Abstract
An interactive strategy for applying cluster-analytic techniques in behavioral research is presented. The two-part approach stresses the use of on-line computers for both data collection and analysis. In data collection, an extension of multidimensional unfolding to clustering reduces the number of judgments required of subjects by as much as 50%, During data analysis, the interactive procedures described permit the testing of multiple clustering models from an extensive family. With each selection, the goodness of fit of the model to the data can be tested. In addition to improving efficiency, the interactive strategy promoted here combines the advantages of the original nonmetric clustering procedures (e.g., Johnson, 1967) with those of the latest linear additive models (e.g., Sattath & Tversky, 1977; Shepard & Arabie, 1979).
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