MDCRC 6270 - Applied Modern Causal Inference In Comparative Effectiveness Research

This course will cover some of the applications of modern causal inference methods in comparative effectiveness research. The course will extend the theoretical frameworks for modern causal inference including counterfactuals, directed acyclic graphs and their use in identifying bias due to confounding, selection bias, and conditioning on intermediates. This course will cover research designs and methods that researchers use to support casual inferences in epidemiology, health services research, and health economics. Some specific topics include randomized trials, network meta-analysis, instrumental variables, propensity score matching, inverse probability of treatment weighting, marginal structural models, and differences in differences.This course will focus on randomized and observational designs used for comparative effectiveness research. Design and statistical analysis will be framed in terms of counterfactual outcomes and required assumptions for causal inference.