Random survival forests for competing risks #MMPMID24728979
Ishwaran H; Gerds TA; Kogalur UB; Moore RD; Gange SJ; Lau BM
Biostatistics 2014[Oct]; 15 (4): 757-73 PMID24728979show ga
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.