DAGs are an essential tool for understanding causal inference. They help researchers identify potential biases and confounders that need to be controlled for in order to estimate the true effect of an exposure on an outcome. By clearly laying out the assumed causal relationships, they provide a structured approach to thinking about complex epidemiological problems and improve the transparency of causal assumptions.
