PSYFL5403 – Introduction to structural equation modelling

Course content

Structural equation modeling (SEM) is a flexible multivariate statistical approach that has become increasingly popular in psychological research.

The course will include lectures and practical exercises in specifying, estimating and testing basic SEM models by means of lavaan, a package in the statistical program R. The course introduces methodologies in analyzing latent variables.

Learning outcome

Knowledge:

• Path models

• Model specification and evaluation

• "The latent variable paradigm"

• Measurement models and confirmatory factor analysis

• Structural regression models

• Longitudinal models, including cross-lagged models and growth curve models

• Multi-group analysis

Skills:

Formulate basic SEM models and implement them using structural equation software.

Evaluate a model, and be able to re-specify it if necessary.

Admission to the course

This course is only for students admitted at the student research program at PSI. Contact the administration if you have problem to sign up in Studentweb.

Teaching

Please consult the semester page for time Schedule.

Participant are required to bring their own laptop to the course. Prior to the course start, we provide instructions on installing the necessary software.

Literature: 

Rosseel, Y. The lavaan tutorial. Ghent University, Belgium. Available at http://lavaan.ugent.be/tutorial/

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

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.

Examination

You will earn 5 credit points for participating in the class included required exercises, and submitting an acceptable paper with reference to the course topics. Papers have to be submitted through 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 give out course confirmations in other ways.

Grading scale

Grades are awarded on a pass/fail scale. Read more about the grading system.

More about examinations at UiO

• Use of sources and citations
• Special exam arrangements due to individual needs
• Withdrawal from an exam
• Illness at exams / postponed exams
• Explanation of grades and appeals
• Resitting an exam
• Cheating/attempted cheating

You will find further guides and resources at the web page on examinations at UiO.