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 structural equation models (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 structural equation models have been quite limited, but the lavaan project (https://lavaan.ugent.be/) has been steadily changing this narrative. The lavaan package is a completely free and open-source R package that implements a wide range of SEMs. 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 SEM using lavaan. We will first cover the lavaan syntax and the workflow of analyses using lavaan. We will then discuss how to implement common SEMs 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. In addition to the scaffolded, self-paced instruction provided by the electronic course materials, participants will also have the opportunity to interact directly with lavaan experts via forum discussions and 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.
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.
Dr. Kyle M. Lang and Dr. Rebecca Kuiper
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 structural equation models, and how they can apply lavaan in their own work. The course will be taught at a beginning master level.
For an overview of all our summer school courses offered by the Department of Methodology and Statistics please click here.
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 structural equation models using lavaan
- Write R scripts to implement simple SEM-based analyses using lavaan
The course content comprises five full days of material 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 course materials will remain available to registered participants for two years after the conclusion of the course. The instructors will be available throughout the course via forum discussions and live, online Q&A sessions. The specific schedule will be available before June 2023.
Please note that there are no graded activities included in this course. Therefore, we are not able to provide students with a transcript of grades. You will obtain a certificate upon completion of this course.
The 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.
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