Causal Inference

Catalog description

As the need for causal discovery increases, and supportive data are increasingly available, there is a growing need to understand causal inference methods and applications beyond experiments. This course is a survey of a broad array of topics including the concepts of causal inference, causal inference methods, and applications of and implementation of causal inference techniques. Topics will include causal diagrams, and causal inference methods such as propensity score methods, instrumental variables, and methods for time-varying exposures Implementation of the methods using statistical software will be addressed. Prerequisites include a regression course and a statistical software course.