Causal Inference in Epidemiology: Concepts and Methods
4 - 6 June 2018.
3 days (approximately 20 hours teaching).
Registration will start at 9am on the first day, the course will finish by 5pm on the final day.
To provide an understanding of the counterfactual framework and the practical application of methods to improve causal inference in epidemiology.
By the end of the course, students will:
- have a thorough understanding of the potential outcomes framework;
- implement DAGs to inform analysis plans;
- appreciate the different methods which can be used to improve causal inference;
- understand the assumptions underlying the various methods.
Who the course is intended for
This course is aimed at proficient epidemiologists and applied statisticians. Applicants must have knowledge and experience of a variety of regression models (including Cox regression) and their implementation in Stata, to beyond the level achieved in the 'Introduction to Linear and Logistic Regression Models' course.
- causal diagrams (DAGs);
- propensity scores;
- inverse probability weighting;
- instrumental variables, including Mendelian randomization;
- other quasi experimental designs such as negative controls;
- marginal structural models.
Please note: Practical sessions of this course will be held in a computer lab, so you will not need to bring a laptop.
FULLY BOOKED, waiting lists in operation.
More information on course fees, fee waivers and reduced prices.
Bristol Medical School
39 Whatley Road
We provide morning and afternoon refreshment breaks, including tea and coffee, biscuits and fresh fruit.
If you have specific dietary needs we ask that you let us know in advance.
Lunch is not included. There are a range of local cafes and supermarkets nearby for students to purchase lunch.
Information about accommodation in the area.
For further information please email firstname.lastname@example.org.