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dc.contributor.authorCasals, Martí
dc.contributor.authorLangohr, Klaus
dc.contributor.authorCarrasco, Josep Lluís
dc.contributor.authorRönnegård, Lars
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Estadística i Investigació Operativa
dc.identifier.citationCasals, M., Langohr, K., Carrasco, J., Rönnegård, L. Parameter estimation of Poisson generalized linear mixed models based on three different statistical principles: a simulation study. "SORT: statistics and operations research transactions", Desembre 2015, vol. 39, núm. 2, p. 281-308.
dc.description.abstractGeneralized linear mixed models are flexible tools for modeling non-normal data and are useful for accommodating overdispersion in Poisson regression models with random effects. Their main difficulty resides in the parameter estimation because there is no analytic solution for the maximization of the marginal likelihood. Many methods have been proposed for this purpose and many of them are implemented in software packages. The purpose of this study is to compare the performance of three different statistical principles -Marginal likelihood, Extended likelihood, Bayesian analysis- in R via simulation studies. Real data on contact wrestling are used for illustration.
dc.format.extent28 p.
dc.publisherInstitut d'Estadística de Catalunya
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística::Investigació operativa::Simulació
dc.subject.lcshOperations research
dc.subject.otherEstimation methods
dc.subject.otherPoisson generalized linear mixed models
dc.subject.othersimu- lation study
dc.subject.otherstatistical principles
dc.subject.othersport injuries
dc.titleParameter estimation of Poisson generalized linear mixed models based on three different statistical principles: a simulation study
dc.subject.lemacInvestigació operativa
dc.contributor.groupUniversitat Politècnica de Catalunya. GRBIO - Grup de Recerca en Bioestadística i Bioinformàtica
dc.description.peerreviewedPeer Reviewed
dc.subject.amsClassificació AMS::90 Operations research, mathematical programming::90B Operations research and management science
dc.rights.accessOpen Access
dc.description.versionPostprint (published version)
upcommons.citation.authorCasals, M.; Langohr, K.; Carrasco, J.; Rönnegård, L.
upcommons.citation.publicationNameSORT: statistics and operations research transactions

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