Working-correlation-structure identification in generalized estimating equations
Hin, Lin-Yee & Wang, You-Gan (2009) Working-correlation-structure identification in generalized estimating equations. Statistics in Medicine, 28(4), pp. 642-658.
Selecting 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 LIS 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.
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|Item Type:||Journal Article|
|Keywords:||clustered data, correlation modelling, correlation information, criterion, covariance, efficiency, generalized estimating equations, model selection, QIC, working correlation structure, longitudinal data, linear-models, gee analyses, selection, misspecification, error|
|Deposited On:||17 Nov 2015 02:55|
|Last Modified:||11 Dec 2015 03:02|
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