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Longitudinal Model Building Using Latent Transition Analysis: An Example Using School Bullying Data

Ji Hoon Ryoo · Cixin Wang · Susan M. Swearer · Dingjing Shi

153 citations0/0 files storedFrontiers in Psychology

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Psychometric Methodologies and Testing Bullying, Victimization, and Aggression Statistical Methods and Bayesian Inference

Abstract

Applications of latent transition analysis (LTA) have emerged since the early 1990s, with numerous scientific findings being published in many areas, including social and behavioral sciences, education, and public health. Although LTA is effective as a statistical analytic tool for a person-centered model using longitudinal data, model building in LTA has often been subjective and confusing for applied researchers. To fill this gap in the literature, we review the components of LTA, recommend a framework of fitting LTA, and summarize what acceptable model evaluation tools should be used in practice. The proposed framework of fitting LTA consists of six steps depicted in Figure 1 from step 0 (exploring data) to step 5 (fitting distal variables). We also illustrate the framework of fitting LTA with data on concerns about school bullying from a sample of 1,180 students ranging from 5th to 9th grade (mean age = 12.2 years, SD = 1.29 years at Time 1) over three semesters. We identified four groups of students with distinct patterns of bullying concerns, and found that their concerns about bullying decreased and narrowed to specific concerns about rumors, gossip, and social exclusion over time. The data and command (syntax) files needed for reproducing the results using SAS PROC LCA and PROC LTA (Version 1.3.2) (2015) and Mplus 7.4 (Muthén and Muthén, 1998-2015) are provided as online supplementary materials.

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References

2014Auxiliary Variables in Mixture Modeling: Three-Step Approaches Using M plus 2000Integrating Person‐Centered and Variable‐Centered Analyses: Growth Mixture Modeling With Latent Trajectory Classes 2009Latent Class and Latent Transition Analysis: With Applications in the Social, Behavioral, and Health Sciences 1969Latent Structure Analysis.2010Latent Class Modeling with Covariates: Two Improved Three-Step Approaches 2012The Rediscovery of Bifactor Measurement Models 2013Latent Class Analysis and Finite Mixture Modeling 1997A person-oriented approach in research on developmental psychopathology

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