On the Robustness of Multidimensional Scaling Techniques

Multidimensional scaling techniques are examined from the standpoint of their vulnerability to error. In particular, an integer-rank transformation is shown to provide a useful procedure for dealing with nonlinearities in the case of metric MDS.

[1]  Lawrence E. Jones,et al.  The effects of random error and subsampling of dimensions on recovery of configurations by non-metric multidimensional scaling , 1974 .

[2]  C. R. Sherman,et al.  Nonmetric multidimensional scaling: A monte carlo study of the basic parameters , 1972 .

[3]  John W. Tukey,et al.  Efficient Utilization of Non-Numerical Information in Quantitative Analysis General Theory and the Case of Simple Order , 1963 .

[4]  David Klahr,et al.  A monte carlo investigation of the statistical significance of Kruskal's nonmetric scaling procedure , 1969 .

[5]  Yoram Wind,et al.  Multiattribute decisions in marketing : a measurement approach , 1973 .

[6]  Forrest W. Young Nonmetric multidimensional scaling: Recovery of metric information , 1970 .

[7]  Paul E. Green,et al.  Rating Scales and Information Recovery—How Many Scales and Response Categories to Use? , 1970 .

[8]  I Spence,et al.  A TABLE OF EXPECTED STRESS VALUES FOR RANDOM RANKINGS IN NONMETRIC MULTIDIMENSIONAL SCALING. , 1973, Multivariate behavioral research.

[9]  Paul D. Isaac,et al.  On the determination of appropriate dimensionality in data with error , 1974 .

[10]  J. Kruskal Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis , 1964 .

[11]  P. Padmos,et al.  QUANTITATIVE INTERPRETATION OF STRESS IN KRUSKAL'S MULTIDIMENSIONAL SCALING TECHNIQUE , 1971 .

[12]  R. Shepard Metric structures in ordinal data , 1966 .

[13]  Joseph L. Zinnes,et al.  Theory and Methods of Scaling. , 1958 .

[14]  Herbert H. Stenson,et al.  GOODNESS OF FIT FOR RANDOM RANKINGS IN KRUSKAL'S NONMETRIC SCALING PROCEDURE * , 1969 .

[15]  On random rankings studies in nonmetric scaling , 1974 .