Structural Equation Modelling Using Mplus
Dates: 4–6 March 2020
Duration: 3 days
Instructor: Dr Nick Shryane
Fee: £585 (£420 for those from educational, government and charitable institutions).
CMI offers up to five subsidised places at a reduced rate of £60 per course day to research staff and students within Humanities at The University of Manchester. These places are awarded in order of application.
Humanities PGR students at The University of Manchester can apply for a methods@manchester bursary to help cover their costs. All applications will be considered on a case-by-case basis and applicants will be required to provide a supporting statement from their supervisor.
Please note: this is not guaranteed and is considered on a case by case basis. Please contact us for more information.
Structural Equation Models (SEM) amalgamate regression analysis, path/mediation analysis and factor analysis, allowing for more richly detailed statistical models to be specified and compared to data than by using these techniques individually.
Historically, SEM models were confined to the analysis of continuous observed data, limiting their usefulness in applied social research, where many phenomena are inherently discrete or are measured only with coarse-grained instruments.
Advances in recent years have made available SEM methods for categorical data to applied researchers. This course covers both linear SEM and generalized SEM for non-continuous outcomes, as well as models with non-continuous latent variables, i.e. latent classes.
This course aims to train quantitative social scientists to use the Mplus programme in the application of structural equation modelling techniques to continuous and non-continuous observed data.
The course also aims to integrate approaches that assume latent dimensions of variation (eg factor analysis) with approaches that assume unobserved groups or categories (eg latent class analysis).
Provisional Course Syllabus
- Session 1: Introducing Mplus
- Session 2: Regression models for binary categorical data
- Session 3: Path Analysis I: continuous dependent variables
- Session 4: Path Analysis II: categorical dependent variables
- Session 5: Continuous latent variables I: Modelling continuous observed data: Factor Analysis
- Session 6: Continuous latent variables II: Modelling binary observed data: Item-Response
- Session 7: Structural Equation Modelling
- Session 8: Multi-group Structural Equation Modelling
- Session 9: Categorical latent variables I: Mixture Models
- Session 10: Categorical latent variables II: Latent Class and Latent Profile Analysis
- Session 11: Repeated measures modelling I: autoregressive and cross-lagged panel models
- Session 12: Repeated measures modelling II: linear and non-linear growth models
Participants should be experienced users of linear and binary logistic regression or probit regression. No previous experience of SEM models or the Mplus programme is required.
The following book would give you a head-start in familiarising yourself with linear SEMs and the Mplus programme, but it is not assumed that you will have read it before the course:
- Byrne, B. (2012) Structural Equation Modelling with Mplus