Abstract
Various methods are discussed that emphasize the graphical representation of results from the analysis of multivariate data. Specifically, qualitative (or categorical) multivariate data will be considered, where observed variables are only partially known, and dealt with by using an optimal scaling framework that replaces nominal and ordinal variables by optimally quantified variables. The approach to graphical display that is advocated is closely related to techniques of multidimensional scaling, and involves the choice of particular standardizations and metrics to be used.
“Many measurement models in the behavioral sciences are based on geometric representations of the observed behavior. Frequently this geometric representation is a one-dimensional scale but it need not be, and multidimensional representations are becoming more common. The points on these scales or in these spaces may represent individuals or stimuli or both, and the relations among the points reflect the observations according to some rule.” (Coombs, Dawes & Tversky, 1970, p. 32).
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Meulman, J.J. (1998). Optimal Scaling Methods for Graphical Display of Multivariate Data. In: Payne, R., Green, P. (eds) COMPSTAT. Physica, Heidelberg. https://doi.org/10.1007/978-3-662-01131-7_6
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DOI: https://doi.org/10.1007/978-3-662-01131-7_6
Publisher Name: Physica, Heidelberg
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