MODEL response <(responseoptions)> = <effects> </ modeloptions>;
MODEL events / trials <(responseoptions)> = <effects> </ modeloptions>;
The MODEL statement defines the statistical model in terms of a response variable (the target) or an events/trials specification, model effects constructed from variables in the input data set, and options. An intercept is included in the model by default. You can remove the intercept with the NOINT option.
You can specify a single response variable that contains your binary, ordinal, or nominal response values. When you have binomial data, you can specify the events/trials form of the response, where one variable contains the number of positive responses (or events) and another variable contains the number of trials. Note that the values of both events and (trials – events) must be nonnegative and the value of trials must be positive.
For information about constructing the model effects, see the section Specification and Parameterization of Model Effects.
There are two sets of options in the MODEL statement. The responseoptions determine how the HPLOGISTIC procedure models probabilities for binary data. The modeloptions control other aspects of model formation and inference. Table 10.3 summarizes these options.
Table 10.3: MODEL Statement Options
Option 
Description 

Response Variable Options 

Reverses the response categories 

Specifies the event category 

Specifies the sort order 

Specifies the reference category 

Model Options 

Specifies the confidence level for confidence limits 

Requests association statistics 

Requests confidence limits 

Requests classification statistics 

Specifies a cutpoint for binary classification 

Specifies the degreesoffreedom method 

Includes effects in all models for model selection 

Requests the Hosmer and Lemeshow goodnessoffit test 

Specifies the link function 

Suppresses checking for infinite parameters 

Suppresses the intercept 

Specifies the offset variable 

Specifies prior probabilities 

Requests a generalized coefficient of determination 

Includes effects in the initial model for model selection 
Response variable options determine how the HPLOGISTIC procedure models probabilities for binary and multinomial data.
You can specify the following responseoptions by enclosing them in parentheses after the response or trials variable.