Standard Binary Logistic Regression Model

The logistic regression model is a type of predictive model that can be used when the response variable is binary, for example, live/die, disease/no disease, purchase/no purchase, win/lose, etc. In short, we want to model the probability of a certain event, in effect modeling the mean of the variable (which is the same as the probability in the case of binary variables). This chapter makes a case for the logistic regression model as a popular binary model because of its ability to make statements about the odds of an event. It is particularly appropriate when analyzing binary data as opposed to a simple linear regression model. We present three significant problems that one may encounter when a linear regression model is fitted to binary data: