Causal Inference and Causal Diagrams for Target Trial Emulations Using Evidence From Real-World Observational Studies and Clinical Trials

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This course will introduce innovative causal inference approaches for the design and analysis of big real-world observational data and pragmatic trials. Topics include causal diagrams (DAGs), target trial emulation, and causal methods for time-independent confounding (multivariate regression, propensity scores) and time-dependent confounding (g-methods), illustrated using clinical case examples.