Causal Inference in R

This workshop provides a structured introduction to causal inference, guiding participants from formulating causal questions to estimating and communicating causal effects using R. Topics include the transition from associational to causal thinking, the role of counterfactuals, and the use of causal diagrams to formalize assumptions. Participants will learn to define causal estimands, implement and diagnose propensity score models, and build outcome models. The workshop also covers methods for continuous exposures, including g-computation, and concludes with approaches to sensitivity analysis. Hands-on exercises in R reinforce each concept, enabling participants to apply modern causal inference techniques in practice.

April 9, 2026

8:30 AM – 5:30 PM

Workshop on Experiments at NEOMA Business School Reims, France 2026