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Arabie, Phipps – Psychometrika, 1978
The issue of whether one should use a single or several random initial configurations in multidimensional scaling is disucssed in this brief note. It is a response to the preceding article (TM 503 491), which commented on another article by Arabie (TM 503 490). (JKS)
Descriptors: Computer Programs, Goodness of Fit, Measurement, Multidimensional Scaling
Peer reviewed Peer reviewed
Harris, David R.; Fenker, Richard – Journal of Educational and Psychological Measurement, 1974
Descriptors: Computer Programs, Goodness of Fit, Individual Differences, Multidimensional Scaling
Peer reviewed Peer reviewed
Spence, Ian; Graef, Jed – Multivariate Behavioral Research, 1974
Descriptors: Computer Programs, Distance, Goodness of Fit, Matrices
Peer reviewed Peer reviewed
Ramsay, J. O. – Psychometrika, 1980
Some aspects of the small sample behavior of maximum likelihood estimates in multidimensional scaling are investigated with Monte Carlo techniques. In particular, the chi square test for dimensionality is examined and a correction for bias is proposed and evaluated. (Author/JKS)
Descriptors: Computer Programs, Goodness of Fit, Maximum Likelihood Statistics, Multidimensional Scaling
Peer reviewed Peer reviewed
Cooper, Lee G. – Psychometrika, 1972
Descriptors: Computer Programs, Goodness of Fit, Mathematical Applications, Multidimensional Scaling
Peer reviewed Peer reviewed
Johnson, Richard M. – Psychometrika, 1973
A method of nonmetric multidimensional scaling is described which minimizes pairwise departures from monotonicity. (Author)
Descriptors: Algorithms, Calculus, Computer Programs, Data Analysis
Peer reviewed Peer reviewed
Carroll, Robert M.; And Others – Educational and Psychological Measurement, 1972
A copy of the computer program, which determines the transformation matrix used to rotate the configuration, the dilation factor, and the translation vector, is available from the first author. (CB)
Descriptors: Computer Programs, Factor Analysis, Factor Structure, Goodness of Fit