Hostname: page-component-745bb68f8f-lrblm Total loading time: 0 Render date: 2025-01-07T17:47:18.312Z Has data issue: false hasContentIssue false

A Further Comparison of Oblique Factor Transformation Methods

Published online by Cambridge University Press:  01 January 2025

A. Ralph Hakstian
Affiliation:
University of British Columbia
Robert A. Abell
Affiliation:
University of Alberta

Abstract

Four prominent oblique transformation techniques—promax, the Harris-Kaiser procedure, biquartimin, and direct oblimin—are examined and compared. Additionally, two newly-developed procedures, falling into the category designated as Case III by Harris and Kaiser [1964], are presented and included in the comparisons. The techniques are compared in light of their freedom from bias in the interfactor correlations, and their ability to yield clear simple structures, over many data sets—some constructed and some “real”—varying widely in terms of number of variables and factors, factorial complexity, and clarity of the hyperplanes. Results are discussed, and implications for practice are noted.

Type
Original Paper
Copyright
Copyright © 1974 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.)

References

Carroll, J. B. Biquartimin criterion for rotation to oblique simple structure in factor analysis. Science, 1957, 126, 11141115.CrossRefGoogle ScholarPubMed
Cattell, R. B. and Muerle, J. L. The “maxplane” program for factor rotation to oblique simple structure. Educational and Psychological Measurement, 1960, 20, 569590.CrossRefGoogle Scholar
Degan, J. W. Dimensions of functional psychosis. Psychometric Monographs, No. 6, 1952.Google Scholar
Hakstian, A. R. A comparative evaluation of several prominent methods of oblique factor transformation. Psychometrika, 1971, 36, 175193.CrossRefGoogle Scholar
Hakstian, A. R. Optimizing the resolution between salient and non-salient factor pattern coefficients. British Journal of Mathematical and Statistical Psychology, 1972, 25, 229245.CrossRefGoogle Scholar
Harman, H. H. Modern factor analysis, 2nd ed., Chicago: University of Chicago Press, 1967.Google Scholar
Harris, C. W. and Kaiser, H. F. Oblique factor analytic solutions by orthogonal transformations. Psychometrika, 1964, 29, 347362.CrossRefGoogle Scholar
Hendrickson, A. E.and White, P. O. PROMAX: A quick method for rotation to oblique simple structure. British Journal of Statistical Psychology, 1964, 17, 6570.CrossRefGoogle Scholar
Horn, J. L. Second-order factors in questionnaire data. Educational and Psychological Measurement, 1963, 23, 117134.CrossRefGoogle Scholar
Jennrich, R. I. and Sampson, P. F. Rotation for simple loadings. Psychometrika, 1966, 31, 313323.CrossRefGoogle ScholarPubMed
Pemberton, C. The closure factors related to other cognitive processes. Psychometrika, 1952, 17, 267288.CrossRefGoogle Scholar
Saunders, D. R. The rationale for an “oblimax” method of transformation in factor analysis. Psychometrika, 1961, 26, 317324.CrossRefGoogle Scholar
Thurstone, L. L. Multiple-factor analysis, 1947, Chicago: University of Chicago Press.Google Scholar