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A Monte Carlo Study of Kruskal’s Variance based Measure on Stress

Published online by Cambridge University Press:  01 January 2025

David M. Levine
David M. Levine*
Affiliation:
Bernard Baruch College (CUNY)
*
Requests for reprints should be sent to David M. Levine, Department of Statistics, Bernard M. Baruch College, 17 Lexington Ave., New York, N. Y. 10010.
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Abstract

Researchers in the past ten years have studied various parameters involved in nonmetric multidimensional scaling by utilizing Monte Carlo procedures. This paper develops stress distributions using Kruskal's second stress formula based upon a null hypothesis of equal likelihood in the ranking of a set of proximities. These distributions can serve to determine whether a set of data has other than random structure.

Keywords

nonmetric multidimensional scalingstress distributionstests of randomness
Type
Original Paper
Information
Psychometrika , Volume 43 , Issue 3 , September 1978 , pp. 307 - 315
Copyright
Copyright © 1978 The Psychometric Society

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Footnotes

The author would like to thank Dr. Joseph Kruskal and three anonymous reviewers for their helpful suggestions on an earlier draft of this paper.

This research was supported in part by a grant from the Baruch College Scholar Assistance program.

References

Reference Notes

Kruskal, J. B. & Carmone, F. J. How to use M-D-SCAL (Version 5M) and other useful information, 1969, Murray Hill, N. J.: Bell Telephone Laboratories.Google Scholar
Levine, D. Estimation of the statistical significance of Kruskal's measure of stress for an asymmetric matrix. Unpublished manuscript, 1976.Google Scholar

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