Propensity‐score matching with competing risks in survival analysis

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...

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, ...

Survival Analysis and Regression Models in the Presence of Competing and Semi-competing Risks

Competing Risks and Survival Tree Ensemble

In the paper the ensemble of dipolar trees for analysis of competing risks is proposed. The tool is build on the base of the learning sets, which contain the data from clinical studies following patients response for a given treatment. In case of competing risks many types of response are investigated. The proposed method is able to cope with incomplete (censored) observations and as a result, ...

Random survival forests for competing risks.

We introduce a new approach to competing risks using random forests. Our method is fully non-parametric and can be used for selecting event-specific variables and for estimating the cumulative incidence function. We show that the method is highly effective for both prediction and variable selection in high-dimensional problems and in settings such as HIV/AIDS that involve many competing risks.