PSY9140P – Paper to Introduction to structural equation modelling

Course content

Structural equation modeling (SEM) is a flexible and widely used statistical framework for analyzing relationships among observed and latent variables. This course combines lectures and hands-on exercises using the R package?lavaan. Participants will learn how to specify, estimate, and evaluate basic SEM models, with a particular focus on latent variable analysis.?

Learning outcome

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

Admission to the course

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 through?this online registration form.

You will find the registration period in the online form.?

Formal prerequisite knowledge

Enrollment in a PhD program. You must have attended the teaching portion (PSY9140), in order to qualify for the exam (PSY9140P).?

Familiarity with the R/RStudio platform, for example through the course PSY9510 - Introduction to Statistics with R (or an equivalent course/experience).

Overlapping courses

  • 2.5 credits overlap with SVTEODR.

Examination

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.

Examination support material

All aids allowed. When using AI, you must account for and be open about the use, read more about guidelines for AI and the exam on Artificial intelligence (AI) at UiO - University of Oslo.

Language of examination

The exam can be submitted in either Norwegian or English.

Grading scale

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

More about examinations at UiO

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

Last updated from FS (Felles studentsystem) Nov. 18, 2025 11:12:01 AM

Facts about this course

Level
PhD
Credits
2.5
Teaching
Spring and autumn
Examination
Spring and autumn
Teaching language
English