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hal.structure.identifierService Biostatistiques et Informatique Médicale (CHU de Dijon) [DIM]
dc.contributor.authorQuantin, Catherine*
hal.structure.identifierDepartment of Statistics
dc.contributor.authorBillard, Lynne*
hal.structure.identifierCEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
dc.contributor.authorTouati, Myriam*
hal.structure.identifierService Biostatistiques et Informatique Médicale (CHU de Dijon) [DIM]
dc.contributor.authorAndreu, N.*
hal.structure.identifier
dc.contributor.authorCotin, Y.*
hal.structure.identifier
dc.contributor.authorZeller, Manfred*
hal.structure.identifierCEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
dc.contributor.authorAfonso, Filipe*
hal.structure.identifierCEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
dc.contributor.authorBattaglia, G.*
hal.structure.identifierCEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
dc.contributor.authorSeck, Djamal*
hal.structure.identifierService Biostatistiques et Informatique Médicale (CHU de Dijon) [DIM]
dc.contributor.authorLe Teuff, G.*
hal.structure.identifierCEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
dc.contributor.authorDiday, Edwin*
dc.date.accessioned2012-02-22T15:29:34Z
dc.date.available2012-02-22T15:29:34Z
dc.date.issued2011
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/8220
dc.language.isoenen
dc.subjectAcute Myocardial Infarctionen
dc.subjectAggregate Data Modelingen
dc.subjectRegression Treesen
dc.subjectClassificationen
dc.subject.ddc519en
dc.titleClassification and Regression Trees on Aggregate Data Modeling: An Application in Acute Myocardial Infarctionen
dc.typeArticle accepté pour publication ou publié
dc.contributor.editoruniversityotherService de Cardiologie Centre Hospitalier du Bocage;France
dc.contributor.editoruniversityotherService de Biostatistique et Informatique Médicale CHU Dijon;France
dc.contributor.editoruniversityotherDepartment of Statistics University of Georgia;États-Unis
dc.description.abstractenCardiologists are interested in determining whether the type of hospital pathway followed by a patient is predictive of survival. The study objective was to determine whether accounting for hospital pathways in the selection of prognostic factors of one-year survival after acute myocardial infarction AMI provided a more informative analysis than that obtained by the use of a standard regression tree analysis CART method . Information on AMI was collected for 1095 hospitalized patients over an 18-month period. The construction of pathways followed by patients produced symbolic-valued observations requiring a symbolic regression tree analysis. This analysis was compared with the standard CART analysis using patients as statistical units described by standard data selected TIMI score as the primary predictor variable. For the 1011 84, resp. patients with a lower higher TIMI score, the pathway variable did not appear as a diagnostic variable until the third second stage of the tree construction. For an ecological analysis, again TIMI score was the first predictor variable. However, in a symbolic regression tree analysis using hospital pathways as statistical units, the type of pathway followed was the key predictor variable, showing in particular that pathways involving early admission to cardiology units produced high one-year survival rates.en
dc.relation.isversionofjnlnameJournal of Probability and Statistics
dc.relation.isversionofjnlvol2011en
dc.relation.isversionofjnldate2011
dc.relation.isversionofjnlpages523937en
dc.relation.isversionofdoihttp://dx.doi.org/10.1155/2011/523937en
dc.description.sponsorshipprivateouien
dc.relation.isversionofjnlpublisherHindawien
dc.subject.ddclabelProbabilités et mathématiques appliquéesen
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