Open Access
September 2008 Random survival forests
Hemant Ishwaran, Udaya B. Kogalur, Eugene H. Blackstone, Michael S. Lauer
Ann. Appl. Stat. 2(3): 841-860 (September 2008). DOI: 10.1214/08-AOAS169


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.


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Hemant Ishwaran. Udaya B. Kogalur. Eugene H. Blackstone. Michael S. Lauer. "Random survival forests." Ann. Appl. Stat. 2 (3) 841 - 860, September 2008.


Published: September 2008
First available in Project Euclid: 13 October 2008

zbMATH: 1149.62331
MathSciNet: MR2516796
Digital Object Identifier: 10.1214/08-AOAS169

Keywords: Conservation of events , cumulative hazard function , ensemble , out-of-bag , prediction error , survival tree

Rights: Copyright © 2008 Institute of Mathematical Statistics

Vol.2 • No. 3 • September 2008
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