Abstract Details
Activity Number:
|
438
|
Type:
|
Contributed
|
Date/Time:
|
Tuesday, August 6, 2013 : 2:00 PM to 3:50 PM
|
Sponsor:
|
Health Policy Statistics Section
|
Abstract - #308989 |
Title:
|
F-Tests in Incomplete Data for Multiple Regression Set-Up
|
Author(s):
|
Ashok Chaurasia*+ and Ofer Harel
|
Companies:
|
Univeristy of Connecticut and University of Connecticut
|
Keywords:
|
Incomplete Data ;
Multiple Imputation ;
Model Selection ;
(Partial and Global) F-test ;
Multiple Linear Regression
|
Abstract:
|
Tests for regression coefficients such as the partial F-test are common is applied research. When dealing with incomplete data, the task of conducting F-tests remains elusive. In this paper we propose a method based on the coefficient of determination to perform partial F-tests with multiply imputed data. Our proposed method can be applied for conducting the "global" F-test (test for all regression coefficients equal to zero), partial F-test (for one or more coefficients, but not all, equal zero), or for equality of regression coefficients. The proposed method is evaluated using simulated data and applied to a health related 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.
Copyright © American Statistical Association.