Emulating Target Trials to Improve Causal Inference From Agent-Based Models

Epidemiologists face two fundamental and interrelated problems when judging causality: knowledge is fallible, and studies are imperfect. In medicine, this will always leave a degre...

Causal modeling and inference rely on strong assumptions, one of which is conditional exchangeability. Uncontrolled confounding is often seen as if it is the most important threat ...