UV9297 – Measurement models
Course description
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:
- Path models and diagrams
- Overview of measurement models
- Model specification, identification, estimation, and evaluation
- Confirmatory and exploratory factor analyses
- Moderation and mediation models
- Multigroup analysis and measurement invariance
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UV9297 Measurement Models is the PhD version of MAE4101 Measurement models, a compulsory course in the master`s program Assessment, Measurement and Evaluation.?The content, schedule and reading list for UV9297 Measurement Models are the same as for MAE4101 Measurement Models.
It is strongly recommended that the students in UV9297 Measurement Models attend all lectures with hands-on components.
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
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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
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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
There is a limited number of seats due to joint teaching with the master’s level version of the course.
PhD candidates at the Faculty of Educational Sciences will be given priority, but it is also possible for others to apply for the course.
The deadline for registration is on the corresponding semester page for the course.?
Candidates admitted to a PhD-program at the Faculty of Educational Sciences (UV) can apply in StudentWeb.
Other applicants can apply by filling out and sending in a electronic registration form, which is found on the corresponding semester page for the course.?
Formal prerequisite knowledge
Master`s degree.
Recommended previous knowledge
It is recommended that candidates have completed MAE4000 Data Science or equivalent. If you are unsure of whether your prior knowledge is sufficient, please?studentinfo@cemo.uio.no.?
Overlapping courses
- 5 credits overlap with MAE4101 – Measurement models.
- 3 credits overlap with UV9210 – Path analysis and structural equation modeling.
- 2 credits overlap with UV9297B.
- 2 credits overlap with UV9292 – Measurement Models (discontinued).
- 1 credits overlap with UV9292U.
- 1 credits overlap with UV9210U.
Teaching
This course combines lectures and seminars with data analysis tasks in statistical software environments.
Joint teaching with the master level version of the course,?MAE4101 Measurement Models.
Lectures are held by Professor Ronny Scherer.
Schedule and literature: Please see the applicable semester page for the course.?
Examination
To obtain 5 credits, 80 % attendance and an exam paper are required. A more specific description of the exam paper will be given at the course.
Language of examination
The examination text is given in English, and you submit your response in 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.