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Psychometrika

, Volume 41, Issue 4, pp 439–463 | Cite as

Spatial, non-spatial and hybrid models for scaling

  • J. Douglas Carroll
Article

Abstract

In this paper, hierarchical and non-hierarchical tree structures are proposed as models of similarity data. Trees are viewed as intermediate between multidimensional scaling and simple clustering. Procedures are discussed for fitting both types of trees to data. The concept of multiple tree structures shows great promise for analyzing more complex data. Hybrid models in which multiple trees and other discrete structures are combined with continuous dimensions are discussed. Examples of the use of multiple tree structures and hybrid models are given. Extensions to the analysis of individual differences are suggested.

Key words

multidimensional scaling hierarchical tree structures clustering geometric models multivariate data analysis 

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Reference notes

  1. Carroll, J. D., and Pruzansky, S. Fitting of hierarchical tree structure (HTS) models, mixtures of HTS models, and hybrid models, via mathematical programming and alternating least squares. Presented at theU.S.-Japan Seminar on Theory, Methods, and Applications of Multidimensional Scaling and related techniques, San Diego, Aug. 1975. Paper in informally published Proceedings of U.S.-Japan Seminar, available on request.Google Scholar
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Copyright information

© Psychometric Society 1976

Authors and Affiliations

  • J. Douglas Carroll
    • 1
  1. 1.Bell LaboratoriesMurray Hill

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