Introduction to Structural Equation Modelling using Mplus
Date:
24/02/2016 - 26/02/2016
Organised by:
CMIST, University of Manchester
Presenter:
Dr Nick Shryane
Level:
Intermediate (some prior knowledge)
Contact:
Laura Watt
laura.watt@manchester.ac.uk
Map:
View in Google Maps (M13 9PL)
Venue:
Humanities Bridgeford Street Building
University of Manchester
Description:
Structural Equation Models (SEM) amalgamate regression analysis, path 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 SEM methods for categorical data available to applied researchers.
Objectives
This course aims to train quantitative social scientists to use the Mplus programme in the application of structural equation modelling techniques to 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
Prerequisites
Participants should be familiar with statistical modelling using linear regression and binary logistic or probit regression.
Cost:
£420 (public sector) £585 (private sector)
Website and registration:
Region:
North West
Keywords:
Quantitative Data Handling and Data Analysis
Related publications and presentations:
Quantitative Data Handling and Data Analysis