Hierarchial causal models are described as pictorial representations of multiple regression equations. These models are particularly helpful for three reasons: (1) the formulation of problems in a path analytic framework forces a degree of explicitness that is often not present in research reports that rely solely on regression; (2) they provide a…

The purpose of this paper is to illuminate the advantages of path analysis for the exposition of results in data analytic papers. Probably the greatest advantage is that it provides a means by which the nature of the problem may be handily summarized. The method of path analysis, although conceived over sixty years ago by Sewell Wright, has only…

With even the simplest bivariate regression, least-squares solutions are inappropriate unless one assumes a priori that reciprocal effects are absent, or at least implausible. While this discussion is limited to bivariate regression, the issues apply equally to multivariate regression, including stepwise regression. (Author/CTM)