Psychometrika

, Volume 36, Issue 2, pp 175–193 | Cite as

A comparative evaluation of several prominent methods of oblique factor transformation

  • A. Ralph Hakstian
Article
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Revised:

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 Policy Statistical Theory Primary Factor Comparative Evaluation Factor Correlation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Psychometric Society 1971

Authors and Affiliations

  • A. Ralph Hakstian
    • 1
  1. 1.University of AlbertaCanada

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