Use of quasi-least squares to adjust for two levels of correlation |
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Authors: | Shults Justine Morrow Ardythe L |
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Institution: | Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, Philadelphia 19104-6021, USA. jshults@cceb.upenn.edu |
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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). |
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Keywords: | Correlated data Cluster randomization Generalized estimating equations Intervention studies Kronecker product Multiple levels of association Quasi–least squares |
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