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Latent Change Classes in Dichotomous Data

Published online by Cambridge University Press:  01 January 2025

Anton K. Formann  and
Ivo Ponocny
Anton K. Formann*
Affiliation:
University of Vienna
Ivo Ponocny
Affiliation:
University of Vienna
*
Requests for reprints should be sent to Anton K. Formann, Institut für Psychologie, Universität Wien, Liebiggasse 5, A-1010 Wien, AUSTRIA. E-Mail: [email protected]
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Abstract

Changes in dichotomous data caused by treatments can be analyzed by means of the so-called linear logistic model with relaxed assumptions (LLRA). The LLRA does not require observable criteria representing a single underlying latent trait, but it postulates the generalizability of the treatment effects over criteria and subjects. To test this latter crucial assumption, the mixture LLRA was proposed that allows directly unobservable types of subjects to have different treatment effects. As the earlier methods for estimating the parameters of the mixture LLRA have specific drawbacks, a further method based on the conditional maximum likelihood principle will be presented here. In contrast to the earlier conditional methods, it uses all of the dichotomous change data while having fewer parameters. Further, its goodness-of-fit tests become more sensitive to a falsely specified number of change-types even though the treatment effects are biased. For typically occurring small to moderate sample sizes, however, parametric bootstrapping of the distributions of the fit statistics is recommended for performing hypotheses tests. Finally, three applications of the new method to empirical data are described: first, about the effect of the so-called Trager psychophysical integration, second, about the effect of autogenic therapy on patients with psychosomatic symptoms, and, third, about the effect of religious education on the attitude towards sects.

Keywords

latent heterogeneitylinear logistic modelslocal stochastic independencemixture binomial(parametric) bootstrappingpanel datatreatment effect
Type
Articles
Information
Psychometrika , Volume 67 , Issue 3 , September 2002 , pp. 437 - 457
Copyright
Copyright © 2002 The Psychometric Society

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Footnotes

The mixture LLRA is implemented in the menu-driven program MIXLLRA which can be obtained from Ivo Ponocny via e-mail ([email protected]).

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