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Modifications to the Patient Rule-Induction Method that utilize non-additive combinations of genetic and environmental effects to define partitions that predict ischemic heart disease

dc.contributor.authorDyson, Gregen_US
dc.contributor.authorFrikke-Schmidt, Ruthen_US
dc.contributor.authorNordestgaard, Børge G.en_US
dc.contributor.authorTybjæ;rg-Hansen, Anneen_US
dc.contributor.authorSing, Charles F.en_US
dc.date.accessioned2009-05-04T18:27:44Z
dc.date.available2010-07-06T14:30:32Zen_US
dc.date.issued2009-05en_US
dc.identifier.citationDyson, Greg; Frikke-Schmidt, Ruth; Nordestgaard, BØrge G.; TybjÆ;rg-Hansen, Anne; Sing, Charles F. (2009). "Modifications to the Patient Rule-Induction Method that utilize non-additive combinations of genetic and environmental effects to define partitions that predict ischemic heart disease." Genetic Epidemiology 33(4): 317-324. <http://hdl.handle.net/2027.42/62158>en_US
dc.identifier.issn0741-0395en_US
dc.identifier.issn1098-2272en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/62158
dc.identifier.urihttp://www.ncbi.nlm.nih.gov/sites/entrez?cmd=retrieve&db=pubmed&list_uids=19025787&dopt=citationen_US
dc.description.abstractThis article extends the Patient Rule-Induction Method (PRIM) for modeling cumulative incidence of disease developed by Dyson et al. (Genet Epidemiol 31:515–527) to include the simultaneous consideration of non-additive combinations of predictor variables, a significance test of each combination, an adjustment for multiple testing and a confidence interval for the estimate of the cumulative incidence of disease in each partition. We employ the partitioning algorithm component of the Combinatorial Partitioning Method to construct combinations of predictors, permutation testing to assess the significance of each combination, theoretical arguments for incorporating a multiple testing adjustment and bootstrap resampling to produce the confidence intervals. An illustration of this revised PRIM utilizing a sample of 2,258 European male participants from the Copenhagen City Heart Study is presented that assesses the utility of genetic variants in predicting the presence of ischemic heart disease beyond the established risk factors. Genet. Epidemiol . 2009. © 2008 Wiley-Liss, Inc.en_US
dc.format.extent147630 bytes
dc.format.extent3118 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.publisherWiley Subscription Services, Inc., A Wiley Companyen_US
dc.subject.otherLife and Medical Sciencesen_US
dc.subject.otherGeneticsen_US
dc.titleModifications to the Patient Rule-Induction Method that utilize non-additive combinations of genetic and environmental effects to define partitions that predict ischemic heart diseaseen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelBiological Chemistryen_US
dc.subject.hlbsecondlevelGeneticsen_US
dc.subject.hlbsecondlevelMolecular, Cellular and Developmental Biologyen_US
dc.subject.hlbtoplevelHealth Sciencesen_US
dc.subject.hlbtoplevelScienceen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Human Genetics, University of Michigan, Ann Arbor, Michiganen_US
dc.contributor.affiliationumDepartment of Human Genetics, University of Michigan, Ann Arbor, Michigan ; Department of Human Genetics, University of Michigan, 1241 East Catherine Street, 5928 Buhl Building, Ann Arbor, MI 48109-0618en_US
dc.contributor.affiliationotherDepartment of Clinical Biochemistry, Section for Molecular Genetics, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmarken_US
dc.contributor.affiliationotherDepartment of Clinical Biochemistry, Herlev University Hospital, Herlev, Denmark ; The Copenhagen City Heart Study, Bispebjerg University Hospital, Copenhagen, Denmarken_US
dc.contributor.affiliationotherDepartment of Clinical Biochemistry, Section for Molecular Genetics, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark ; The Copenhagen City Heart Study, Bispebjerg University Hospital, Copenhagen, Denmarken_US
dc.identifier.pmid19025787en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/62158/1/20383_ftp.pdf
dc.identifier.doi10.1002/gepi.20383en_US
dc.identifier.sourceGenetic Epidemiologyen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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