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A PC program to aid in the choice of the design matrix in multiple linear regression

dc.contributor.authorFurey, Amy M.en_US
dc.contributor.authorKowalski, Charles J.en_US
dc.contributor.authorSchneiderman, Emet D.en_US
dc.contributor.authorWillis, Stephen M.en_US
dc.date.accessioned2006-04-10T15:40:37Z
dc.date.available2006-04-10T15:40:37Z
dc.date.issued1993-07en_US
dc.identifier.citationFurey, Amy M., Kowalski, Charles J., Schneiderman, Emet D., Willis, Stephen M. (1993/07)."A PC program to aid in the choice of the design matrix in multiple linear regression." International Journal of Bio-Medical Computing 33(1): 1-23. <http://hdl.handle.net/2027.42/30687>en_US
dc.identifier.urihttp://www.sciencedirect.com/science/article/B7GH2-4C88WFJ-N/2/260c5b2610e0073fa6c09f7557270285en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/30687
dc.identifier.urihttp://www.ncbi.nlm.nih.gov/sites/entrez?cmd=retrieve&db=pubmed&list_uids=8349356&dopt=citationen_US
dc.description.abstractA PC program, DESIGN, which can be used to evaluate and compare alternative choices of the design matrix, X, in the general linear model Y = X[beta] + [epsilon] is described, illustrated and made available to interested readers. Given X, the program (1) computes various measures of the `stability' of X and X'X and (2) determines the precisions of estimates of the model parameters, [beta], and of predicted values y, at the given design points. Examples focusing on polynomial regression are given.en_US
dc.format.extent1782669 bytes
dc.format.extent3118 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherElsevieren_US
dc.titleA PC program to aid in the choice of the design matrix in multiple linear regressionen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelPublic Healthen_US
dc.subject.hlbsecondlevelWest European Studiesen_US
dc.subject.hlbtoplevelHealth Sciencesen_US
dc.subject.hlbtoplevelSocial Sciencesen_US
dc.subject.hlbtoplevelHumanitiesen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USAen_US
dc.contributor.affiliationumDepartment of Oral Biology, University of Michigan, Ann Arbor, MI 48109, USAen_US
dc.contributor.affiliationotherDepartment of Oral and Maxillofacial Surgery, Baylor College of Dentistry, 3302 Gaston Ave., Dallas, TX 75246, USAen_US
dc.contributor.affiliationotherDepartment of Oral and Maxillofacial Surgery, Baylor College of Dentistry, 3302 Gaston Ave., Dallas, TX 75246, USAen_US
dc.identifier.pmid8349356en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/30687/1/0000332.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1016/0020-7101(93)90056-Cen_US
dc.identifier.sourceInternational Journal of Bio-Medical Computingen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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