Admission requirements
The course is a sequel to the course Causal inference I. Students are expected to be familiar with formulating causal questions within the potential outcome framework, assessing causal assumptions that are needed to identify a causal effect, visualizing such assumptions using directed acyclic graphs, and applying computational methods to account for confounding (outcome regression and inverse probability weighting) in statistical software.
Description
Understanding what causes what, is the starting point of understanding the world around us. In Causal Inference I, we focused on causal questions regarding the average effects of point interventions. In Causal Inference II, we extend our focus to more complex data settings that are encountered in practice and explore recent advances in causal machine learning. Several advanced methods are offered, and students choose to study one particular method in detail. Topics include causal mediation analysis, causal discovery with graphical models, doubly robust methods, time-varying exposures and instrumental variable analysis. Students work during the course on a deeper understanding of their chosen topic, including applying it to case study data and explaining the topic to the other students.
Course Objectives
After successful completion students are able to:
Independently evaluate scientific literature to learn a new causal inference method
Apply an advanced causal inference method to case study data, including
- Formulating the research question
- Evaluating whether the necessary causal assumptions hold
- Programming the method in statistical software
- Interpreting results and drawing conclusions
Explain newly derived knowledge to peer students
Report on a causal analysis method and the results of a case study analysis both orally and in writing.
Timetable
You will find the timetables for all courses and degree programmes of Leiden University in the tool MyTimetable (login). Any teaching activities that you have sucessfully registered for in MyStudyMap will automatically be displayed in MyTimeTable. Any timetables that you add manually, will be saved and automatically displayed the next time you sign in.
MyTimetable allows you to integrate your timetable with your calendar apps such as Outlook, Google Calendar, Apple Calendar and other calendar apps on your smartphone. Any timetable changes will be automatically synced with your calendar. If you wish, you can also receive an email notification of the change. You can turn notifications on in ‘Settings’ (after login).
For more information, watch the video or go the the 'help-page' in MyTimetable. Please note: Joint Degree students Leiden/Delft have to merge their two different timetables into one. This video explains how to do this.
Mode of Instruction
Student groups teach their chosen topic to the other students. Preparation tasks include: literature reading, data analysis, preparing presentations, report writing. Each group is coached by a topic expert.
Assessment method
Assessment consists a group assignment presented in a written report (30%), a final presentation (individual, 20%), plus an oral exam (individual, 50%).
Partial grades cannot be carried over to the next academic year, the grades should be obtained within the same year.
Reading list
The list of literature will be posted on Brightspace.
Registration
Every student must register for courses with the new enrollment tool MyStudymap. There are two registration periods per year: registration for the fall semester opens in July and registration for the spring semester opens in December. Please see this page for more information.
Please note that it is compulsory to register for every exam and retake. Not being registered for a course means that you are not allowed to participate in the final exam.
Extensive FAQ on MyStudymap can be found here.
Contact
n.van_geloven@lumc.nl