Comparison between a measurement error model and a linear model without measurement error

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dc.contributor.authorVidal, Ignacio
dc.contributor.authorIglesias, Pilar
dc.date.accessioned2024-01-10T13:11:52Z
dc.date.available2024-01-10T13:11:52Z
dc.date.issued2008
dc.description.abstractThe regression of a response variable y on an explanatory variable from observations on (y, x), where x is a measurement of xi, is a special case of errors-in-variables model or measurement error model (MEM). In this work we attempt to answer the following question: given the data (y, x) under a MEM, is it possible to not consider the measurement error on the covariable in order to use a simpler model? To the best of our knowledge, this problem has not been treated in the Bayesian literature. To answer that question, we compute Bayes factors, the deviance information criterion and the posterior mean of the logarithmic discrepancy. We apply these Bayesian model comparison criteria to two real data sets obtaining interesting results. We conclude that, in order to simplify the MEM, model comparison criteria can be useful to compare structural MEM and a random effect model, but we would also need other statistic tools and take into account the final goal of the model. (c) 2008 Elsevier B.V. All rights reserved.
dc.fechaingreso.objetodigital2024-04-09
dc.format.extent11 páginas
dc.fuente.origenWOS
dc.identifier.doi10.1016/j.csda.2008.06.016
dc.identifier.eissn1872-7352
dc.identifier.issn0167-9473
dc.identifier.urihttps://doi.org/10.1016/j.csda.2008.06.016
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/78109
dc.identifier.wosidWOS:000259710400007
dc.information.autorucMatemática;Iglesias P;S/I;100265
dc.issue.numero1
dc.language.isoen
dc.nota.accesocontenido parcial
dc.pagina.final102
dc.pagina.inicio92
dc.publisherELSEVIER
dc.revistaCOMPUTATIONAL STATISTICS & DATA ANALYSIS
dc.rightsacceso restringido
dc.subjectINFLUENTIAL OBSERVATIONS
dc.subjectINFLUENCE DIAGNOSTICS
dc.subjectMARGINAL LIKELIHOOD
dc.subjectVARIABLES
dc.subject.ods03 Good Health and Well-being
dc.subject.odspa03 Salud y bienestar
dc.titleComparison between a measurement error model and a linear model without measurement error
dc.typeartículo
dc.volumen53
sipa.codpersvinculados100265
sipa.indexWOS
sipa.indexScopus
sipa.trazabilidadCarga SIPA;09-01-2024
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