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arXiv · 0811.1645

Random survival forests

Hemant Ishwaran·Udaya B. Kogalur·Eugene H. Blackstone·Michael S. Lauer
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Abstract

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. 2008-11-11. Random survival forests. https://doi.org/10.1214/08-aoas169

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