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dc.contributor.author
Nores, Maria Laura
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dc.contributor.author
Diaz, Maria del Pilar
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dc.date.available
2024-08-09T12:47:08Z
dc.date.issued
2008-03
dc.identifier.citation
Nores, Maria Laura; Diaz, Maria del Pilar; Some properties of regression estimators in GEE models for clustered ordinal data; Elsevier Science; Computational Statistics and Data Analysis; 52; 7; 3-2008; 3877-3888
dc.identifier.issn
0167-9473
dc.identifier.uri
http://hdl.handle.net/11336/242194
dc.description.abstract
In this paper we study properties of the estimators of marginal mean parameters in the GEE1approac h of Heagerty and Zeger (J. Amer. Statist. Assoc. 91 (1996) 1024) for clustered ordinal data. We consider two aspects: coverage probabilities and efficiency. The first point was tackled by a simulation study, calculating empirical levels of confidence intervals for regression parameters using different sample sizes. We conclude that inferences have more validity for sample sizes greater than 100, while some care must be taken when the number of clusters is smaller since in several situations empirical levels were much lower than nominal levels. Regarding the second aspect, we studied asymptotic efficiency for the case of an independence working specification in relation to a correctly specified exchangeable association structure. We extended to ordinal measurements the results derived for binary outcomes, sustaining that the loss of efficiency depends both on the intensity of the association between responses and the design matrix. We showed that relative efficiency of independence to exchangeable estimator is high when responses are independent, when covariates are mean-balanced, or when all covariates are constant within clusters. However, relative efficiency noticeably declines with increasing association for non mean-balanced within-cluster covariates. Simulation studies also supported these conclusions for data with an approximately exchangeable association structure.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Elsevier Science
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dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
COVERAGE PROBABILITIES
dc.subject
EFFICIENCY
dc.subject
ASSOCIATION
dc.subject
GLOBAL ODDS RATIOS
dc.subject
COVARIATE DESIGN
dc.subject.classification
Estadística y Probabilidad
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dc.subject.classification
Matemáticas
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dc.subject.classification
CIENCIAS NATURALES Y EXACTAS
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dc.title
Some properties of regression estimators in GEE models for clustered ordinal data
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2024-08-08T15:48:12Z
dc.journal.volume
52
dc.journal.number
7
dc.journal.pagination
3877-3888
dc.journal.pais
Países Bajos
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dc.journal.ciudad
Amsterdam
dc.description.fil
Fil: Nores, Maria Laura. Universidad Nacional de Córdoba; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina
dc.description.fil
Fil: Diaz, Maria del Pilar. Universidad Nacional de Córdoba. Facultad de Medicina. Escuela de Nutrición; Argentina
dc.journal.title
Computational Statistics and Data Analysis
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dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0167947307004689
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.csda.2007.12.009
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