Path analysis is an extension of multiple regression. It goes beyond regression in that it allows for the analysis of more complicated models. In particular, it can examine situations in which there are several final dependent variables and those in which there are “chains” of influence, in that variable A influences variable B, which in turn affects variable C. Despite its previous name of “causal modelling,” path analysis cannot be used to establish causality or even to determine whether a specific model is correct; it can only determine whether the data are consistent with the model. However, it is extremely powerful for examining complex models and for comparing different models to determine which one best fits the data. As with many techniques, path analysis has its own unique nomenclature, assumptions, and conventions, which are discussed in this paper.