%0 Journal Article %1 Carey2011 %A Carey, Vincent J %A Wang, You-Gan %D 2011 %J Statistics in medicine %K Anticonvulsants Anticonvulsants:therapeuticuse ComputerSimulation DataInterpretation Epilepsy Epilepsy:epidemiology Humans LongitudinalStudies LongitudinalStudies:statistics&numericaldata Models NormalDistribution RandomizedControlledTrialsasTopic:statistics Software Software:statistics&numericaldata Statistical gamma-AminobutyricAcid gamma-AminobutyricAcid:analogs&derivatives gamma-AminobutyricAcid:therapeuticuse RCT %N 26 %P 3117-24 %R 10.1002/sim.4300 %T Working covariance model selection for generalized estimating equations. %U http://dx.doi.org/10.1002/sim.4300 http://www.ncbi.nlm.nih.gov/pubmed/21748775 %V 30 %X We investigate methods for data-based selection of working covariance models in the analysis of correlated data with generalized estimating equations. We study two selection criteria: Gaussian pseudolikelihood and a geodesic distance based on discrepancy between model-sensitive and model-robust regression parameter covariance estimators. The Gaussian pseudolikelihood is found in simulation to be reasonably sensitive for several response distributions and noncanonical mean-variance relations for longitudinal data. Application is also made to a clinical dataset. Assessment of adequacy of both correlation and variance models for longitudinal data should be routine in applications, and we describe open-source software supporting this practice. %@ 1097-0258

@article{Carey2011, abstract = {We investigate methods for data-based selection of working covariance models in the analysis of correlated data with generalized estimating equations. We study two selection criteria: Gaussian pseudolikelihood and a geodesic distance based on discrepancy between model-sensitive and model-robust regression parameter covariance estimators. The Gaussian pseudolikelihood is found in simulation to be reasonably sensitive for several response distributions and noncanonical mean-variance relations for longitudinal data. Application is also made to a clinical dataset. Assessment of adequacy of both correlation and variance models for longitudinal data should be routine in applications, and we describe open-source software supporting this practice.}, added-at = {2023-02-03T11:44:35.000+0100}, author = {Carey, Vincent J and Wang, You-Gan}, biburl = {https://www.bibsonomy.org/bibtex/21794c246d23c9a8bcbb005a76f51988c/jepcastel}, doi = {10.1002/sim.4300}, interhash = {5876ad82c01c98544d827eb9658cfc44}, intrahash = {1794c246d23c9a8bcbb005a76f51988c}, isbn = {1097-0258}, issn = {1097-0258}, journal = {Statistics in medicine}, keywords = {Anticonvulsants Anticonvulsants:therapeuticuse ComputerSimulation DataInterpretation Epilepsy Epilepsy:epidemiology Humans LongitudinalStudies LongitudinalStudies:statistics&numericaldata Models NormalDistribution RandomizedControlledTrialsasTopic:statistics Software Software:statistics&numericaldata Statistical gamma-AminobutyricAcid gamma-AminobutyricAcid:analogs&derivatives gamma-AminobutyricAcid:therapeuticuse RCT}, month = {11}, note = 6264, number = 26, pages = {3117-24}, pmid = {21748775}, timestamp = {2023-05-04T08:59:38.000+0200}, title = {Working covariance model selection for generalized estimating equations.}, url = {http://dx.doi.org/10.1002/sim.4300 http://www.ncbi.nlm.nih.gov/pubmed/21748775}, volume = 30, year = 2011 }