Prerequisites: BIOSTAT 601, BIOSTAT 602, BIOSTAT 650, BIOSTAT 651, BIOSTAT 653, BIOSTAT 801, and BIOSTAT 802 (concurrent also accepted).
Description: This course covers statistical theory and methodology for drawing causal conclusions from observational and experimental data. We will cover theoretical foundations including DAGs and SEMs, followed by special topics, which may include instrumental variable analysis, causal inference in high dimensions, and causal inference with longitudinal data.
Learning Objectives: At the end of the course the students will be able to:
1. Translate a scientific question into a causal contrast to be estimated.
2. Derive graphical models for investigating the conditions under which the causal contrasts of interest are identified from data collected under specific study designs.
3. Formulate adequate structural models for making inference about the causal contrasts of interest.
4. Implement simulations appropriate for investigating the properties of causal estimators.
