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