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Constrained Latent Class Analysis: Simultaneous Classification and Scaling of Discrete Choice Data

Published online by Cambridge University Press:  01 January 2025

Ulf Böckenholt  and
Ingo Böckenholt
Ulf Böckenholt*
Affiliation:
University of Illinois, Champaign-Urbana
Ingo Böckenholt
Affiliation:
University of Karlsruhe
*
Requests for reprints should be sent to Ulf Böckenholt, Department of Psychology, University of Illinois at Urbana-Champaign, 603 East Daniel Street, Champaign, IL 61820.
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Abstract

A reparameterization of a latent class model is presented to simultaneously classify and scale nominal and ordered categorical choice data. Latent class-specific probabilities are constrained to be equal to the preference probabilities from a probabilistic ideal-point or vector model that yields a graphical, multidimensional representation of the classification results. In addition, background variables can be incorporated as an aid to interpreting the latent class-specific response probabilities. The analyses of synthetic and real data sets illustrate the proposed method.

Keywords

latent class analysismultidimensional scalingclassification
Type
Original Paper
Information
Psychometrika , Volume 56 , Issue 4 , December 1991 , pp. 699 - 716
Copyright
Copyright © 1991 The Psychometric Society

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Footnotes

The authors thank Yosiho Takane, the editor and referees for their valuable suggestions. Authors are listed in reverse alphabetical order.

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