This master-class provides a foundation for those wishing to utilise structural equation modelling (SEM) to explore and test complex relationships.
The course is designed as an applied introduction to SEM using Stata, aimed at providing participants with a sound understanding of when to use SEM and how to assess and report their models
Dr Joanna Dipnall is an applied statistician with interests in the advanced statistical methods, including machine learning and deep learning techniques. She completed her Honours in Econometrics with Monash University and her PhD with IMPACT SRC, School of Medicine, Deakin University. Joanna works extensively with registry and linked medical data and collaborates extensively with the Faculty of IT at Monash to supervise Masters and PhD students to integrate artificial intelligence within health research. Joanna teaches within the Monash Biostatistics Unit and is the Unit Co-coordinator for the Monash Masters of Health Data Analytics course. Joanna has taught advanced statistical methods for many years at universities and for ACSPRI.
This Master-class is designed for participants with an introductory-level understanding of the statistical methods of regression analysis and exploratory factor analysis. Participants will experience hands-on SEM examples and have the ability to build their own Stata SEM models.
This workshop is targeted at those researchers who wish to expand their understanding of this highly powerful technique. SEM has been utilised in many areas of research from psychology to medicine.
Day 1: Fundamentals of SEM
- Brief overview of multiple regression and exploratory factor analysis using Stata
- Discussion of the advantages of SEM over conventional analytical techniques
- Understanding of the fundamentals underlying SEM; model conceptualisation, path diagrams, model specification and when should they be used
- Introduction to Stata SEM notation and diagrams
- Introduction to path analysis using Stata
Day 2: Working with SEM Models
- Introduction to confirmatory factor analysis using Stata
- Extending path analysis to use with binary outcomes
- Brief introduction to more complex SEM models
- Stata postestimation tests, predictions and goodness of fit statistics
- Guidelines for writing up SEM models
This workshop will take place in a classroom. You will need to bring your own laptop with Stata. If you don't have a copy of Stata, please let us know in advance and we will organise a trial version for the course.
This course assumes that participants have familiarity with the Stata command language and a sufficient understanding of statistics to be able to comprehend the material covered in the course outline, such as a basic grounding in regression and exploratory factor analysis.
Course notes will be supplied.
No specific references are suggested but participants might find the following text useful:
- Bollen KA. 1989. Structural equations with latent variables. New York: John Wiley.
- Schumacker RE & Lomax RG. 2010. A Beginner’s Guide to Structural Equation Modeling. Mahwah, New Jersey: Lawrence Erlbaum.
- A Acock, 2013,Discovering Structural Equation Modeling Using Stata, Revised Edition, A Stata Press Publication.
Stata is distributed in Australia and New Zealand by Survey Design and Analysis Services.