This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 599
Type: Invited
Date/Time: Thursday, August 5, 2010 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistical Learning and Data Mining
Abstract - #305982
Title: Penalized Regression Methods for Ranking Variables by Effect Size, with Applications to Genetic Mapping Studies
Author(s): Nam-Hee Choi and Kerby Shedden and Ji Zhu*+
Companies: University of Michigan and University of Michigan and University of Michigan
Address: 439 West Hall, Ann Arbor, MI, 48109,
Keywords: Variable Selection ; Ridge Regression ; Lasso ; Genetic Mapping

Multiple regression can be used to rank predictor variables according to their "unique" association with a response variable - that is, the association that is not explained by other measured predictors. Such a ranking is useful in applications such as genetic mapping studies, where one goal is to clarify the relative importance of several correlated genetic variants with weak effects. The use of classical multiple regression to rank the predictors according to their unique associations with the response is limited by difficulties due to collinearities among the predictors. Here we show that regularized regression can improve the accuracy of this ranking, with the greatest improvement occurring when the pairwise correlations among the predictor variables are strong and heterogeneous.

The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.

Back to the full JSM 2010 program

2010 JSM Online Program Home

For information, contact or phone (888) 231-3473.

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