Nonparametric estimation with recurrent competing risks data

Parametric Estimation in a Recurrent Competing Risks Model

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 compet- ing 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. ...

Nonparametric Estimation for Current Status Data with Competing Risks

Nonparametric estimation with left truncated semi-competing risks data

SUMMARY Cause-specific hazard and cumulative incidence function are of practical importance in competing risks studies. Inferential procedures for these quantities are well developed and can be applied to semi-competing risks data, where a terminating event censors a non-terminating event, after coercing the data into the competing risks format. Complications arise when there is left truncation...

Nonparametric Predictive Multiple Comparisons with Censored Data and Competing Risks

This paper provides an overview of nonparametric predictive inference for comparison of multiple groups of data including right-censored observations. Different right-censoring schemes discussed are early termination of an experiment, progressive censoring and competing risks. Theoretical results are briefly stated, detailed justifications are presented elsewhere. The methods are illustrated an...

Nonparametric predictive pairwise comparison with competing risks

In reliability, failure data often correspond to competing risks, where several failure modes can cause a unit to fail. This paper presents nonparametric predictive inference (NPI) for pairwise comparison with competing risks data, assuming that the failure modes are independent. These failure modes could be the same or different among the two groups, and these can be both observed and unobserv...