The LOGISTIC Procedure

Overview

You can now fit a generalized logit model when you have nominal response data. In this multiple-logit model, each nonreference response category is contrasted against the reference category. This model reduces to the binary logit model when there are only two response categories. Unlike the cumulative logit model (for ordinal response data) that contains one set of slope parameters for the entire model, the generalized logit model contains a set of slope parameters for each response category other than the reference category. The generalized logit model is specified by the MODEL statement option LINK=GLOGIT. You can choose the response category to use as the reference in forming the various logit functions. The default is to use the last response category as the reference.

Options specific to the response variable can be specified immediately after the response variable in the MODEL statement by enclosing them in a pair of parentheses. These response variable options include

the EVENT= option for specifying the event category for binary response models
the REFERENCE= option for specifying the reference category
the ORDER= option for specifying the sorting order of the response categories
the DESCENDING option for reversing the order of the response categories

For ordinal models, names of the intercept parameters in the OUTEST= data are changed to reflect the corresponding response levels.

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