Causal Inference in Practice Short Course
This course covers the latest developments in causal inference methods and provides practical explanations for applying them to real research questions.
Course details
Course timetable: Causal Inference in Practice
Course dates: 18th-20th February 2026
Location: UCL GOSICH - Wolfson Centre, first floor, room G, Google Maps.
About the course
Causal inference is one of the most important and challenging aims in statistics and data science. Many fields, from clinical medicine to social sciences, strive to use empirical data to understand how different factors influence the world.
Recent developments in the field of causal inference have significantly aided researchers in producing more reliable evidence of cause and effect. Causal inference methods offer a framework and structure for developing and assessing the assumptions on which causal interpretation relies.
Structure
This 3-day in-person course covers the latest developments in causal inference methods and provides practical explanations for applying them to real research questions. It will cover potential outcomes, target trial emulation, propensity score-based methods, instrumental variable analysis, and mediation analysis.
The course will consist of a combination of lectures, small-group work, and computer practicals. Computer practicals will be conducted on your own laptop and software, and we will provide simulated data for participants to work with and take home.
Intended learning objectives:
Understand:
- the potential outcomes framework and how to apply it;
- how to use directed acyclic graphs;
- estimate causal effects using observational data and the assumptions required, and
- define research questions using a target trial;
- interpret causal analyses.
Who should apply?
This is an advanced course is aimed at people conducting applied epidemiological, medical and other quantitative research, from PhD students to experienced researchers interested in learning more about causal inference methods. Participants should be familiar with applied statistical analysis and have an MSc in statistics, data science, or other quantitative subjects.
Timetable
Refreshments & Lunch
Coffee, tea and light refreshments will be provided daily at 9, mid-morning and mid-afternoon.
There will be an hour for lunch each day, but this will not be provided. Several dining options are available, including a Waitrose in the Brunswick Centre, 5 minutes from where the course will take place. Opposite Russell Square Station, you will find a Pret a Manger and a Tesco.
Course materials
Participants will be given access to the course materials during the course, and will be free to take them with them, including code and simulated data used in the practicals.
Registration
Please register here.
“Really enjoyed the course, great mixture of lectures and practicals with plenty of time for discussion and questions. The lecturers were very knowledgeable and approachable.”
“Outstanding course. Brilliant lectures delivered by experts in the field and stimulating group practicals.”
“This was such an excellent and insightful course! The content was super informative, and I really appreciated how well everything was structured. Karla, Neil, and Peter did a fantastic job explaining the concepts"