333 – Survival Methods for Risk Estimation/Prediction
Cross-Validation of Survival Bump Hunting by Recursive Peeling Methods
Jean-Eudes Dazard
Case Western Reserve University
Michael Choe
Case Western Reserve University
Michael LeBlanc
Fred Hutchinson Cancer Research Center
J. Sunil Rao
University of Miami
We introduce a survival/risk bump hunting framework to build a bump hunting model with a possibly censored time-to-event type of response and to validate model estimates. First, we describe the use of adequate survival peeling criteria to build a survival/risk bump hunting model based on recursive peeling methods. Our method called "Patient Recursive Survival Peeling" is a rule-induction method that makes use of speci c peeling criteria such as hazards ratio or log-rank statistics. Second, to validate our model estimates and improve survival prediction accuracy, we describe a resampling-based validation technique speci fically designed for the joint task of decision rule making by recursive peeling (i.e. decision-box) and survival estimation. This alternative technique, called "combined" cross-validation is done by combining test samples over the cross-validation loops, a design allowing for bump hunting by recursive peeling in a survival setting. We provide empirical results showing the importance of cross-validation and replication.