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Detecting Intervention Effects Using a Multilevel Latent Transition Analysis with a Mixture IRT Model

Published online by Cambridge University Press:  01 January 2025

Sun-Joo Cho ,
Allan S. Cohen  and
Brian Bottge
Sun-Joo Cho*
Affiliation:
Vanderbilt University
Allan S. Cohen
Affiliation:
The University of Georgia
Brian Bottge
Affiliation:
University of Kentucky
*
Requests for reprints should be sent to Sun-Joo Cho, Department of Psychology and Human Development, Peabody #H213A, Peabody College of Vanderbilt University, 230 Appleton Place, Nashville, TN 37203, USA. E-mail: sj.cho@vanderbilt.edu
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Abstract

A multilevel latent transition analysis (LTA) with a mixture IRT measurement model (MixIRTM) is described for investigating the effectiveness of an intervention. The addition of a MixIRTM to the multilevel LTA permits consideration of both potential heterogeneity in students’ response to instructional intervention as well as a methodology for assessing stage sequential change over time at both student and teacher levels. Results from an LTA–MixIRTM and multilevel LTA–MixIRTM were compared in the context of an educational intervention study. Both models were able to describe homogeneities in problem solving and transition patterns. However, ignoring a multilevel structure in LTA–MixIRTM led to different results in group membership assignment in empirical results. Results for the multilevel LTA–MixIRTM indicated that there were distinct individual differences in the different transition patterns. The students receiving the intervention treatment outscored their business as usual (i.e., control group) counterparts on the curriculum-based Fractions Computation test. In addition, 27.4 % of the students in the sample moved from the low ability student-level latent class to the high ability student-level latent class. Students were characterized differently depending on the teacher-level latent class.

Keywords

latent class modelmixture item response theory modelmultilevel latent transition analysis

Information

Type
Original Paper
Information
Psychometrika , Volume 78 , Issue 3 , July 2013 , pp. 576 - 600
Copyright
Copyright © 2013 The Psychometric Society

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