APTS Causal Inference Module

This module focuses on causal inference, covering methods for establishing cause-and-effect relationships from data.

Course Overview

This module provides an in-depth exploration of causal inference, equipping students with the tools and knowledge to analyze and interpret causal relationships from observational and experimental data.

Key Topics

• Potential Outcomes Framework: Introduction to the Rubin Causal Model.
• Randomization and Observational Studies: Design and analysis considerations.
• Confounding and Bias: Identification and mitigation strategies.
• Instrumental Variables: Using instrumental variables for causal estimation.
• Mediation Analysis: Understanding pathways of causal effects.

Course Materials

Online notes are available here.