Loterre: SAGE: causal diagrams

... > health > public health > epidemiology > statistics and research methods > causal diagrams

causal diagrams

From their inception in the early 20th century, causal systems models (more commonly known as structural-equations models) were accompanied by graphical representations or path diagrams that provided compact summaries of qualitative assumptions made by the models. Figure 1 provides a graph that would correspond to any system of five equations encoding these assumptions: Independence of A and B Direct dependence of C on A and B Direct dependence of E on A and C Direct dependence of F on C Direct dependence of D on B, C, and E The interpretation of “direct dependence” was kept rather informal and usually conveyed by causal intuition, for example, that the entire influence of A on F is “mediated” by C. Figure 1 Example of a Directed Acrylic Graph By the 1980s, it was recognized that these diagrams could be reinterpreted formally as probability models, which opened the visual power of graph theory for use in probabilistic inference and allowed easy deduction of other independence conditions implied by the assumptions. [Source: Encyclopedia of Epidemiology; Causal Diagrams]

http://data.loterre.fr/ark:/67375/N9J-MR4P556Q-G

RDF/XML TURTLE JSON-LD

LOTERRE