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A comparative evaluation of several prominent methods of oblique factor transformation

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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.

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Authors and Affiliations

  1. University of Alberta, Canada

    A. Ralph Hakstian

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  1. A. Ralph Hakstian
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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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Ralph Hakstian, A. A comparative evaluation of several prominent methods of oblique factor transformation. Psychometrika 36, 175–193 (1971). https://doi.org/10.1007/BF02291397

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  • DOI: https://doi.org/10.1007/BF02291397

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