Hostname: page-component-745bb68f8f-b95js Total loading time: 0 Render date: 2025-01-08T12:03:05.926Z Has data issue: false hasContentIssue false

On a Connection Between Factor Analysis and Multidimensional Unfolding

Published online by Cambridge University Press:  01 January 2025

Clyde H. Coombs
Affiliation:
University of Michigan
Richard C. Kao
Affiliation:
Planning Research Corporation Los Angeles, California

Abstract

Given 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.

Type
Original Paper
Copyright
Copyright © 1960 The Psychometric Society

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

*

The preparation of this paper was supported in part by a grant from the National Science Foundation and in part by Project MICHIGAN, a project of the University of Michigan in the field of Combat Surveillance sponsored by the Department of the Army. The contract (DA-36-039 ac 78801) is administered by the U. S. Army Signal Corps. The authors are indebted to L. A. Raphael, Caroline K. Tefft, and F. M. Goode for programming assistance, and to L. W. Staugas for providing other computer services during various stages of this study.

References

Anderson, T. W. An introduction to multivariate statistical analysis, New York: Wiley, 1958.Google Scholar
Bartlett, M. S. Tests of significance in factor analysis. Brit. J. Psychol., Statist. Sec., 1950, 3, 7785.CrossRefGoogle Scholar
Bartlett, M. S. The effect of standardization on aχ 2-approximation in factor analysis. Biometrika, 1951, 38, 337344.Google Scholar
Bartlett, M. S. A further note on tests of significance in factor analysis. Brit. J. Psychol., Statist. Sec., 1951, 4, 12.CrossRefGoogle Scholar
Bartlett, M. S. Factor analysis in psychology as a statistician sees it. Uppsala symposium on psychological factor analysis. Uppsala, Sweden: Almqvist and Wiksell, 1953, 2334.Google Scholar
Bennett, J. F. and Hays, W. L. Multidimensional unfolding: determining the dimensionality of ranked preference data. Psychometrika, 1960, 25, 2744.CrossRefGoogle Scholar
Coombs, C. H. Psychological scaling without a unit of measurement. Psychol. Rev., 1950, 57, 145158.CrossRefGoogle ScholarPubMed
Coombs, C. H. A theory of psychological scaling, Ann Arbor: Univ. Michigan Press, 1952.Google Scholar
Coombs, C. H. Social choice and strength of preferences. In Thrall, R. M., Coombs, C. H., Davis, R. L. (Eds.), Decision processes. New York: Wiley, 1954, 6986.Google Scholar
Coombs, C. H. Inconsistency of preferences in psychological measurement. J. exp. Psychol., 1958, 55, 17.CrossRefGoogle ScholarPubMed
Hays, W. L. and Bennett, J. F. Multidimensional unfolding: determining configuration from complete rank order preference data. Psychometrika. (in press).Google Scholar
Kendall, M. G. and Smith, B. B. Factor analysis. J. roy statist. Soc. (B), 1950, 12, 6094.CrossRefGoogle Scholar
MacRae, D. Jr. A factorial analysis of political preferences. Revue Francaise de Science Politique, 1958, 8, 95109.CrossRefGoogle Scholar
RAND Corporation. A million random digits with 100,000 normal deviates, Glencoe, Illinois: Free Press, 1955.Google Scholar
Tucker, L. R. A method for synthesis of factor analysis studies. Princeton: Educ. Test. Serv. Res. Bull. No. 984, 1951.CrossRefGoogle Scholar