Model Fitting: Logistic Regression |
The Logistic Regression analysis fits a logistic regression model by using the method of maximum likelihood estimation.
If are explanatory variables and
is the response probability
to be modeled, the logistic model has the form
The explanatory variables in the Logistic Regression analysis can be interval variables or nominal variables (also known as classification variables). You can also specify more complex model terms such as interactions and nested terms. Any term specified in the model is referred to as an effect, whether it is the main effect of a variable, or a classification variable, or an interaction, or a nested term.
You can run a Logistic Regression analysis by selecting
Analysis Model Fitting
Logistic Regression from the main menu.
The computation of
the estimated regression coefficients, confidence limits, and related
statistics is implemented by calling the LOGISTIC procedure in
SAS/STAT. See the
documentation for the LOGISTIC procedure
in the SAS/STAT User's Guide for additional details.