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A Comparative Evaluation of Several Prominent Methods of Oblique Factor Transformation

Published online by Cambridge University Press:  01 January 2025

A. Ralph Hakstian
A. Ralph Hakstian*
Affiliation:
University of Alberta
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Abstract

The oblimax, promax, maxplane, and Harris-Kaiser techniques are compared. For five data sets, of varying reliability and factorial complexity, each having a graphic oblique solution (used as criterion), solutions obtained using the four methods are evaluated on (1) hyperplane-counts, (2) agreement of obtained with graphic within-method primary factor correlations and angular separations, (3) angular separations between obtained and corresponding graphic primary axes. The methods are discussed and ranked (descending order): Harris-Kaiser, promax, oblimax, maxplane. The Harris-Kaiser procedure—independent cluster version for factorially simple data, P'P proportional to Φ, with equamax rotations, for complex—is recommended.

Keywords

Public PolicyStatistical TheoryPrimary FactorComparative EvaluationFactor Correlation
Type
Original Paper
Information
Psychometrika , Volume 36 , Issue 2 , June 1971 , pp. 175 - 193
Copyright
Copyright © 1971 The Psychometric Society

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Footnotes

*

This paper is based upon part of the author's doctoral dissertation [Hakstian, 1969] completed at the University of Colorado. The author is greatly indebted to Dr. Gene V Glass, who, as thesis advisor, generously contributed his time, erudition, and encouragement.

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