title: A note on implementation of decaying product correlation structures for quasi-least squares.
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.
authors.affiliation: Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, Philadelphia, PA, U.S.A.
authors.forename: Justine
authors.initials: J
authors.lastname: Shults
authors.forename: Matthew W
authors.initials: MW
authors.lastname: Guerra
mesh_terms: D000465:Algorithms; D000928:Antidepressive Agents / Q000627:therapeutic use; D056808:Biostatistics; D001714:Bipolar Disorder / Q000188:drug therapy; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data; D003511:Cyclohexanols / Q000627:therapeutic use; D006801:Humans; D016018:Least-Squares Analysis; D018020:Lithium Compounds / Q000627:therapeutic use; D008137:Longitudinal Studies; D015233:Models, Statistical; D000069470:Venlafaxine Hydrochloride
chemical_list: D000928:Antidepressive Agents; D003511:Cyclohexanols; D018020:Lithium Compounds; D000069470:Venlafaxine Hydrochloride
keywords: decaying product; feasible; generalized estimating equations; longitudinal binary data; quasi-least squares