QMEG Masterclass: Longitudinal Growth Modelling with SEM
Date:
21/10/2026
Organised by:
University of Southampton – Quantitative Methods in Education Group (QMEG)
Presenter:
Dr James Hall
Level:
Intermediate (some prior knowledge)
Contact:
Dr James Hall
J.E.Hall@Soton.ac.uk
Venue: Online
Longitudinal research frequently seeks to understand not only whether people or other units change over time, but also whether they differ in their starting points, rates of change, and the factors associated with these differences. Growth modelling provides a family of statistical approaches for addressing such questions.
This masterclass introduces longitudinal growth modelling with a particular focus on Structural Equation Modelling (SEM). The first part of the session will introduce the concepts underlying growth models, contrast multilevel and SEM approaches, and consider the distinctive possibilities offered by latent growth models. The second part will provide a worked demonstration in R, using lavaan to specify, estimate, interpret and extend a basic latent growth model.
The session is intended for researchers who already have some familiarity with quantitative analysis. Previous exposure to regression and/or SEM will be helpful, but specialist knowledge of longitudinal modelling is not assumed.
The session is free to attend and will take place online via Microsoft Teams.
Cost:
free
Website and registration:
Region:
International
Keywords:
Longitudinal Research , Quantitative Data Handling and Data Analysis, Longitudinal Data Analysis, Growth curve models, Growth mixture models, Latent class growth analysis, Latent Variable Models, Latent class analysis, Confirmatory factor analysis, Structural equation models, Time Series Analysis, ICT and Software, Quantitative Software, R
Related publications and presentations from our eprints archive:
Longitudinal Research
Quantitative Data Handling and Data Analysis
Longitudinal Data Analysis
Growth curve models
Growth mixture models
Latent class growth analysis
Latent Variable Models
Latent class analysis
Confirmatory factor analysis
Structural equation models
Time Series Analysis
ICT and Software
Quantitative Software
R
