INTRODUCTION TO CAUSAL INFERENCE BY RHIAN DANIEL (CARDIFF UNIVERSITY)

This course is a whistle-stop tour of the key concepts and methods in causal inference, suitable for newcomers to the area. The emphasis throughout is more strongly on the concepts than the methods, with the aim of giving participants enough familiarity with the topics that they are able to follow the majority of the talks in the main EURO-CIM meeting. The course will touch on the following:

• Causal language (do-notation, potential outcomes, counterfactuals)

• Identification, and assumptions that make identification possible (conditional exchangeability / no unmeasured confounding, consistency, positivity, no interference)

• Non-parametric and parametric estimation (including the role of traditional regression models in causal inference)

• Graphical methods (DAGs and SWIGs)

• The propensity score and associated methods

• Instrumental variables (including Mendelian randomisation and the regression discontinuity design)

• Longitudinal casual effects and time-dependent confounding

• Mediation analysis

The course will be delivered via a combination of pre-recorded short videos, “live” video lectures, a small-group discussion and a short practical session (which can be completed using any statistical software). Although the pre-recorded videos will be made available in advance, there will be breaks during the course for these to be watched.