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Multilevel Structural Equation Modeling with lavaan
Dozent
Msc. Jasper Bogaert (in collaboration with, Prof. Yves Rosseel, developer of the R package lavaan), Ghent University, Department of Data Analysis
Course Objectives
First, the course provides an introduction to the theory and application of structural equation modeling and illustrates how to use the open-source R package lavaan (see https://lavaan.org) to conduct an SEM analysis. Next, we briefly discuss several special topics that are often needed by applied users, such as handling missing data, non-normal data, categorical data, and longitudinal data. Finally, we delve into the topic of multilevel SEM. If time permits, we will explore some of the latest developments in lavaan that can be of great use to applied users.
Working method in the course
The two days primarily consist of lectures (to maximize the amount of information that can be taught) with a brief practical and troubleshooting session at the end of each day. Additionally, do-it-yourself practicals, including written feedback and solutions, will be provided to illustrate all the topics covered in the course.
Course language
English
Requirements
Participants should have a solid understanding of regression analysis and basic statistics (hypothesis testing, p-values, etc.). Some knowledge of (exploratory) factor analysis (or PCA) is recommended, but not required. Because lavaan is an R package, some experience with R (reading in a dataset, fitting a regression model) is recommended, but not required.
- Format: Kurs
- Leitung:
- Msc. Jasper Bogaert, Teaching assistant & PhD researcher, Ghent University, Department of Data Analysis
- Zielgruppen:
- Mitarbeitende an Hochschulen
- Behördenmitglieder
- Dozierende an Hochschulen
- Mitarbeitende an Hochschulen
- Themen:
- Überfachliche Kompetenzen
- Ort: Campus Brugg-Windisch
- Preis: CHF 300.00
- Anmeldeschluss: Fr, 18.4.2025
- Beginn: Mo, 2.6.2025
- Bemerkungen: Diese Angebot ist Teil des Angebots «Methodenwoche | Kursangebot zu forschungsmethodischen und überfachlichen Themen».
KI in der Wissenschaft – von der Themenfindung bis zur wissenschaftlichen Publikation | (Kurs B: Do–Fr) (Kurs) |
KI in der Wissenschaft – von der Themenfindung bis zur wissenschaftlichen Publikation | (Kurs A: Mo–Di) (Kurs) |