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Maximally Correlated Orthogonal Composites and Oblique Factor Analytic Solutions

Published online by Cambridge University Press:  01 January 2025

James M. Price  and
W. Alan Nicewander
James M. Price
Affiliation:
University of Oklahoma
W. Alan Nicewander*
Affiliation:
University of Oklahoma
*
Requests for reprint should be sent to Dr. W. Alan Nicewander, Department of Psychology, University of Oklahoma, Norman, Oklahoma 73069.
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Abstract

Kaiser presented a method for finding a set of derived orthogonal variables which correlate maximally with a set of original variables. A simpler, more complete derivation of Kaiser's result is given and compared to related types of transformations. The transformation derived here suggests a direct method for finding the orthogonal factor solution which is maximally similar to a given oblique solution.

Keywords

factor analysisProcrustestransformation
Type
Notes And Comments
Information
Psychometrika , Volume 42 , Issue 3 , September 1977 , pp. 439 - 442
Copyright
Copyright © 1977 The Psychometric Society

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References

Reference Notes

Schönemann, P. H. On the formal differentiation of traces and determinants, 1965, Chapel Hill: L. L. Thurstone Psychometric Laboratory, University of North Carolina.Google Scholar

References

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Kaiser, H. F. Uncorrelated linear composites maximally related to a complex of correlated observations. Educational and Psychological Measurement, 1967, 27, 3–6.CrossRefGoogle Scholar
Schönemann, P. H. A generalized solution of the orthogonal Procrustes problem. Psychometrika, 1966, 31, 1–10.CrossRefGoogle Scholar