Logistic Regression

Abstract

In bivariate and multiple regression (Chapters 12 and 13), we used a continuous dependent variable. There are occasions in which the outcome is an either-or (0, 1) binary outcome. Fisher developed a technique known as discriminant analysis for predicting group membership (by maximizing the combination of predictor scores to separate the two groups). This is a fine technique, and one that has been around for a long time. There is, however, one major problem with discriminant analysis, namely that it can take advantage only of continuous predictors. A more modern technique to the prediction (and classification as desired) of group membership in two groups represented by 0s and 1s is known as logistic regression. Logistic regression allows the use of both continuous and binary predictors.