Cross-Validation of Survival Bump Hunting by Recursive Peeling Methods

• Activity Number: 333
• Type: Contributed
• Date/Time: Tuesday, August 5, 2014 : 10:30 AM to 12:20 PM
• Sponsor: Biometrics Section
• Author(s): Jean-Eudes Dazard*+ and Michael Choe and Michael LeBlanc and J. Sunil Rao
• Companies: Case Western Reserve University and Case Western Reserve University and Fred Hutchinson Cancer Research Center and University of Miami
• Keywords: K-Fold Cross-Validation ; Bump Hunting ; Non-Parametric Survival Analysis ; Patient Rule-Induction Method ; Survival/Risk Estimation ; Survival/Risk Prediction

Abstract

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.