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Scaling a Conditional Proximity Matrix to Symmetry

Published online by Cambridge University Press:  01 January 2025

Joseph Levin*
Affiliation:
Tel-Aviv University
Morton Brown
Affiliation:
Tel-Aviv University
*
Requests for reprints should be sent to Dr. Joseph Levin, Department of Psychology, Tel-Aviv University, ISRAEL.

Abstract

Two least squares procedures for symmetrization of a conditional proximity matrix are derived. The solutions provide multiplicative constants for scaling the rows or columns of the matrix to maximize symmetry. It is suggested that the symmetrization is applicable for the elimination of bias effects like response bias, or constraints on the marginal frequencies imposed by the experimental design, as in confusion matrices.

Type
Notes And Comments
Copyright
Copyright © 1979 The Psychometric Society

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Footnotes

The application of the scaling procedure to a matrix of conditional probabilities was suggested by one of the referees, whose helpful comments are gratefully acknowledged.

References

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