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Standard Errors for Rotated Factor Loadings

Published online by Cambridge University Press:  01 January 2025

Claude O. Archer
Affiliation:
Naval Missile Center
Robert I. Jennrich
Affiliation:
University of California at Los Angeles and Educational Testing Service

Abstract

Beginning with the results of Girshick on the asymptotic distribution of principal component loadings and those of Lawley on the distribution of unrotated maximum likelihood factor loadings, the asymptotic distribution of the corresponding analytically rotated loadings is obtained. The principal difficulty is the fact that the transformation matrix which produces the rotation is usually itself a function of the data. The approach is to use implicit differentiation to find the partial derivatives of an arbitrary orthogonal rotation algorithm. Specific details are given for the orthomax algorithms and an example involving maximum likelihood estimation and varimax rotation is presented.

Type
Original Paper
Copyright
Copyright © 1973 The Psychometric Society

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Footnotes

*

This research was supported in part by NIH Grant RR-3. The authors are grateful to Dorothy T. Thayer who implemented the algorithms discussed here as well as those of Lawley and Maxwell. We are particularly indebted to Michael Browne for convincing us of the significance of this work and for helping to guide its development and to Harry H. Harman who many years ago pointed out the need for standard errors of estimate.

References

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