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A General Framework for using Latent Class Analysis to Test Hierarchical and Nonhierarchical Learning Models
Published online by Cambridge University Press: 01 January 2025
Abstract
Several articles in the past fifteen years have suggested various models for analyzing dichotomous test or questionnaire items which were constructed to reflect an assumed underlying structure. This paper shows that many models are special cases of latent class analysis. A currently available computer program for latent class analysis allows parameter estimates and goodness-of-fit tests not only for the models suggested by previous authors, but also for many models which they could not test with the more specialized computer programs they developed. Several examples are given of the variety of models which may be generated and tested. In addition, a general framework for conceptualizing all such models is given. This framework should be useful for generating models and for comparing various models.
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- Copyright © 1983 The Psychometric Society
Footnotes
Information about the Maximum Likelihood Latent Structure Analysis (MLLSA) computer program may be obtained from Clifford Clogg, Population Issues Research Office, 22 Burrowes Building, Pennsylvania State University, University Park, Pennsylvania 16802.
The author is indebted to Clifford Clogg, and two anonymous referees for comments which substantially improved this paper. They are not responsible for any errors which might remain.
Thanks also go to Ed Haertel for useful discussions about the general area, and for providing one of the data sets analyzed in the paper.
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