Abstract Details
Activity Number:
|
305
|
Type:
|
Contributed
|
Date/Time:
|
Tuesday, August 6, 2013 : 8:30 AM to 10:20 AM
|
Sponsor:
|
Section on Nonparametric Statistics
|
Abstract - #308788 |
Title:
|
Testing for the Covariate Effect in the Fully Nonparametric ANCOVA
|
Author(s):
|
Shu-Min Liao*+ and Michael G. Akritas
|
Companies:
|
Amherst College and The Pennsylvania State University
|
Keywords:
|
Nonparametric ;
Analysis of Covariance ;
Nested Designs ;
Asymptotic Theory
|
Abstract:
|
In this talk, we introduce a new approach for testing the covariate effect in the context of the fully nonparametric ANCOVA which capitalizes on the connection to the testing problems in two-fold nested designs. The basic idea behind the proposed method is to think of each distinct covariate value as a level of a sub-class nested in each group/class. A projection-based tool is developed to obtain a new class of quadratic forms, whose asymptotic behavior is then studied to establish the limiting distributions of the proposed test statistic under the null hypothesis and local alternatives. Simulation studies show that this new method, compared with existing alternatives, has better power properties and achieves the nominal level under violations of the classical assumptions. Analysis of several data sets are also included.
|
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.
Copyright © American Statistical Association.