Course content

In this course, you will get acquainted with the fundamental theories and applications of measurement models and their roles in structural equation models. The focus will be on using these methods for applied research.

You also gain practical competency in statistical software for analyzing data.

The course covers the following key topics:

  1. Overview of latent variable models and measurement error
  2. Path diagram, causality, and matrix notation
  3. Model fit and comparison
  4. Confirmatory and exploratory factor analysis
  5. Moderation and mediation
  6. Multigroup analysis and measurement invariance

Learning outcome

Knowledge

  • Recognize the general principles of measurement models
  • Understand the key assumptions that underlie these models and methods
  • Understand what violations of their assumptions can mean for model selection and associated inferences

Skills

  • Select, apply, and interpret the parameters of a measurement model for the research question at hand, for instance, in the context of structural equation modeling
  • Test key assumptions and offer possible solutions to violations
  • Write up the results of an analysis in an appropriate way
  • Analyze data with the help of existing statistical software packages

Competencies

  • Demonstrate a facility with measurement models to answer well-defined research questions, for instance, in the context of structural equation modeling
  • Interpret published scientific research that uses these models and methods
  • Evaluate the tenability of associated inferences and knowledge claims

Admission to the course

Obligatory for students in the Assessment, Measurement and Evaluation master program. Students from other master’s programs at UiO may be considered if there is capacity. Contact us at studentinfo@cemo.uio.no to request registration.

Ph.d. candidates can take the Ph.d. version of the course: UV9297

Having completed MAE4000 Data Science or equivalent. If you are unsure of whether your prior knowledge is sufficient, please contact studentinfo@cemo.uio.no

Overlapping courses

Teaching

This course combines lectures and seminars with data analysis tasks in statistical software environments.

Obligatory course components:

  • 80% attendance requirement
  • Completion of two individual written assignments

Examination

The exam consists of a 4-hour individual written examination covering all course material and topics.

You need to have successfully completed the obligatory course components before being allowed to sit the exam. If you do not fulfill these requirements, you must submit a written request to apply for an additional assignment prior to sitting the exam. The application must document stated reasons for absence beyond your control.

Previous exams

Examination support material

No examination support material is allowed.

Language of examination

The examination text is given in English, and you submit your response in English.

Grading scale

Grades are awarded on a scale from A to F, where A is the best grade and F is a fail. 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 (Common Student System) Nov. 10, 2024 3:42:06 AM

Facts about this course

Level
Master
Credits
10
Teaching
Spring
Examination
Spring
Teaching language
English