 In recent years, the formal analysis of causation has been significantly enhanced by the development of graphical methods for representing causal hypotheses and for choosing among candidate hypotheses given one’s evidence, in particular those using directed acyclic graphs (=DAGs: Pearl 1988, 2000 [2009]; Spirtes et al. 2000). A DAG contains a set of nodes connected by a set of directed edges or arrows such that there are no cycles (one cannot get from a node back to itself via a set of directed arrows). In the causal context, the nodes in a DAG are random variables and the arrows correspond to direct causal relationships. It is common to assume that the set of variables in a DAG is causally sufficient, meaning that it includes all common causes of variables in the set.