Data Science Events Calendar
Welcome to your calendar for data science events! Dive into a curated list of courses, conferences, seminars, workshops, and key deadlines. Tailor your search to match your interests by adjusting the event category filters. For those specifically looking for PhD courses, simply modify the filter settings to include these events as well. Stay connected and up-to-date with the latest in data science, all in one place.
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Components of causal inference with focus on assumptions and confounding control
November 18 - November 20
Welcome to: Components of causal inference with focus on assumptions and confounding control
PhD Programme: Epidemiology & Biostatistics
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.
Course format: Class lectures and hands-on workshop
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 ECTS
Date: 18-20 November 2024
Time: 9:00-15:30
Place: SUND building, Aalborg University, Selma Lagerløfs Vej 249
Zip code: 9260
City: Gistrup
Number of seats: 25
Deadline: 28 October 2024
Requirements: 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.
Important information concerning PhD courses: We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registration.
Disclaimer:
DDSA has explicit permission from Arcanic and the owners of the https://phdcourses.dk/ website to display the courses on ddsa.dk.
