Logistic Regression

This chapter discusses statistical models for a dichotomous qualitative response variable. The statistical models discussed are logistic regression models or binary regression models. The use of logistic regression has only recently been made possible with the widespread availability of microcomputers and statistical computing packages, and as a result, logistic regression models are now commonly used in biomedical research for modeling a dichotomous response variable as a function of a set of explanatory variables. The chapter also discusses methods for checking the assumptions of a logistic regression model. After fitting and assessing the fit of a logistic regression model, provided none of the assumptions are violated and the model is fitting the observed data adequately, the fitted model can be used for making statistical inferences about the relationship between the response variable and the explanatory variables. An important application of logistic regression is in the two-category classification problem.