Abstract Details
Activity Number:
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333
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Type:
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Contributed
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Date/Time:
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Tuesday, August 5, 2014 : 10:30 AM to 12:20 PM
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Sponsor:
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Biometrics Section
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Abstract #312982
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Title:
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Cross-Validation of Survival Bump Hunting by Recursive Peeling Methods
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Author(s):
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Jean-Eudes Dazard*+ and Michael Choe and Michael LeBlanc and J. Sunil Rao
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Companies:
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Case Western Reserve University and Case Western Reserve University and Fred Hutchinson Cancer Research Center and University of Miami
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Keywords:
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K-Fold Cross-Validation ;
Bump Hunting ;
Non-Parametric Survival Analysis ;
Patient Rule-Induction Method ;
Survival/Risk Estimation ;
Survival/Risk Prediction
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Abstract:
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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 specic 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 specifically 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.
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Authors who are presenting talks have a * after their name.
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