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Configural frequency trees

Published online by Cambridge University Press:  10 March 2021

Wolfgang Wiedermann Open the ORCID record for Wolfgang Wiedermann [Opens in a new window] ,
Keith C. Herman ,
Wendy Reinke  and
Alexander von Eye
Wolfgang Wiedermann*
Affiliation:
Department of Educational, School & Counseling Psychology and Missouri Prevention Science Institute, University of Missouri, Columbia, USA
Keith C. Herman
Affiliation:
Department of Educational, School & Counseling Psychology and Missouri Prevention Science Institute, University of Missouri, Columbia, USA
Wendy Reinke
Affiliation:
Department of Educational, School & Counseling Psychology and Missouri Prevention Science Institute, University of Missouri, Columbia, USA
Alexander von Eye
Affiliation:
Department of Psychology, Michigan State University, East Lansing, MI, USA
*
Author for Correspondence: Wolfgang Wiedermann, Statistics, Measurement, and Evaluation in Education, Department of Educational, School, and Counseling Psychology, College of Education, and Missouri Prevention Science Institute, University of Missouri, 13B Hill Hall, Columbia, MO, 65211, USA; E-mail: [email protected].
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Abstract

Although variable-oriented analyses are dominant in developmental psychopathology, researchers have championed a person-oriented approach that focuses on the individual as a totality. This view has methodological implications and various person-oriented methods have been developed to test person-oriented hypotheses. Configural frequency analysis (CFA) has been identified as a prime method for a person-oriented analysis of categorical data. CFA searches for configurations in cross-classifications and asks whether the number of observed cases is larger (CFA type) or smaller (CFA antitype) than expected under a probability model. The present study introduces a combination of CFA and model-based recursive partitioning (MOB) to test for type/antitype heterogeneity in the population. MOB CFA is well suited to detect complex moderation processes and can distinguish between subpopulation and population types/antitypes. Model specifications are discussed for first-order CFA and prediction CFA. Results from two simulation studies suggest that MOB CFA is able to detect moderation processes with high accuracy. Two empirical examples are given from school mental health research for illustrative purposes. The first example evaluates heterogeneity in student behavior types/antitypes, the second example focuses on the effect of a teacher classroom management intervention on student behavior. An implementation of the approach is provided in R.

Keywords

configural frequency analysismodel-based recursive partitioningmoderationperson-oriented researchregression trees
Type
Regular Article
Information
Development and Psychopathology , Volume 34 , Issue 4 , October 2022 , pp. 1585 - 1603
Copyright
© The Author(s), 2021. Published by Cambridge University Press

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