A note on competing risks in survival data analysis

Simulating competing risks data in survival analysis.

Competing risks analysis considers time-to-first-event ('survival time') and the event type ('cause'), possibly subject to right-censoring. The cause-, i.e. event-specific hazards, completely determine the competing risk process, but simulation studies often fall back on the much criticized latent failure time model. Cause-specific hazard-driven simulation appears to be the exception; if done, ...

Semi-Competing Risks Data Analysis

Hospital readmission is a key marker of quality of healthcare; it has been used to investigate variation in quality among patients in a broad range of clinical contexts and has become an important policy measure. Notwithstanding its widespread use, however, readmission remains controversial as a measure of quality. Among the concerns raised, whether and how patient deaths are handled in the ana...

Competing risks survival analysis with recurrent events

The competing risks too arise when one type of event may affect the probability of occurrence of other events. Some authors have made important contributions in this area of research, multistate multivariate models have been proposed. Varieties of record are frequently encountered in areas as medicine, engineering, sociology, biology, social science, among others. Classical survival analysis mo...

INFERENCE ON CENSORED SURVIVAL DATA UNDER COMPETING RISKS by

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. ...