Students should be conversant about randomized experiments and have the basic tools to plan and to conduct randomized experiments.
Students should be able to
- Understand causal modeling
- Understand relationship of randomization to causal modeling
- Gain the statistical tools to analyze randomized experiments
- Become aware of underlying assumptions, strengths, and weaknesses of experimental approaches
- Become acquainted with key players in the development and implementation of randomized experiments
- Gain the statistical tools to design randomized experiments
- Understand other key issues in design and implementation of random experiments.
The student should be conversant in the world of causal modeling. They should be able to be consumers and producers of experimental research. They should have the background to develop and implement ethically sound and scientifically valid randomized controlled trials. They should also have proficiency in software designed to measure statistical power.
Additionally the course address important implementation issues in randomized controlled trials in social sciences, such as attrition, fidelity and compliance. What can be done to assure low attrition, and high fidelity and compliance? The course discusses the practical aspects of running a randomized controlled trial including a discussion of its growing importance in policy formation and evaluation.
Finally, the students will be introduced to mixed method designs for investigating why or why not an intervention is effective. The class discusses how mixed methods are necessary for understanding mechanisms, fidelity, and compliance. Particularly, qualitative data collection can inform the researcher about each of these issues prompting improved data collection and rigorous scaffolding of complementary research designs.
Required prerequisite knowledge
Recommended previous knowledge
|Term paper||1/1||Pass - Fail|
- Full participation during the whole course is required. (One week on intensive lectures and PC-lab exercises, Monday through Friday, 9 -16).
- Generally active participation in discussions in general.
In addition, there is a term paper requirement ( 8-10 pages, demonstrating knowledge and application skills).
Method of work
Students are expected to prepare for and review lecture materials on their own. The expected work loads of this course are: Lectures: 22 hours Computer Lab sessions: 8 hours
Seminars: 5 Preparations and reviews of materials: 65 hours Paper requirement: 50 hours TOTAL: 150 hours
Sist oppdatert: 01.06.2020