  One way to start thinking about what we have to explain in psychiatry is to borrow from Thagard’s (1999, 114–5) account of diseases as networks of “statistically based causal relations” which are discovered using epidemiological and experimental methods. This fits the picture that Kendler and Prescott present for depression quite neatly (although their models are designed to incorporate both causal relations between variables and correlations). Thagard’s causal-statistical networks, like Kendler and Prescott’s path models, provide “a kind of narrative explanation of why a person becomes sick” (p15). They incorporate information about the typical course of a disease as it unfolds over time, including information about typical risk factors for the disease—such as the finding that heavy use of aspirin increases acid secretion which makes a duodenal ulcer more likely. The causal network does not specify how each causal factor produces its effects, though. It is really a descriptive model that lets us ask the question; what facts make it true that people get sick in these ways?