Graduate School of health and Medical Sciences

Advanced topics in causal inference
Provider: Faculty of Health and Medical Sciences

Activity no.: 3356-25-00-00	There are 19 available seats
	Enrollment deadline: 15/09/2025

Date and time	14.10.2025, at: 09:00 - 23.10.2025, at: 16:00
Regular seats	20
Course fee	6,240.00 kr.
Lecturers	Erin Gabriel
ECTS credits	2.80

Contact person	Susanne Kragskov Laupstad E-mail address: skl@sund.ku.dk

Enrolment Handling/Course Organiser	PhD administration SUND E-mail address: phdkursus@sund.ku.dk

Aim and content This is a generic course. This means that the course is reserved for PhD students at the Graduate School of Health and Medical Sciences at UCPH. Anyone can apply for the course, but if you are not a PhD student at the Graduate School, you will be placed on the waiting list until enrollment deadline. After the enrollment deadline, available seats will be allocated to the waiting list. The course is free of charge for PhD students at Danish universities (except Copenhagen Business School), and for PhD students at NorDoc member faculties. All other participants must pay the course fee. Aim This four-day intensive course aimed at Ph.D. students in Biostatistics, Epidemiology, Health Data Science, or Statistics who already work in causal inference and in particular statistical methods for causal inference and want information about an advanced topic. When participating in this course, you will get a working knowledge of the conceptual roots of a set of special and advanced topics in causal inference. Learning objectives A student who has met the objectives of the course will be able to: 1. Be aware basic longitudinal causal inference, tmle and time-to-event causal inference topics 2. Be aware of and be able to discuss and use concepts from the special topics that will rotate each time the course is given. 3. Special topics for fall 2025 will include but are not limited to, dynamic treatment regimes, Bayesian causal inference Content Day 1: Basics of TMLE, Basics in event-time causal inference, Basics in longitudinal causal inference Day 2: special topics TBD Day 3: special topics TBD: causal discovery Day 4: special topics TBD Other topics may be included. Statistical software We will be working with the open source statistical software R using the interface RStudio. To participate in the course you must bring your own laptop with R and RStudio installed. Prerequisites Familiarity with R programming is necessary for taking part in the exercise classes and for completing the homework problems. If you are not familiar with R programming, we recommend that you complete the free access e-learning course at https://biostat.ku.dk/r/ before starting on this course. Introduction to causal inference or other similar courses. Mathematical theory, some basic understanding of calculus. Participants Ph.D.-students. In case of vacant seats also other medical researchers. Max. 20 participants. Relevance to graduate programmes The course is relevant to PhD students from the following graduate programmes at the Graduate School of Health and Medical Sciences, UCPH: Biostatistics and Bioinformatics All graduate programmes Language English Form Lectures and interactive learning for all 6 hours per day Course director Professor Erin Gabriel, Section of Biostatistics Teachers Professor Erin Gabriel Professor Erica Moodie, McGill University Additional teachers TBD Dates Tuesdays and Thursdays: 14, 16, 21 and 23 October 2025, All days 9-16 Course location The Faculty of Social Sciences (also known as CSS) - located in the old municipal hospital as part of City Campus. Registration Please register before 15 September 2025 Seats to PhD students from other Danish universities will be allocated on a first-come, first-served basis and according to the applicable rules. Applications from other participants will be considered after the last day of enrolment. Note: All applicants are asked to submit invoice details in case of no-show, late cancellation or obligation to pay the course fee (typically non-PhD students). If you are a PhD student, your participation in the course must be in agreement with your principal supervisor.

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