PSY9140 – Introduction to structural equation modelling

Knowledge:

• Path analysis
• Specification and evaluation of SEM models
• The latent variable paradigm
• Measurement models and confirmatory factor analysis
• Structural regression models
• Longitudinal models (including cross-lagged and growth curve models)
• Multi-group analysis

Skills:

• Specify and estimate basic SEM models using structural equation software
• Evaluate model fit and re-specify models when necessary

This is an elective course in the PhD program in Psychology. PhD candidates at the Department of Psychology can sign up for this course in Studentweb. Please contact the administration if you have problems registering for the course in Studentweb.

PhD candidates at the Department of Psychology will be given priority, but it is also possible for others to apply for the course. Applicants must have at least a Master`s degree. Other candidates can apply to the course throughthis online registration form.

You will find the registration period in the online form.

Please consult the semester page for the detailed course schedule. Participants must bring their own laptop. Instructions for installing required software will be provided in advance.

Please consult the corresponding semester page for the course schedule.

Literature:

• Rosseel, Y. The lavaan tutorial. Ghent University, Belgium. Available at http://lavaan.ugent.be/tutorial/ (recommended)
• Bauer, D.J. & Curran, P.J. Structural equation modeling: R demonstration notes. Curran‐Bauer Analytics, Durham: NC. Available at https://curranbauer.org/wp-content/uploads/2019/04/SEM-R-notes-2019-3.pdf (recommended)

• UCLA Advanced Research Computing. Introduction to structural equation modeling (SEM) in R with lavaan. Available at https://stats.oarc.ucla.edu/r/seminars/rsem/

In addition, one of the following books providing a general introduction to structural equation modeling can be helpful:

• Kline, R. B. (2016). Principles and practice of structural equation modeling (4th ed.). Guilford.
• Keith, T. Z. (2019). Multiple regression and beyond. An Introduction to multiple regression and structural equation modeling. (3rd ed.). Taylor & Francis.

You earn 2.5 credits by attending the course and completing required exercises (PSY9140). An additional 2.5 credits are awarded for submitting an accepted course paper (PSY9140P), to be delivered in Inspera.

If you need confirmation on passing this course, you must do this through studentweb and use the description on this web page for information. We do not otherwise give out course confirmations.