Joint Inference for Competing Risks Survival Data

INFERENCE ON CENSORED SURVIVAL DATA UNDER COMPETING RISKS by

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, ...

Nonparametric predictive inference for combined competing risks data

The nonparametric predictive inference (NPI) approach for competing risks data has recently been presented, in particular addressing the question due to which of the competing risks the next unit will fail, and also considering the effects of unobserved, re-defined, unknown or removed competing risks. In this paper, we introduce how the NPI approach can be used to deal with situations where uni...

A general joint model for longitudinal measurements and competing risks survival data with heterogeneous random effects.

This article studies a general joint model for longitudinal measurements and competing risks survival data. The model consists of a linear mixed effects sub-model for the longitudinal outcome, a proportional cause-specific hazards frailty sub-model for the competing risks survival data, and a regression sub-model for the variance-covariance matrix of the multivariate latent random effects based...

Classification Trees for Survival Data with Competing Risks