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Activity Number: 34
Type: Contributed
Date/Time: Sunday, July 31, 2016 : 2:00 PM to 3:50 PM
Sponsor: Biometrics Section
Abstract #318597
Title: On the Discovery and Use of Disease Risk Factors with Logistic Regression: New Prostate Cancer Risk Factors
Author(s): David Booth* and Venugopal Gopapalakrishna-Remani and Matthew Cooper and Fiona Green and Margaret Rayman
Companies: Kent State University and The University of Texas at Tyler and Washington University and University of Manchester and University of Surrey
Keywords: Prostate Cancer ; risk factors ; lasso regression ; stepwise regression ; boosting

We begin by arguing that the most commonly used algorithm for the discovery and use of disease risk factors, stepwise logistic regression, is unstable. We then argue that there are other algorithms available that are much more stable and reliable(e.g. the lasso). We then propose a protocol for the discovery and use of disease risk factors using lasso variable selection with logistic regression followed by boosting. We then illustrate the use of the protocol with a set of prostate cancer data and show that it recovers known risk factors. Finally we use the protocol to identify new risk factors for prostate cancer.

Authors who are presenting talks have a * after their name.

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