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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.


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