Working‐correlation‐structure identification in generalized estimating equations
Copyright policy )Working‐correlation‐structure identification in generalized estimating equations
AbstractSelecting an appropriate working correlation structure is pertinent to clustered data analysis using generalized estimating equations (GEE) because an inappropriate choice will lead to inefficient parameter estimation. We investigate the well‐known criterion of QIC for selecting a working correlation structure, and have found that performance of the QIC is deteriorated by a term that is theoretically independent of the correlation structures but has to be estimated with an error. This leads us to propose a correlation information criterion (CIC) that substantially improves the QIC performance. Extensive simulation studies indicate that the CIC has remarkable improvement in selecting the correct correlation structures. We also illustrate our findings using a data set from the Madras Longitudinal Schizophrenia Study. Copyright © 2008 John Wiley & Sons, Ltd.
- University of Queensland Australia
- University of Queensland Australia
- Queensland University of Technology Australia
- Commonwealth Scientific and Industrial Research Organisation Australia
longitudinal data, model selection, Biometry, 330, selection, generalized estimating equations, working correlation structure, Cluster Analysis, clustered data, Computer Simulation, 2613 Statistics and Probability, gee analyses, correlation information, Likelihood Functions, Covariance, QIC, misspecification, criterion, error, Correlation information criterion, Clustered data, linear-models, correlation modelling, Correlation modelling, efficiency, covariance, Data Interpretation, Statistical, Regression Analysis, 2713 Epidemiology
longitudinal data, model selection, Biometry, 330, selection, generalized estimating equations, working correlation structure, Cluster Analysis, clustered data, Computer Simulation, 2613 Statistics and Probability, gee analyses, correlation information, Likelihood Functions, Covariance, QIC, misspecification, criterion, error, Correlation information criterion, Clustered data, linear-models, correlation modelling, Correlation modelling, efficiency, covariance, Data Interpretation, Statistical, Regression Analysis, 2713 Epidemiology
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