PSY9140 – Introduction to structural equation modelling
Course description
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.
Recommended previous knowledge
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.
Teaching
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.
Participants are required to bring their own laptop to the course. We will provide instructions on installing the necessary software you need prior to the course
?
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)
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- UCLA Advanced Research Computing. Introduction to structural equation modeling (SEM) in R with lavaan. Available at https://stats.oarc.ucla.edu/r/seminars/rsem/
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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 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
- Use of sources and citations
- How to use AI as a student
- 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.