Generalized Latent Class Analysis: A New Methodology for Market Structure Analysis

  • I. Böckenholt
  • W. Gaul


In this paper a generalization of LCA (Latent Class Analysis) is presented which allows a simultaneous classification and MDS (MultiDimensional Scaling) of ordered categorical data. This approach is managerially useful in several ways, because additional background variables can be directly incorporated to identify latent class specific response probabilities. Furthermore, this technique allows a graphical representation of the classification results obtained. Essential features of the methodology will be demonstrated in the empirical part of this paper.


Latent Class Market Structure Ideal Point Latent Class Analysis Latent Class Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. AKAIKE, H.: On Entropy Maximization Principle, in: Krishnaiah, P.R. (ed.), Applications of Statistics, North Holland, Amsterdam, 1977, 27 – 41.Google Scholar
  2. BÖCKENHOLT, I.: Mehrdimensionale Skalierung qualitativer Daten: Ein Instrument zur Unterstützung von Marketingentscheidungen, Lang, Frankfurt, 1989.Google Scholar
  3. BÖCKENHOLT, I., GAUL, W.: Analysis of Choice Behavior via Probabilistic Ideal Point and Vector Models, Applied Stochastic Models and Data Analysis, 2, 1986, 202 – 226.CrossRefGoogle Scholar
  4. DE SARBO, W., HOFFMAN, D.: Simple and Weigthed Unfolding Threshold Models for the Spatial Representation of Binary Choice Data, Applied Psychological Measurement, 10, 1986, 247 – 264.CrossRefGoogle Scholar
  5. FORMANN, A.K.: Die Latent-Class-Analyse, Beltz, Weinheim, 1984.Google Scholar
  6. GOODMAN, L.A.: Analysing Qualitative/Categorical Data: Log-Linear Models and Latent-Structure Analysis, Abt Books, Cambridge, Mass., 1978.Google Scholar
  7. GOODMAN, L.A.: On the Estimation of Parameters in Latent Structure Analysis, Psychometrika, 44, 1979, 123 – 128.MathSciNetCrossRefGoogle Scholar
  8. GROVER, R., DILLON, W. R.: A Probabilistic Model for Testing Hypothesized Hierarchical Market Structure, Marketing Science, 4, 1985, 312 – 335.CrossRefGoogle Scholar
  9. GROVER, R., SRINIVASAN, V.: A Simultaneous Approach to Market Segmentation and Market Structuring, Journal of Marketing Research, 24, 1986, 139 – 153.CrossRefGoogle Scholar
  10. LAZARSFELD, P. F.: Logical and Mathematical Foundations of Latent Structure Analysis, in: Stouffer, S. A. et al. (eds.), Studies in Social Psychology in World War II, Vol. IV, Princeton Univ. Press, Princeton, N.J., 1950.Google Scholar
  11. ROST, J.: A Latent Class Model for Rating Data, Psychometrika, 50, 1985, 37 – 49.CrossRefGoogle Scholar
  12. ROST, J.: Rating Scale Analysis with Latent Class Models, Psychometrika, 53, 1988, 327 – 348.Google Scholar

Copyright information

© Springer-Verlag Berlin · Heidelberg 1989

Authors and Affiliations

  • I. Böckenholt
    • 1
  • W. Gaul
    • 1
  1. 1.Institut für Entscheidungstheorie und UnternehmensforschungUniversität Karlsruhe (TH)Germany

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