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Use of quasi-least squares to adjust for two levels of correlation
Authors:Shults Justine  Morrow Ardythe L
Institution:Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, Philadelphia 19104-6021, USA. jshults@cceb.upenn.edu
Abstract:This article considers data with two levels of association. Our motivating example is an international intervention trial with repeated observations on subjects who reside within geographically defined clusters. To account for the potential correlation within clusters and within the repeated measurements that pertain to each subject, we apply a method based on generalized estimating equations for a correlation structure proposed by Lefkopoulou, Moore, and Ryan (1989, Journal of the American Statistical Association 84, 810-815).
Keywords:Correlated data  Cluster randomization  Generalized estimating equations  Intervention studies  Kronecker product  Multiple levels of association  Quasi–least squares
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