RANDOM SURVIVAL FORESTS

被引：1684
|
作者：
Ishwaran, Hemant [1 ]
Kogalur, Udaya B. [2 ]
Blackstone, Eugene H. [3 ]
Lauer, Michael S. [4 ]
机构：
[1] Cleveland Clin, Dept Quantitat Hlth Sci, Cleveland, OH 44195 USA
[2] Columbia Univ, Dept Stat, New York, NY 10027 USA
[3] Cleveland Clin, Dept Thorac & Cardiovasc Surg, Cleveland, OH 44195 USA
[4] NHLBI, Div Prevent & Populat Sci, Rockledge Ctr 2, Bethesda, MD 20892 USA
来源：
ANNALS OF APPLIED STATISTICS | 2008年 / 2卷 / 03期
基金：
美国国家卫生研究院;
关键词：
Conservation of events; cumulative hazard function; ensemble; out-of-bag; prediction error; survival tree;
D O I：
10.1214/08-AOAS169
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
We introduce random survival forests, a random forests method for the analysis of right-censored survival data. New survival splitting rules for growing survival trees are introduced, as is a new missing data algorithm for imputing missing data. A conservation-of-events principle for survival forests is introduced and used to define ensemble mortality, a simple interpretable measure of mortality that can be used as a predicted outcome. Several illustrative examples are given, including a case study of the prognostic implications of body mass for individuals with coronary artery disease. Computations for all examples were implemented using the freely available R-software package. randomSurvivalForest.
引用
收藏
页码：841 / 860
页数：20
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