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The Rationale for an “Oblimax” Method of Transformation in Factor Analysis

Published online by Cambridge University Press:  01 January 2025

D. R. Saunders
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Abstract

Factorial transformation is viewed as an estimation problem in which the usual assumption of homogeneously distributed error cannot be applied, but may be replaced by a principle of maximum kurtosis. This leads to quartimax in the orthogonal case, and to “oblimax” in the oblique case. Oblimax is readily programmable, and typically provides results similar to those of subjective rotation. However, oblimax may encounter special difficulty in data which do not determine a simple structure, or which have been imprecisely factored.

Type
Original Paper
Information
Psychometrika , Volume 26 , Issue 3 , September 1961 , pp. 317 - 324
Copyright
Copyright © 1961 The Psychometric Society

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Footnotes

*

The Managing Editor has substituted the word “transformation” for the word “rotation” in the title and throughout this paper, on the grounds that “oblique rotation” is a self-contradictory term, the use of which need not be perpetuated.

†

This paper is primarily a condensation of material that first appeared in ETS Research Bulletins 53-10 and 54-31, both long out of print. In this treatment the principle of maximum kurtosis receives increased emphasis, and the special case for equation (10) is recognized. The writer is indebted to his former colleagues, Mr. Charles Pinzka and Dr. Ledyard Tucker, for invaluable assistance in achieving a straightforward and general derivation of equation (10).

References

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