Abstract Details
|
Activity Number:
|
297
|
|
Type:
|
Contributed
|
|
Date/Time:
|
Tuesday, August 5, 2014 : 8:30 AM to 10:20 AM
|
|
Sponsor:
|
Section on Medical Devices and Diagnostics
|
|
Abstract #312009
|
View Presentation
|
|
Title:
|
A Score Test for Detecting Heterogeneous Within-Group Variances in Linear Mixed Models
|
|
Author(s):
|
Chul Ahn*+ and Nelson Lu
|
|
Companies:
|
FDA-CDRH and FDA/CDRH
|
|
Keywords:
|
Diagnostic test ;
model violation ;
heteroscadasticity ;
score statistic
|
|
Abstract:
|
One of the common assumptions in linear mixed models is that the within-group variances are homogeneous. This paper investigates the impact of heterogeneous within-group variances on the estimate of a regression coefficient especially when the within-group variance depends on a group-level covariate. We also develop a diagnostic test based on score statistic to detect heterogeneous within-group variances in linear mixed linear models. The method is applied to the data from an orthopedic device clinical trial.
|
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.