Longitudinal Structural Equation Modelling
Date:
05/12/2016
Organised by:
University of Manchester
Presenter:
Dr Alexandru Cernat
Level:
Advanced (specialised prior knowledge)
Contact:
Michelle Kelly
cmist-courses@manchester.ac.uk
0161 275 4579
Location:
View in Google Maps (M13 9PL)
Venue:
The University of Manchester
Humanities Bridgeford Street Building
Description:
Outline
Structural Equation Modelling (SEM) has been growing in popularity due to its ability to estimate complex relationships between variables, the possibility to control for measurement error and the comprehensive model fit indicators. This approach is also very well suited to deal with longitudinal data (i.e., data collected repeatedly from the same unit). In this context, it offers a number of unique modelling opportunities. Thus, using SEM with longitudinal data it is possible to investigate how the change in one variable is related to the change in another. For example, it can estimate how the change in physical health is linked to changes in happiness. Similarly, the SEM framework makes it possible to create typologies based on patterns of change in time. Thus, it is possible to see what are the typical patterns of change in cognitive ability or party support and who are the people that manifest them.
This one-day course introduces two of the main models used to analyse longitudinal data using SEM: cross-lagged models and latent growth models (LGM). The cross-lagged model is typically used to better understand the causal relationships in longitudinal studies. On the other hand, LGM models are used to estimate individual level change. Both help answer essential questions related to how individuals/organisations/countries change in time.
The course will be a mix of short conceptual presentations and hands on applications using Mplus (which will be available in the computer cluster). No prior knowledge of Mplus is required.
Cost:
£195 (£140 for those from educational, government and charitable institutions).
Website and registration:
Region:
North West
Keywords:
Quantitative Data Handling and Data Analysis, Longitudinal data analysis , Structural Equation Modelling , Mplus , Latent Growth Models , Cross-lagged models
Related publications and presentations from our eprints archive:
Quantitative Data Handling and Data Analysis