Applied Quantitative Methods for Management Research - 2025

Module B: Introduction to Structural Equation Modelling


Course coordinator: John Thøgersen

Lecturer: John Thøgersen

Workload: 3 ECTS

Administrative assistance: Lisbeth Widahl

Time and place: 

Week 44, Wednesday-Friday, 29-31 October 2025

Aarhus BSS, Aarhus University, Fuglesangs Allé 4, 8210 Aarhus V. Room: 29 October: 2636-U111; 30 October: 2636-U214; 31 October: 2628-M211.

Application deadline: 15 September 2025


Course description

This introductory Structural Equation Modelling (SEM) course builds on and extends Applied Quantitative Methods for Management Research Module A: Understanding causality. However, completing Module A is not a requirement for taking this course, which is designed to be useful for anyone who needs a quick, hands-on introduction to SEM.

This SEM course shares the focus on understanding causality and how to deal with threats to causal inferences with Module A and Module C. Hence, we will especially focus on causality assumptions and the use of cross-lagged panel designs for quasi-experimental and longitudinal studies in SEM. Another focus point is how SEM deals with the pervasive endogeneity issues stemming from measurement error. In addition, the course will demonstrate the ease with which not only multiple regression analysis, but also path, mediation, and moderation analyses, are done with SEM.

After completing this course, participants should be able to:

  • Understand the basic principles of SEM and its application to empirical studies in management and marketing
  • Understand the importance of correcting for measurement error – an important source of endogeneity in empirical studies – and how this is done in SEM
  • Understand the principles and master the praxis of multiple regression, path, mediation, moderation, and multi-group analyses in SEM
  • Understand the principles and master the praxis of cross-lagged panel designs for quasi-experimental and longitudinal studies in SEM

In line with Module A, instead of focusing on building equations, we use software with a handy graphical interface to build directed acyclic graphs to visualize the assumptions underlying our research questions. And we learn SEM by reading about its underlying intuition, seeing it work in published empirical articles in marketing and management, and in-class exercises, giving hands-on experience with an easy-to-use, state-of-the-art SEM software, JMP-Pro.

Like the other modules of this course, an important goal is to de-mystify the concepts and skills involved in SEM, to spark your interest in designing your own study, and to facilitate that you become an engaged and collaborative contributor to the academic community.


Day 1: The basics of structural equation modelling

  • Introduction to the module, the teacher and the participants
  • What is SEM?
  • Test of fit of model to data in SEM
  • Measurement error and classical test theory
  • Manifest vs. latent variables
  • Introduction to JMP Pro’s SEM module
  • Multiple regression and path analysis
  • Exercises

Day 2: The core of structural equation modelling

  • Confirmatory factor analysis
  • A structural model with latent variables
  • Assessing model fit
  • The use of modification indices for improving model fit
  • Mediation and moderation analysis in SEM
  • Subgroup analysis
  • Exercises and group work

Day 3: Structural equation modelling with panel data

  • Cross-lagged panel analysis
  • Power analysis for SEM
  • Miscellaneous topics and issues
  • Exercises and group work
  • Wrap-up and assignments
  • Pre-class assignment: Journal articles and book chapters (TBA)
  • Post-class assignment: 3-4 pages review of an empirical journal article using SEM

Application
Deadline for application: 15 September 2025. Please download and fill in the application form. The application form should be sent by email to: Department of Management, Aarhus BSS, Aarhus University, att. Lisbeth Widahl. Please note that your application is binding.

Fee
External participants (from outside Aarhus University) will have to pay a fee to cover lunch and refreshments. For more information, please contact Lisbeth Widahl. Participants will have to make their own arrangements regarding travel and accommodation.