Validating the Logistic Regression Model

The purpose of this write-up is to introduce the principal features of a bootstrap validation method for the ever-popular logistic regression model.

Lest the model builder forgets, the logistic regression model (LRM) depends on the important assumption that the logit of the probability for a binary dependent variable (Y, typically assumes character values yes and no; or numeric values 0 and 1), is a linear function of predictor variables (X1, X2, ... , Xn). Recall, the logit of a probability p is defined as log (p/1 - p), where log represents the natural logarithm.

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