Literature DB >> 19065625

Working-correlation-structure identification in generalized estimating equations.

Lin-Yee Hin1, You-Gan Wang.   

Abstract

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 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.

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Year:  2009        PMID: 19065625     DOI: 10.1002/sim.3489

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  18 in total

1.  On the analysis of very small samples of Gaussian repeated measurements: an alternative approach.

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Journal:  Stat Med       Date:  2017-01-08       Impact factor: 2.373

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4.  Pseudo-value approach for comparing survival medians for dependent data.

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Journal:  Stat Med       Date:  2013-12-15       Impact factor: 2.373

5.  A covariance correction that accounts for correlation estimation to improve finite-sample inference with generalized estimating equations: A study on its applicability with structured correlation matrices.

Authors:  Philip M Westgate
Journal:  J Stat Comput Simul       Date:  2015-09-23       Impact factor: 1.424

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Authors:  Amadou Barry; Karim Oualkacha; Arthur Charpentier
Journal:  J Appl Stat       Date:  2021-07-26       Impact factor: 1.416

7.  Health-selective migration among patients with rheumatoid arthritis in Québec: a cohort study using administrative data.

Authors:  Jeremy A Labrecque; Ryan P Kyle; Lawrence Joseph; Sasha Bernatsky
Journal:  Rheumatol Int       Date:  2016-07-26       Impact factor: 2.631

8.  Src inhibits midline axon crossing independent of Frazzled/Deleted in Colorectal Carcinoma (DCC) receptor tyrosine phosphorylation.

Authors:  Michael P O'Donnell; Greg J Bashaw
Journal:  J Neurosci       Date:  2013-01-02       Impact factor: 6.167

9.  Improving power in small-sample longitudinal studies when using generalized estimating equations.

Authors:  Philip M Westgate; Woodrow W Burchett
Journal:  Stat Med       Date:  2016-04-18       Impact factor: 2.373

10.  Impact of protocol change on individual factors related to course of adverse reactions to chemotherapy for breast cancer.

Authors:  Daniela Polessa Paula; Vanessa I do Brasil Costa; Rosane V Jorge; Flávio F Nobre
Journal:  Support Care Cancer       Date:  2019-05-06       Impact factor: 3.603

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