Course Causal Inference in Health Sciences

ECTS: 4.1

Course leader: Cecilia Ramlau-Hansen

Language: English

Graduate school: Faculty of Health

Graduate program: PH

Course fee: 4,920.00 DKK

Status: Course is open for application

Semester: Spring 2023

Application deadline: 10/04/2023

Start date: 08/05/2023

Administrator: Thilde Møller Risgaard

The course P281/05 Causal Inference in Health Sciences is being offered by the Graduate School of Health, Aarhus University, 2023.

Criteria for participation: University degree in medicine, dentistry, nursing, or Master’s degree in other fields, and/or postgraduate research fellows (PhD students and research-year medical students) or senior researchers from Denmark and other Scandinavian countries.

Recommended knowledge for participation: Although this is an introductory course to causal inference methods, it requires some knowledge on epidemiology, statistics, and mathematics as well as experience in working with statistical software (please see “Prerequisites”).

Prerequisites: Knowledge about Directed Acyclic Graphs (DAGs) equivalent to the Aarhus University PhD courses: Epidemiology II or Introduction to DAGs. Knowledge in statistics and epidemiology equivalent to the Aarhus University PhD courses: Epidemiology I and Basic Biostatistics part 1 and 2. Knowledge on linear and logistic regression models. Basic knowledge on probability theory. Intermediate skills with Stata or other statistical software.

Aim: Introduce participants to the basic theory and practical usage of modern causal inference methods in the health sciences.

Learning outcomes: 

  • Introduction to the potential outcome framework and counterfactuals
  • Assumptions for causal inference
  • Introduction to and practical experience with g-methods
  • Introduction to and practical experience with causal interaction analysis
  • Introduction to and practical experience with causal mediation analysis

Workload: The full workload of the course is expected to be 102 hours.


Day 1: Causal concepts and frameworks

Day 2: Definition and identification of total effects

Day 3: Estimation of total effects and g-computation

Day 4: Interaction and mediation analyses

Day 5: Practical application of causal inference methods

Instructors:    Onyebuchi Arah, Andreas Ernst, Stefan Hansen and Nis Brix  

Venue: Aarhus University, Aarhus.

Participation in the course is without cost for:

  • PhD students, Health Research Year students and Health Research Honours Programme students from Aarhus University
  • PhD students enrolled at partner universities of the Nordoc collaboration
  • PhD students from other institutions in the open market agreement for PhD courses

Course dates:

  • 08 May 2023 08:15 - 15:00
  • 09 May 2023 08:15 - 15:00
  • 15 May 2023 08:15 - 15:00
  • 16 May 2023 08:15 - 15:00
  • 17 May 2023 08:15 - 15:00