Random survival forests for competing risks

被引:192
|
作者
Ishwaran, Hemant [1 ]
Gerds, Thomas A. [2 ]
Kogalur, Udaya B. [3 ]
Moore, Richard D. [4 ]
Gange, Stephen J. [5 ]
Lau, Bryan M. [5 ]
机构
[1] Univ Miami, Div Biostat, Miami, FL 33136 USA
[2] Univ Copenhagen, Dept Biostat, DK-1014 Copenhagen, Denmark
[3] Cleveland Clin, Dept Quantitat Hlth Sci, Cleveland, OH 44195 USA
[4] Johns Hopkins Univ, Sch Med, Dept Med, Baltimore, MD 21205 USA
[5] Johns Hopkins Univ, Dept Epidemiol, Bloomberg Sch Publ Hlth, Baltimore, MD 21205 USA
基金
美国国家卫生研究院; 美国国家科学基金会;
关键词
AIDS; Brier score; Competing risks; C-index; Cumulative incidence function; Ensemble; SELECTION; MODEL;
D O I
10.1093/biostatistics/kxu010
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
收藏
页码:757 / 773
页数:17
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