Regression Analysis and Discriminant Analysis: An Application of R. A. Fisher's Theorem to Data in Political Science

Abstract

The conversion of multiple regression analysis to discriminant analysis is not only of theoretical interest, but—in view of the extensive use of these methods in political science—it also has considerable value for applications. It is the purpose of this presentation to explain the underlying theoretical relationship and to demonstrate its application in the form of an example chosen from the judicial process. Specifically, the Supreme Court's acceptance or rejection of the fact that the defendant was not advised of his right to counsel in an involuntary confession case is considered as a function of the appearance, nonappearance, or denial of the fact in lower court records and appellate briefs. Since the acceptance or rejection of the fact by the Supreme Court is a dichotomous dependent variable, discriminant analysis is appropriate. It is shown in this study how discriminant analysis can be employed by initially using regression analysis, not only in the example presented for illustration, but in any situation in which a phenomenon with dichotomous manifestations may be examined as a function of specified variables.