Ishwaran, Hemant2; Gerds, Thomas A3; Kogalur, Udaya B2; Moore, Richard D2; Gange, Stephen J2; Lau, Bryan M2
1 Section of Biostatistics, Department of Public Health, Faculty of Health and Medical Sciences, Københavns Universitet2 unknown3 Section of Biostatistics, Department of Public Health, Faculty of Health and Medical Sciences, Københavns Universitet
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.