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 examine the validity of regression estimates when skewed dichotomous scales are used as independent variables. When Pearson product-moment correlations are used to measure zero-order associations involving dichotomous variables, the resulting coefficients underestimate the true associations. As a result, using…

The author is generally critical of the previous article (TM 503 686), which concerned the use of multiple regression for nonparametric analysis of variance. (JKS)

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)

A LISREL analysis demonstrates the value of regressing reputational ratings on three latent variables: size, faculty research productivity, and the quality of program graduates. The model was tested using National Research Council data for each of six disciplines: English, French, philosophy, geography, political science, and sociology.…