Abstract Details
Activity Number:
|
413
|
Type:
|
Contributed
|
Date/Time:
|
Tuesday, August 5, 2014 : 2:00 PM to 3:50 PM
|
Sponsor:
|
Section for Statistical Programmers and Analysts
|
Abstract #313492
|
|
Title:
|
Fitting Marginal Models to Clustered Temporal Data with Informative Cluster Size and Informative Number of Temporal Observations
|
Author(s):
|
Joseph Bible*+ and Somnath Datta
|
Companies:
|
University of Louisville and University of Louisville
|
Keywords:
|
Informative Cluster Size
|
Abstract:
|
We fit GEE type marginal models in a longitudinal study where the number of observations in a cluster (cluster size) is potentially informative of the overall response in a cluster. Furthermore, for each unit in a given cluster, the number of temporal observations on the unit is correlated to the responses for that unit. A standard inverse cluster size reweighted GEE is not sufficient for obtaining unbiased marginal parameter estimates in this situation. We device a new reweighting scheme that is capable of producing nearly unbiased parameter estimators in such situations. We apply our method on a temporal dataset of periodontal disease measurements extracted from the Piedmont Study.
|
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.