MAE4054 – Study Designs for Causal Inference
Course description
Schedule, syllabus and examination date
Course content
This course aims to discuss avenues, challenges, and limitations in the design of studies that intend to address causal research and evaluation questions.
The course covers experimental designs, quasi-experimental designs, and program evaluations. Key principles are illustrated with real-life example studies to improve the understanding of the assumptions and prerequisites of the methods and to critically discuss their scope.
Learning outcome
Upon completion of the course, you:
Knowledge?
- recognize the core relevance and challenges in drawing causal inferences from data;?
- understand advantages, challenges, and limitations of experimental, quasi-experimental, and evaluation study designs;?
- know central design elements and principles of experimental, quasi-experimental, and evaluation study designs.
Skills?
- apply specific methodological procedures and techniques to analyze data in line with the study design.
Competencies?
- critically read and evaluate the support for causal inferences in empirical studies;?
- take a systematic and reasoned approach to designing studies, considering the advantages, challenges, and limitations of the variety of approaches in light of the central research questions and/or evaluation objectives.
Admission to the course
Students who are admitted to study programmes at UiO must each semester register which courses and exams they wish to sign up for?in Studentweb.
If you are not already enrolled as a student at UiO, please see our information about?admission requirements and procedures.
All students in the Assessment, Measurement and Evaluation Master program have equal access to the course. Qualified exchange students or students from other master's programmes at UiO may be considered based on capacity.
Contact us if you want to apply for the course. If you are unsure of whether or not you have sufficient prior knowledge, please send us documentation of previous relevant courses you have taken.
Formal prerequisite knowledge
Basic knowledge of the statistical programming environment R is required.
Recommended previous knowledge
MAE4000 Data Science or equivalent.
Overlapping courses
- 3 credits overlap with UV9204 – Study Design for Causal Inference.
Teaching
This course combines lectures, seminars (including critical discussions of pro and contras of specific studies), and more practical lab activities.
Obligatory activity:?
- Participation in the seminars
- Presentation of a critique of an assigned study and participation in the discussion in the seminars
- Compulsory assignment
Once qualified for participating in the exam, you retain this qualification for the next two times the course is offered.
Examination
In order to qualify for the exam, you must have given a presentation of a critique of an assigned study and participated?in the discussion in the seminars.
The exam is a three-day take home exam and consists of an individually written paper. In 1500-2000 words you characterize and critique an empirical study in light of the study objectives, study design, and causal inferences that were drawn with specific attention to identification issues and possible specification and robustness checks.
Previously given exams and grading guides.?
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.
Your grade is solely based on the final individual written assignment.
Resit an examination
More about examinations at UiO
- Use of sources and citations
- 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.