Structural Equation Models
Course, Master's level, 2ST114
Spring 2024 Spring 2024, Uppsala, 50%, On-campus, English
- Location
- Uppsala
- Pace of study
- 50%
- Teaching form
- On-campus
- Instructional time
- Daytime
- Study period
- 21 March 2024–2 June 2024
- Language of instruction
- English
- Entry requirements
-
120 credits including 90 credits in statistics, or 120 credits including 60 credits in statistics and 30 credits in mathematics and/or computer science.
- Selection
-
Higher education credits (maximum 285 credits)
- Fees
-
If you are not a citizen of a European Union (EU) or European Economic Area (EEA) country, or Switzerland, you are required to pay application and tuition fees.
- First tuition fee instalment: SEK 12,500
- Total tuition fee: SEK 12,500
- Application deadline
- 16 October 2023
- Application code
- UU-76631
Admitted or on the waiting list?
- Registration period
- 21 December 2023–14 January 2024
- Information on registration from the department
Spring 2025 Spring 2025, Uppsala, 50%, On-campus, English
- Location
- Uppsala
- Pace of study
- 50%
- Teaching form
- On-campus
- Instructional time
- Daytime
- Study period
- 25 March 2025–8 June 2025
- Language of instruction
- English
- Entry requirements
-
120 credits including 90 credits in statistics, or 120 credits including 60 credits in statistics and 30 credits in mathematics and/or computer science.
- Selection
-
Higher education credits (maximum 285 credits)
- Fees
-
If you are not a citizen of a European Union (EU) or European Economic Area (EEA) country, or Switzerland, you are required to pay application and tuition fees.
- First tuition fee instalment: SEK 12,500
- Total tuition fee: SEK 12,500
- Application deadline
- 15 October 2024
- Application code
- UU-76631
Admitted or on the waiting list?
About the course
The course introduces the core methods of structural equation modelling (SEM), a family of statistical approaches that explore complex relationships between and among latent (unobserved) and observed variables. In addition, the course emphasises the empirical applications of SEM and latent variable techniques to broadly address relevant questions in the different disciplines. Course lectures, readings, and assignments will reflect this applied focus. At the end of the course, you are expected to understand the essential issues within SEM and be able to carry out analysis independently.