Introduction to Structural Equation Modeling using lavaan (E-Learning Course)

Course code
Course fee
Course Level

In this e-learning course, we will cover the basics of structural equation modeling (SEM) using the R package lavaan. Participants will learn how to interact with the lavaan software and how to run common types of SEMs (e.g., path models, confirmatory factor analyses, latent regression models, multiple group models) using lavaan. No prior knowledge of lavaan is necessary, but some experience with R and SEM (although not strictly required) is strongly encouraged.

Structural equation modeling (SEM) is a powerful tool with which researchers can build intricate models of structural relationships and measurement processes. Traditionally, open-source software options for estimating SEMs have been quite limited, but the lavaan project ( has been steadily changing this narrative. The lavaan package is a completely free and open-source R package that implements a wide range of structural equation models. The package is also being actively developed, so its capabilities continue to grow.

In this e-learning course, we will go over the basics of structural equation modeling using lavaan. We will first cover the lavaan syntax and the workflow of analyses using lavaan. We will then discuss how to implement common structural equation models in lavaan. For example:

  • Path models
  • Latent regression models
  • Confirmatory factor analyses (CFAs)
  • Multiple-group CFAs

We will also consider issues that complicate the analysis and how these issues are addressed in lavaan. For example:

  • Missing data
  • Model selection
  • Categorical indicators

The course will be open for two weeks. During this time the participants can work through the material at their own pace. The instructors will be available via forum discussions and several live, online Q&A sessions.

Participants should install both R and RStudio (the free desktop version) on their computers before the beginning of the course.

  • R can be downloaded here.
  • RStudio can be downloaded here.

No prior experience with lavaan is required, but we will have very little time to cover the theory of SEM or basic R usage. We will focus primarily on how to implement various SEM analyses using lavaan. So, some prior experience with R and SEM is strongly encouraged. We will provide information on external resources that participants can use to brush-up on their R or SEM knowledge before following this course.

Day-to-day programme (PDF)
Course director
Kyle M. Lang


dr. Kyle M. Lang and dr. Rebecca Kuiper

Target audience

Master and PhD students, PhDs, researchers, and other professionals who are interested in learning (more) about the lavaan project, how to use lavaan to estimate common SEMs, and how they can apply lavaan in their own work. The course will be taught at a beginning master level.

Aim of the course

After completing this course, participants will be able to:

  • Compare and contrast the strengths/weaknesses of the lavaan software relative to other SEM packages
  • Translate their own analyses into lavaan models
  • Estimate common SEMs using lavaan

Write R scripts to implement simple SEM-based analyses using lavaan.

Study load

Five full days of content delivered via pre-prepared online lessons. The course will run for two weeks. The participants can work through the content at their own pace during these two weeks. The instructors will be available throughout the course via forum discussions and at several discrete times for live, online Q&A sessions. The specific schedule will be available before June 2022.


Course fee:
Fee covers
Course + course materials
Extra information about the fee

Tuition fee for PhD students from the Faculty of Social and Behavioural Sciences from Utrecht University will be funded by the Graduate School of Social and Behavioural Sciences.

Utrecht Summer School does not offer scholarships for this course.

More information

Irma Reyersen -


Application deadline: 
Registration deadline
20 June 2022