Graphical Tools for Linear Path Models

This article introduces tools for analyzing path diagrams using graphical methods, which are better known in epidemiology than among researchers in the behavioral sciences, who would be more familiar with traditional structural equation modeling (SEM). We describe graphical tools that locate covariates for adjustment and instrumental variables, both of which can be used to identify and estimate individual causal effects. These tools also find conditional independences implied by the model and overidentified parameters, which can be used to test the model at the level of local fit. Their application in a real data set is demonstrated with a freely-available computer tool.