What is another name for causal diagrams used to visualize causal relationships in epidemiology?

• A. Random forest
• B. Directed acyclic graphs or modified path models
• C. Linear regression model
• D. Time-series graph

Answer: (B)

In epidemiology, the causal diagrams used to visualize how variables influence each other are directed acyclic graphs, or DAGs. A DAG represents variables as nodes and direct causal effects as arrows between them, with the important constraint that there are no cycles—no feedback loops. This acyclic structure lets researchers map out all paths from an exposure to an outcome and reason about potential confounding, mediating, and colliding variables. It also provides a practical way to decide which variables to adjust for to identify the causal effect, using ideas like the backdoor criterion. While some related terms like path models exist, the standard name for this type of causal diagram is directed acyclic graphs. The other options describe different methods or graph types (for example, modeling algorithms or time-series visuals) and do not serve the same purpose of encoding causal assumptions.