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

页码：841 / 860

页数：20

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