A reformulation of the general Euclidean model for the external analysis of preference data

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Abstract

This paper discusses least squares methods for fitting a reformulation of the general Euclidean model for the external analysis of preference data. The reformulated subject weights refer to a common set of reference vectors for all subjects and hence are comparable across subjects. If the rotation of the stimulus space is fixed, the subject weight estimates in the model are uniquely determined. Weight estimates can be guaranteed nonnegative. While the reformulation is a metric model for single stimulus data, the paper briefly discusses extensions to nonmetric, pairwise, and logistic models. The reformulated model is less general than Carroll's earlier formulation.

Original languageEnglish (US)
Pages (from-to)305-320
Number of pages16
JournalPsychometrika
Volume53
Issue number3
DOIs
StatePublished - Sep 1 1988

Keywords

  • multidmensional scaling
  • preference data
  • regression

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