Random survival forests for competing risks

TY - JOUR

T1 - Random survival forests for competing risks

AU - Ishwaran, Hemant

AU - Gerds, Thomas A

AU - Kogalur, Udaya B

AU - Moore, Richard D

AU - Gange, Stephen J

AU - Lau, Bryan M

N1 - © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: [email protected].

PY - 2014/10/1

Y1 - 2014/10/1

N2 - 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.

AB - 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.

U2 - 10.1093/biostatistics/kxu010

DO - 10.1093/biostatistics/kxu010

M3 - Journal article

C2 - 24728979

SN - 1465-4644

VL - 15

SP - 757

EP - 773

JO - Biostatistics

JF - Biostatistics

IS - 4

ER -