Causal Inference in Epidemiology: Concepts and Methods
1 - 3 July 2019
3 days (approximately 18 hours teaching).
Registration will start at 9am on the first day, the course will finish by 4pm on the final day.
To define causation in biomedical research, describe methods to make causal inferences in epidemiology and health services research, and demonstrate the practical application of these methods.
By the end of the course, students will:
- have a thorough understanding of the potential (counterfactual) outcomes approach to defining causal effects;
- implement DAGs to document assumptions and inform analysis plans;
- understand the key sources of bias in analyses of observational data, and how to investigate them using DAGs; and
- appreciate key methods which can be used to estimate causal effects, and understand the assumptions underlying them.
Who the course is intended for
This course is aimed at epidemiologists, statisticians and other quantitative researchers. 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.
- Potential (counterfactual) outcomes;
- Causal diagrams (DAGs);
- Control of confounding using stratification, standardization, regression models, propensity scores and inverse probability weighting;
- Selection and information biases;
- Instrumental variable estimation, including analysis of Mendelian randomization studies;
- Time-varying confounding and 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.
Make a booking
This course is now fully booked. If you would like to join the waiting list, please complete the booking form.
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.
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