model is called the recurrent competing risks model (RCRM) and is coupled with two repair strategies whenever the system fails. Ma...

CRISCAT is a computer program for the analysis of grouped survival data with competing risks via weighted least squares methods. Competing risks adjustments are obtained from general matrix operations using many of the strategies employed in a previously developed program (GENCAT) for multivariate categorical data. CRISCAT computes survival rates at several time points for multiple causes of fa...

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 when there exist competing risks within a cluster. Under competing risks, the underlying processes affecting the events of interest and competing events could be different but correlated. In this paper, the hierarchi...

The epidemiologist primarily studies transitions between states of health and disease. The purpose of the present article is to define a foundational parameter for such studies, namely risk. We begin simply and build to the setting in which there is more than 1 event type (i.e., competing risks or competing events), as well as more than 1 treatment or exposure level of interest. In the presence...

This paper proposes a new bivariate competing risks model that speci…es each marginal duration as the …rst time a Lévy subordinator crosses a random threshold. Our speci…cation is a natural variant of the competing risks version of the mixed proportional hazards model, but it allows time-varying heterogeneity and simultaneous termination of both durations. When the structural multiplicative e¤e...