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Components of causal inference with focus on assumptions and confounding control (2025)
Welcome to Components of causal inference with focus on assumptions and confounding control (2025)
Program: Epidemiology & Biostatistics ***mandatory course ****
Description:
Purpose: You already know that establishing a causal relationship is distinct from observing an association. While individuals who receive the flu vaccine tend to have a lower mortality rate compared to those who do not, we must consider whether this lower mortality is directly attributable to the vaccine or if it arises from other distinctions between the vaccinated and unvaccinated groups. The concept of confounding introduces a pervasive bias when we compare groups that are not fundamentally similar. It represents a substantial challenge to drawing accurate causal conclusions from observational data. Consequently, the course’s primary focus revolves around the essential task of mitigating confounding in epidemiological research using various techniques.
Course objectives: This course focus on models for confounding control (or adjustment), their application to epidemiologic data, and the assumptions required to endow the parameter estimates with a causal interpretation. The course introduces participants to a set of methods for confounding control with focus on survival analysis: methods that require measuring confounders and how this could be applied in perspective to the research question of interest. Specifically, the course introduces aspects of directed acyclic graphs, outcome regression, propensity score methods, and inverse-probability weighting of marginal structural models as means for confounding control, and how this can be implemented and analysed in standard statistical software.
(Mandatory course for AAU PhD programme Epidemiology & Biostatistics)
Prerequisites:
Basic training in epidemiology required (eg., the AAU course “Epidemiology – Basic principles” or similar). Basic statistics and basic programming abilities with Stata or R. All participants must bring a laptop with either Stata or R installed.
Key literature:
Organizer:
Peter Brønnum Nielsen, PhD, Assoc. Prof., Department of Clinical Medicine, AAU
Lecturers: Søren Paaske Johnsen, Peter Brønnum Nielsen, Chalotte W. Nicolajsen, +additional
ECTS: 2.5
Time: 17, 18, 19 November 2025
Place: SUND building, Aalborg University, Selma Lagerløfs Vej 249
Zip code: 9260
City: Aalborg/Gistrup
Maximal number of participants: 25
Deadline: 27 October 2025
Disclaimer:
DDSA has explicit permission from Arcanic and the owners of the https://phdcourses.dk/ website to display the courses on ddsa.dk.
