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CLASSI: A classification model for the study of sequential processes and individual differences therein

Published online by Cambridge University Press:  01 January 2025

Eva Ceulemans and
Iven Van Mechelen
Eva Ceulemans*
Affiliation:
Katholieke Universiteit Leuven
Iven Van Mechelen
Affiliation:
Katholieke Universiteit Leuven
*
Requests for reprints should be sent to Eva Ceulemans, Department of Psychology, Katholieke Universiteit Leuven, Tiensestraat 102, 3000 Leuven, Belgium. E-mail: Eva.Ceulemans@psy.kuleuven.be
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Abstract

In psychological research, one often aims at explaining individual differences in S-R profiles, that is, individual differences in the responses (R) with which people react to specific stimuli (S). To this end, researchers often postulate an underlying sequential process, which boils down to the specification of a set of mediating variables (M) and the processes that link these mediating variables to the stimuli and responses under study. Obviously, a crucial task is to chart how the individual differences in the S-R profiles are caused by individual differences in the S-M link and/or by individual differences in the M-R link. In this paper we propose a new model, called CLASSI, which was explicitly designed for this task. In particular, the key principle of CLASSI consists of reducing the S, M, and R nodes of a sequential process to a few mutually exclusive types and inducing an S-M and an M-R person typology from the data, with the S-M person types being characterized in terms of if S type then M type rules and the M-R person types in terms of if M type then R type rules. As such, the S-M and M-R person types and their associated if–then rules represent the important individual differences in the S-M and M-R links of the sequential process under study. An algorithm to fit the CLASSI model is described and evaluated in a simulation study. An application of CLASSI to data from the behavioral domain of anger and sadness is discussed. Finally, we relate CLASSI to other methods and discuss possible extensions.

Keywords

sequential processindividual differencesmultiway clusteringclassificationsimulated annealing

Information

Type
Theory and Methods
Information
Psychometrika , Volume 73 , Issue 1 , March 2008, pp. 107 - 124
Copyright
Copyright © 2007 The Psychometric Society

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Footnotes

The first author is a post-doctoral fellow of the Fund for Scientific Research—Flanders (Belgium). The research reported in this paper was partially supported by the Research Council of K.U. Leuven (GOA/05/04).

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