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Cathie Marsh Institute for Social Research

Structural Equation Modelling Using Mplus

Dates: 22-24 February 2016 
Duration: 3 days
Instructor: Dr Nick Shryane
Level: Intermediate
Fee: £585 (£420 for those from educational and charitable institutions). The Cathie Marsh Institute (CMIST) offers five free places to research staff and students within the Faculty of Humanities at The University of Manchester and the North West Doctoral Training Centre.
Postgraduate students requesting a free place will be required to provide a letter of support from their supervisor.


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

Day 1

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

Day 2

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

Day 3

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.

Recommended reading

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

About the instructor