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A note on implementation of decaying product correlation structures for quasi‐least squares
Authors:Justine Shults  Matthew W Guerra
Institution:1. Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, , Philadelphia, PA, U.S.A.;2. Division of Biometrics III, Office of Biostatistics, OTS, CDER, FDA, , Silver Spring, MD, U.S.A.
Abstract:This note implements an unstructured decaying product matrix via the quasi‐least squares approach for estimation of the correlation parameters in the framework of generalized estimating equations. The structure we consider is fairly general without requiring the large number of parameters that are involved in a fully unstructured matrix. It is straightforward to show that the quasi‐least squares estimators of the correlation parameters yield feasible values for the unstructured decaying product structure. Furthermore, subject to conditions that are easily checked, the quasi‐least squares estimators are valid for longitudinal Bernoulli data. We demonstrate implementation of the structure in a longitudinal clinical trial with both a continuous and binary outcome variable. Copyright © 2014 John Wiley & Sons, Ltd.
Keywords:decaying product  feasible  generalized estimating equations  longitudinal binary data  quasi‐least squares
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