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The CLASSI-N Method for the Study of Sequential Processes

Published online by Cambridge University Press:  01 January 2025

Eva Vande Gaer ,
Eva Ceulemans ,
Iven Van Mechelen  and
Peter Kuppens
Eva Vande Gaer*
Affiliation:
Katholieke Universiteit Leuven
Eva Ceulemans
Affiliation:
Katholieke Universiteit Leuven
Iven Van Mechelen
Affiliation:
Katholieke Universiteit Leuven
Peter Kuppens
Affiliation:
Katholieke Universiteit Leuven
*
Requests for reprints should be sent to Eva Vande Gaer, Methodology of Educational Sciences Research Group and Research Group of Quantitative Psychology and Individual Differences, Katholieke Universiteit Leuven, Andreas Vesaliusstraat 2, P.O. Box 3762, 3000 Leuven, Belgium. E-mail: eva.vandegaer@ppw.kuleuven.be
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Abstract

In many psychological research domains stimulus-response profiles are explained by conjecturing a sequential process in which some variables mediate between stimuli and responses. Charting sequential processes is often a complex task because (1) many possible mediating variables may exist, and (2) interindividual differences may occur in the relationship between these mediating variables and the response. Recently, Ceulemans and Van Mechelen (Psychometrika 73(1):107–124, 2008) addressed these challenges by developing the CLASSI model. A major drawback of CLASSI is that it requires information about the same set of stimuli for all participants (i.e., crossed data), whereas recently a number of data gathering techniques have been proposed in which the set of stimuli differs across participants, yielding nested data. Therefore we present the CLASSI-N model, which extends the CLASSI model to nested data. A simulated annealing algorithm is proposed. The results of a simulation study are discussed as well as an application to data concerning depression.

Keywords

sequential processesCLASSIindividual differencesbinary dataclusterwise regressionclustering

Information

Type
Article
Information
Psychometrika , Volume 77 , Issue 1 , January 2012 , pp. 85 - 105
Copyright
Copyright © 2011 The Psychometric Society

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