Abstract
A method for nonmetric interactive multidimen sional scaling (MDS) of similarity judgments is de scribed which is also capable of using responses from previous judges to supplement the judgments of a current subject. The method combines recent advances in interactive MDS with recent advances in numerical methods in MDS to produce a pro gram capable (1) of performing nonmetric interac tive MDS and (2) of fitting a wide variety of models, such as the individual differences model. The empirical investigation compared three versions of the system: (1) a metric simple Euclidean model- fitting version (similar to previous interactive scal ing programs); (2) a metric individual differences version; and (3) a nonmetric individual differences version. There were no statistically significant dif ferences among the three versions.
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