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Re-Evaluation of Monte Carlo Studies in Nonmetric Multidimensional Scaling

Published online by Cambridge University Press:  01 January 2025

Andrew K. Clark
Andrew K. Clark*
Affiliation:
University of Alberta
*
Requests for reprints should be sent to Andrew K. Clark, Department of Industrial and Vocational Education, the University of Alberta, Edmonton, Alberta, Canada T6G OY1.
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Abstract

Critical examination is made of the recent controversy over the value of Monte Carlo techniques in nonmetric multidimensional scaling procedures. The case is presented that the major relevance of Monte Carlo studies is not for the local minima problem but for the meaningfulness of the obtained solutions.

Keywords

significanceconfigurationminima (local)
Type
Original Paper
Information
Psychometrika , Volume 41 , Issue 3 , September 1976 , pp. 401 - 403
Copyright
Copyright © 1976 The Psychometric Society

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References

Reference Note

Kruskal, J. B. & Carmone, F. How to use MDSCAL (version 5M) and other useful information. Unpublished manuscript, 1969.Google Scholar

References

Arabie, P. Concerning Monte Carlo evaluations of nonmetric multidimensional scaling algorithms. Psychometrika, 1973, 38, 607–608.CrossRefGoogle Scholar
Klahr, D. A Monte Carlo investigation of the statistical significance of Kruskal's nonmetric scaling procedure. Psychometrika, 1969, 34, 319–330.CrossRefGoogle Scholar
Lingoes, J. C., & Roskam, E. E. A mathematical and empirical study of two multidimensional scaling algorithms. Psychometrika Monograph Supplement, 1973, 38, 4–4.Google Scholar
Shepard, R. N. The analysis of proximities: Multidimensional scaling with an unknown distance function. I.. Psychometrika, 1962, 27, 125–140.CrossRefGoogle Scholar
Shepard, R. N. Metric structures in ordinal data. Journal of Mathematical Psychology, 1966, 3, 287–315.CrossRefGoogle Scholar
Shepard, R. N. Representation of structure in similarity data: Problems and prospects. Psychometrika, 1974, 39, 373–421.CrossRefGoogle Scholar
Spaeth, H. J., & Guthery, S. B. The use and utility of the monotone criterion in multi-dimensional scaling. Multivariate Behavioral Research, 1969, 4, 501–515.CrossRefGoogle Scholar
Stenson, H. H. & Knoll, R. L. Goodness of fit for random rankings in Kruskal's nonmetric scaling procedure. Psychological Bulletin, 1969, 71, 122–126.CrossRefGoogle Scholar
Wagenaar, W. A., & Padmos, P. Quantitative interpretation of stress in Kruskal's multi-dimensional scaling technique. British Journal of Mathematical and Statistical Psychology, 1971, 24, 101–110.CrossRefGoogle Scholar