A model-based approach to Bayesian classification with applications to predicting pregnancy outcomes from longitudinal beta-hCG profiles

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dc.contributor.authorDe La Cruz Mesia, Rolando
dc.contributor.authorQuintana, Fernando A.
dc.date.accessioned2024-01-10T13:11:01Z
dc.date.available2024-01-10T13:11:01Z
dc.date.issued2007
dc.description.abstractThis paper discusses Bayesian statistical methods for the classification of observations into two or more groups based on hierarchical models for nonlinear longitudinal profiles. Parameter estimation for a discriminant model that classifies individuals into distinct predefined groups or populations uses appropriate posterior simulation schemes. The methods are illustrated with data from a study involving 173 pregnant women. The main objective in this study is to predict normal versus abnormal pregnancy outcomes from beta human chorionic gonadotropin data available at early stages of pregnancy.
dc.fechaingreso.objetodigital2024-04-30
dc.format.extent11 páginas
dc.fuente.origenWOS
dc.identifier.doi10.1093/biostatistics/kxl003
dc.identifier.issn1465-4644
dc.identifier.pubmedidMEDLINE:16754632
dc.identifier.urihttps://doi.org/10.1093/biostatistics/kxl003
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/77979
dc.identifier.wosidWOS:000245512000005
dc.information.autorucMatemática;De La Cruz-Mesía R;S/I;119
dc.information.autorucMatemática;Quintana F;S/I;100343
dc.issue.numero2
dc.language.isoen
dc.nota.accesocontenido parcial
dc.pagina.final238
dc.pagina.inicio228
dc.publisherOXFORD UNIV PRESS
dc.revistaBIOSTATISTICS
dc.rightsacceso restringido
dc.subjectdiscriminant analysis
dc.subjectlongitudinal data
dc.subjectnonlinear hierarchical models
dc.subjectHUMAN CHORIONIC-GONADOTROPIN
dc.subjectPOPULATION PHARMACOKINETIC MODELS
dc.subjectDISCRIMINANT-ANALYSIS
dc.subjectMIXED MODELS
dc.subjectPROGESTERONE
dc.subjectESTRADIOL
dc.subject.ods03 Good Health and Well-being
dc.subject.odspa03 Salud y bienestar
dc.titleA model-based approach to Bayesian classification with applications to predicting pregnancy outcomes from longitudinal beta-hCG profiles
dc.typeartículo
dc.volumen8
sipa.codpersvinculados119
sipa.codpersvinculados100343
sipa.indexWOS
sipa.indexScopus
sipa.trazabilidadCarga SIPA;09-01-2024
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