PROC LOGISTIC MODELING Options
Use this text box to specify options for the PROC LOGISTIC MODEL statement.
The MODEL statement names the response variable and the explanatory effects, including covariates, main effects, interactions, and nested effects.
Note: To enable this field, you must select Automated as the analysis Mode.
You can specify any PROC LOGISTIC Modeling option using the following syntax:
Option
where:
• | Option is the PROC LOGISTIC Model Statement option. |
• | Enclose the options within parentheses, for example (EVENT="cancer"), where "cancer" is one of the levels of the dependent class variable. |
Some PROC LOGISTIC Modeling options are described in the following table:
Option |
Definition |
EVENT=”event” |
Specifies the event category for the binary response model. PROC LOGISTIC models the probability of the event category. The EVENT= option has no effect when there are more than two response categories. You can specify the value (formatted if a format is applied) of the event category in quotation marks. |
INCLUDE=n |
Includes the first n effects in the MODEL statement in every model. By default, INCLUDE=0. |
MAXITER=n |
Choose this option to specify the maximum number of iterations to perform. By default, MAXITER=25. If convergence is not attained in the number of iterations, the displayed output and all output data sets created by the procedure contain results that are based on the last maximum likelihood iteration. |
OUTROC=name |
Choose this option to create and name, for binary response models, an output SAS data set that contains the data necessary to produce the receiver operating characteristic (ROC) curve. |
To Specify One or More PROC LOGISTIC Response Options:
8 | Make sure that Automated has been selected as the analysis Mode. |
8 | Type specific PROC LOGISTIC Modeling options in the PROC LOGISTIC Modeling Options field. |
8 | For example, to specify cancer as the event category, type (EVENT=”cancer”) in the text box. |
8 | Be sure to separate individual options with a space. |
Refer to the SAS PROC LOGISTIC MODEL Statement documentation for more information.