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A note on implementation of decaying product correlation structures for quasi‐least squares
Author(s) -
Shults Justine,
Guerra Matthew W.
Publication year - 2014
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.6194
Subject(s) - estimator , generalized least squares , least squares function approximation , bernoulli's principle , product (mathematics) , mathematics , bernoulli trial , correlation , outcome (game theory) , variable (mathematics) , matrix (chemical analysis) , statistics , computer science , mathematical analysis , engineering , aerospace engineering , materials science , geometry , mathematical economics , composite material
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.