Relative Risk Trees for Censored Survival Data
Michael LeBlanc(University of Toronto), John Crowley(University of Toronto)
Cited by 438
Abstract
A method is developed for obtaining tree-structured relative risk estimates for censored survival data. The first step of a full likelihood estimation procedure is used in a recursive partitioning algorithm that adopts most aspects of the widely used Classification and Regression Tree (CART) algorithm of Breiman et al. (1984, Classification and Regression Trees, Belmont, California: Wadsworth). The performance of the technique is investigated through stimulation and compared to the tree-structured survival methods proposed by Davis and Anderson (1989, Statistics in Medicine 8, 947-961) and Therneau, Grambsch, and Fleming (1990, Biometrika 77, 147-160).
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