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.
- Brier score
- Competing risks
- Cumulative incidence function
ASJC Scopus subject areas
- Statistics and Probability
- Statistics, Probability and Uncertainty