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Factor Analysis by Minimizing Residuals (Minres)

Published online by Cambridge University Press:  01 January 2025

Harry H. Harman
Affiliation:
System Development Corporation
Wayne H. Jones
Affiliation:
System Development Corporation

Abstract

This paper is addressed to the classical problem of estimating factor loadings under the condition that the sum of squares of off-diagonal residuals be minimized. Communalities consistent with this criterion are produced as a by-product. The experimental work included several alternative algorithms before a highly efficient method was developed. The final procedure is illustrated with a numerical example. Some relationships of minres to principal-factor analysis and maximum-likelihood factor estimates are discussed, and several unresolved problems are pointed out.

Type
Original Paper
Copyright
Copyright © 1966 Psychometric Society

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Footnotes

*

The authors wish to thank the Factor Analysis Work Group (supported, in part, by ONR) for valuable criticisms and suggestions made in the course of a discussion of the present work in April, 1965.

Now with the Department of Defense.

References

Bargmann, R. Factor analysis program for 7090 preliminary version. IBM Research Center, Inter. Doc. 28–126, October 1963.Google Scholar
Boldt, R. F. Factoring to fit off diagonals. Psychometrika (in press).Google Scholar
Comrey, A. L. The minimum residual method of factor analysis. Psychol. Reports, 1962, 11, 1518.CrossRefGoogle Scholar
Eckart, C. and Young, G. The approximation of one matrix by another of lower rank. Psychometrika, 1936, 1, 211218.Google Scholar
Finkel, R. W. The method of resultant descents for the minimization of an arbitrary function. Paper 71, preprint of paper presented at 14th National Meeting of Association of Computing Machinery, 1959.CrossRefGoogle Scholar
Gengerelli, J. A. A simplified method for approximating multiple regression coefficients. Psychometrika, 1948, 13, 135146.CrossRefGoogle ScholarPubMed
Harman, H. H. Modern factor analysis, Chicago, Ill.: Univ. Chicago Press, 1960.Google Scholar
Horst, P. A method of factor analysis by means of which all coordinates of the factor matrix are given simultaneously. Psychometrika, 1937, 2, 225236.CrossRefGoogle Scholar
Householder, A. S., Young, G. Matrix approximation and latent roots. Amer. math. Monthly, 1938, 45, 165171.CrossRefGoogle Scholar
Hotelling, H. Analysis of a complex of statistical variables into principal components. J. educ. Psychol., 1933, 24, 417441.CrossRefGoogle Scholar
Howe, W. G. Some contributions to factor analysis. Report No. ORNL-1919, Oak Ridge, Tenn.: Oak Ridge National Laboratory, 1955.Google Scholar
Jöreskog, K. G. Testing a simple structure hypothesis in factor analysis, Princeton, N. J.: Educ. Test. Serv., 1965.Google Scholar
Keller, J. B. Factorization of matrices by least-squares. Biometrika, 1962, 49, 239242.CrossRefGoogle Scholar
Lawley, D. N. A modified method of estimation in factor analysis and some large sample results. Uppsala Symposium on Psychological Factor Analysis. Uppsala: Almqvist & Wiksell, 1953, 3542.Google Scholar
Shah, B. V., Buehler, R. J., and Kempthorne, O. Some algorithms for minimizing a function of several variables. J. Society for Industrial and Applied Mathematics, 1964, 12, 7492.Google Scholar
Spang, H. A. III A review of minimization techniques for nonlinear functions. SIAM Review, 1962, 4, 343365.Google Scholar
Thurstone, L. L. Multiple-factor analysis, Chicago, Ill.: Univ. Chicago Press, 1947.Google Scholar
Thurstone, L. L. A method of factoring without communalities. 1954 Invitational Conference on Testing Problems. Princeton, N. J.: Educ. Test. Serv., 1955, 5962.Google Scholar
Whittaker, E. and Robinson, G. The calculus of observations, London: Blackie & Son, 1944.Google Scholar
Whittle, P. On principal components and least square methods of factor analysis. Skand. Aktuar., 1952, 35, 223239.Google Scholar