Abstract Details
|
Activity Number:
|
104
|
|
Type:
|
Invited
|
|
Date/Time:
|
Monday, August 4, 2014 : 8:30 AM to 10:20 AM
|
|
Sponsor:
|
Korean International Statistical Society
|
|
Abstract #310703
|
View Presentation
|
|
Title:
|
Treatment Effect Modifiers Based on Functional Data
|
|
Author(s):
|
R. Todd Ogden*+ and Adam Ciarleglio and Eva Petkova and Thaddeus Tarpey
|
|
Companies:
|
Columbia University and New York University School of Medicine and New York University School of Medicine and Wright State University
|
|
Keywords:
|
biosignature ;
imaging data
|
|
Abstract:
|
In many biomedical applications it is of interest to use functional data observed at baseline to predict clinical outcome for a patient assigned to a particular treatment. When multiple treatments are available, the expected effectiveness of each treatment may depend in some way on the functional predictors, i.e, the functional data can be said to modify the treatment effect. We describe various statistical models for such a situation along with methods for estimation and testing within each model.
|
Authors who are presenting talks have a * after their name.
Back to the full JSM 2014 program
|
2014 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Professional Development 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.
Copyright © American Statistical Association.