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The Comparison of Interdependent Correlations between Optimal Linear Composites

Published online by Cambridge University Press:  01 January 2025

James H. Steiger  and
Michael W. Browne
James H. Steiger*
Affiliation:
University of British Columbia
Michael W. Browne
Affiliation:
University of South Africa
*
Requests for reprints and details of a FORTRAN program useful in computing the significance tests described in this article should be sent to James H. Steiger, Department of Psychology, University of British Columbia, Vancouver, B.C., Canada V6T 1Y7.
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Abstract

A general procedure is provided for comparing correlation coefficients between optimal linear composites. The procedure allows computationally efficient significance tests on independent or dependent multiple correlations, partial correlations, and canonical correlations, with or without the assumption of multivariate normality. Evidence from some Monte Carlo studies on the effectiveness of the methods is also provided.

Keywords

asymptotic distribution theorycorrelational significance testsmultiple correlationpartial correlationcanonical correlation

Information

Type
Original Paper
Information
Psychometrika , Volume 49 , Issue 1 , March 1984 , pp. 11 - 24
Copyright
Copyright © 1984 The Psychometric Society

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Footnotes

This research was supported in part by an operating grant (#67-4640) to the first author from the National Sciences and Engineering Research Council of Canada. The authors would also like to acknowledge the helpful comments and encouragement of Alexander Shapiro, Stanley Nash, and Ingram Olkin.

References

Reference Notes

Steiger, J. H. (1980). K-sample pattern hypotheses on correlation matrices by the method of generalized least squares. University of British Columbia, Institute of Applied Mathematics and Statistics Research Bulletin 80-2.Google Scholar
Steiger, J. H. (June 2, 1982). A robust large-sample procedure for comparing dependent correlations. Paper presented at the annual Spring Meeting of the Psychometric Society.Google Scholar

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