Causal inference in register studies, 7.5 Credits
About the course
Two languages for causal reasoning and inference are presented; i) the potential outcome framework (Rubin Causal Model) and ii) graphical models (structural models). Identification of causal parameters is discussed within the two approaches. Non- and semi-parametric estimators of average causal effects, and their associated inference, are presented. Observational studies using registers and other large scale microdata studies are used as motivation for the models and methods presented.
Level of Education: Advanced
Course Menu
Contact Information
Department of Statistics
