JSM 2013 Home
Online Program Home
My Program

Abstract Details

Activity Number: 194
Type: Contributed
Date/Time: Monday, August 5, 2013 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract - #309363
Title: Local Likelihood-Based Estimation for Quantile Classification in the Logistic Regression Model
Author(s): John Rice*+ and Jeremy Taylor
Companies: University of Michigan and University of Michigan
Keywords: classification ; robust estimation ; logistic regression ; asymmetric loss ; local likelihood
Abstract:

Much work has been done on the problem of predicting future binary outcomes in a population based on a sample from that population. However, most authors have focused primarily on median classification (i.e., a positive response is predicted if $\hat{p}_i>0.5$) or have made use of nonparametric ``black box'' methods. We desire to classify future subjects on the basis of a probability threshold $p^*$, not necessarily equal to 0.5, using a rule based on a linear combination of the covariates. To do this, we solve a weighted form of the score equations, using a kernel-like weight function centered about $p^*$; the bandwidth for the weight function is selected by cross validation. This work differs from most previous approaches in local likelihood and robust methods in that the weight depends on both the unknown regression parameters and the covariates (but not the outcome). Simulation results are given showing the reduction in misclassification rates that can be obtained with this method, even under certain forms of model misspecification. Analysis of a melanoma data set is also presented to demonstrate the utility of the method in practice.


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

Back to the full JSM 2013 program




2013 JSM Online Program Home

For information, contact jsm@amstat.org or phone (888) 231-3473.

If you have questions about the Continuing Education program, please contact the Education Department.

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

ASA Meetings Department  •  732 North Washington Street, Alexandria, VA 22314  •  (703) 684-1221  •  meetings@amstat.org
Copyright © American Statistical Association.