A Product Partition Model With Regression on Covariates

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dc.contributor.authorMueller, Peter
dc.contributor.authorQuintana, Fernando
dc.contributor.authorRosner, Gary L.
dc.date.accessioned2024-01-10T13:46:03Z
dc.date.available2024-01-10T13:46:03Z
dc.date.issued2011
dc.description.abstractWe propose a probability model for random partitions in the presence of covariates. In other words, we develop a model-based clustering algorithm that exploits available covariates. The motivating application is predicting time to progression for patients in a breast cancer trial. We proceed by reporting a weighted average of the responses of clusters of earlier patients. The weights should be determined by the similarity of the new patient's covariate with the covariates of patients in each cluster. We achieve the desired inference by defining a random partition model that includes a regression on covariates. Patients with similar covariates are a priori more likely to be clustered together. Posterior predictive inference in this model formalizes the desired prediction.
dc.description.abstractWe build on product partition models (PPM). We define an extension of the PPM to include a regression on covariates by including in the cohesion function a new factor that increases the probability of experimental units with similar covariates to be included in the same cluster. We discuss implementations suitable for any combination of continuous, categorical, count, and ordinal covariates.
dc.description.abstractAn implementation of the proposed model as R-package is available for download.
dc.description.funderNIH
dc.description.funderFONDECYT
dc.description.funderLaboratorio de Analisis Estocastico
dc.description.funderNATIONAL CANCER INSTITUTE
dc.fechaingreso.objetodigital2024-05-15
dc.format.extent19 páginas
dc.fuente.origenWOS
dc.identifier.doi10.1198/jcgs.2011.09066
dc.identifier.issn1061-8600
dc.identifier.pubmedidMEDLINE:21566678
dc.identifier.urihttps://doi.org/10.1198/jcgs.2011.09066
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/79113
dc.identifier.wosidWOS:000288580600019
dc.information.autorucMatemática;Quintana F ;S/I;100343
dc.issue.numero1
dc.language.isoen
dc.nota.accesocontenido parcial
dc.pagina.final278
dc.pagina.inicio260
dc.publisherAMER STATISTICAL ASSOC
dc.revistaJOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS
dc.rightsacceso restringido
dc.subjectClustering
dc.subjectNonparametric Bayes
dc.subjectVariable selection
dc.subjectBAYESIAN-ANALYSIS
dc.subjectMIXTURES
dc.subject.ods03 Good Health and Well-being
dc.subject.odspa03 Salud y bienestar
dc.titleA Product Partition Model With Regression on Covariates
dc.typeartículo
dc.volumen20
sipa.codpersvinculados100343
sipa.indexWOS
sipa.indexScopus
sipa.trazabilidadCarga SIPA;09-01-2024
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