JSM 2013 Home
Online Program Home
My Program

Abstract Details

Activity Number: 593
Type: Topic Contributed
Date/Time: Wednesday, August 7, 2013 : 2:00 PM to 3:50 PM
Sponsor: Biometrics Section
Abstract - #307619
Title: Identifying Multiple Regulation in Semiparametric Regression Models
Author(s): Denis Agniel*+ and Tianxi Cai and Katherine P. Liao and Robert M. Plenge
Companies: and Harvard University and Brigham and Women's Hospital and Brigham and Women's Hospital
Keywords: semi-parametric regression ; sparse regression ; resampling ; closed testing ; multiple regulation ; hierarchical lasso
Abstract:

Often it is suspected that many related outcomes have a shared, sparse set of predictors. In genetics, researchers might hypothesize that a group of related diseases share a common genetic basis. In these cases, from a large set of potential predictors, we seek to identify a small set related with a set of outcomes. Furthermore, since not every predictor that is related to the outcomes will necessarily be related to all of them, we would like to identify for each predictor which outcomes it is associated with. In particular, we want to identify predictors that are important for multiple outcomes, which we will call "multiple regulators". This type of problem has been well studied in the case of multivariate linear regression, but we propose a method for identifying multiple regulation in semi-parametric regression models based on the hierarchical lasso (Zhou and Zhu, 2010). We further offer a resampling method to assess the variability in our estimator. And we finally propose a closed testing procedure to assess multiple regulation in the presence of randomness in the observed data.


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.