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On a connection between factor analysis and multidimensional unfolding
dc.contributor.authorCoombs, Clyde H.en_US
dc.contributor.authorKao, Richard C. W.en_US
dc.date.accessioned2006-09-11T16:22:33Z
dc.date.available2006-09-11T16:22:33Z
dc.date.issued1960-09en_US
dc.identifier.citationCoombs, Clyde H.; Kao, Richard C.; (1960). "On a connection between factor analysis and multidimensional unfolding." Psychometrika 25(3): 219-231. <http://hdl.handle.net/2027.42/45708>en_US
dc.identifier.issn0033-3123en_US
dc.identifier.issn1860-0980en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/45708
dc.description.abstractGiven the preference ordering of each of a number of individuals over a set of stimuli, it is proposed that if the preference orderings are generated in a Euclidean space of r dimensions which can be recovered by unfolding the preference orderings, then a factor analysis of the correlations between individual's preference orderings will yield a space of r + 1 dimensions with the original r -space embedded in it, and the additional dimension will be one of social utility. The proposition is clearly shown to be satisfied by means of the Monte Carlo technique for both random and lattice stimuli in three dimensions and for two other examples with random stimuli in one and two dimensions.en_US
dc.format.extent853492 bytes
dc.format.extent3115 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherSpringer-Verlag; Psychometric Societyen_US
dc.subject.otherStatistics for Social Science, Behavorial Science, Education, Public Policy, and Lawen_US
dc.subject.otherPsychologyen_US
dc.subject.otherStatistical Theory and Methodsen_US
dc.subject.otherPsychometricsen_US
dc.subject.otherAssessment, Testing and Evaluationen_US
dc.titleOn a connection between factor analysis and multidimensional unfoldingen_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelPsychologyen_US
dc.subject.hlbtoplevelSocial Sciencesen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumUniversity of Michigan, USAen_US
dc.contributor.affiliationotherPlanning Research Corporation, Los Angeles, Californiaen_US
dc.contributor.affiliationumcampusAnn Arboren_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/45708/1/11336_2005_Article_BF02289726.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1007/BF02289726en_US
dc.identifier.sourcePsychometrikaen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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