Multivariate Analysis: Discrete Variables (Logistic Regression)

Abstract

In this article the main features of logistic regression are described and some aspects of interpretation of logistic regression are illustrated with an example. The logistic regression model is first introduced for the simple case where there is only a single predictor variable. This model is compared and contrasted with the classical linear regression model. Later the generalizations to more than one predictor variables are considered. A major emphasis of this article is placed on how logistic regression is used in practice and how the logistic regression coefficients should be interpreted. An example, based on data from the US General Social Survey, is used to illustrate and reinforce the main concepts. Finally, extensions of logistic regression to clustered data are also considered.