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Best Univocal Estimates of Orthogonal Common Factors

Published online by Cambridge University Press:  01 January 2025

A. Ralph Hakstian ,
James V. Zidek  and
Roderick P. McDonald
A. Ralph Hakstian*
Affiliation:
University of British Columbia
James V. Zidek
Affiliation:
University of British Columbia
Roderick P. McDonald
Affiliation:
The Ontario Institute for Studies in Education
*
Requests for reprints should be sent to A. Ralph Hakstian, Department of Psychology, University of British Columbia, Vancouver, British Columbia, CANADA.
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Abstract

A general formulation is presented for obtaining conditionally unbiased, univocal common-factor score estimates that have maximum validity for the true orthogonal factor scores. We note that although this expression is formally different from both Bartlett's formulation and Heermann's approximate expression, all three, while developed from very different rationales, yield identical results given that the common-factor model holds for the data. Although the true factor score validities can be raised by a different non-orthogonal transformation of orthogonalized regression estimates—as described by Mulaik—the resulting estimates lose their univocality.

Keywords

factor scorescommon-factor analysisunivocal factor score estimates

Information

Type
Notes And Comments
Information
Psychometrika , Volume 42 , Issue 4 , December 1977 , pp. 627 - 630
Copyright
Copyright © 1977 The Psychometric Society

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References

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