MODEL Statement

MODEL variable < (variable_options) > = < effects >< /options >;

DESCENDING | DESC

reverses the order of the response categories (levels). If both the DESCENDING and ORDER= options are specified, PROC LOGISTIC orders the response categories according to the ORDER= option and then reverses that order.

EVENT=`category' | keyword

specifies the event category (level) 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 event category (formatted if a format is applied) in quotes or you can specify one of the following keywords. The default is EVENT=FIRST.

FIRST: designates the first ordered category as the event
LAST: designates the last ordered category as the event

Consider the example where the response variable Y takes the values 1 and 0 for event and nonevent, respectively, and Exposure is the explanatory variable. To model the event probability, you simply specify

   proc logistic;
      model Y(event='1') = Exposure;
   run;

ORDER= DATA | FORMATTED | FREQ | INTERNAL

specifies the sorting order of the categories (levels) of the response variable. The following table shows the interpretation of the ORDER= values.

Value of ORDER=	Levels Sorted By
DATA	order of appearance in the input data set
FORMATTED	external formatted value, except for numeric
	variables with no explicit format, which are
	sorted by their unformatted (internal) value
FREQ	descending frequency count; levels with the
	most observations come first in the order
INTERNAL	unformatted value

By default, ORDER=FORMATTED. For the FORMATTED and INTERNAL specifications, the sort order may be machine dependent. For numeric response variables with no explicit format (that is, no corresponding FORMAT statement in the current PROC LOGISTIC run or in the DATA step that created the data set), ORDER=FORMATTED orders the response levels by their numeric values.^*

For more information on sorting order, see the chapter on the SORT procedure in the SAS Procedures Guide.

REFERENCE=`category' | keyword

REF=`category' | keyword

specifies the reference category for the generalized logit model and the binary response model. For the generalized logit model, each nonreference category is contrasted with the reference category. For the binary response model, specifying one response category as the reference is equivalent to specifying the other response category as the event category. You can specify the reference category (formatted if a format is applied) in quotes or you can specify one of the following keywords. The default is REF=LAST.

FIRST: designates the first ordered category as the reference
LAST: designates the last ordered category as the reference

LINK=keyword

L=keyword

specifies the function linking the response probabilities to the linear predictors. You can specify one of the following keywords. The default is LINK=LOGIT.

CLOGLOG: the complementary log-log function. PROC LOGISTIC fits the binary CLOGLOG model when there are two response categories and fits the cumulative CLOGLOG model when there are more than two response categories.
GLOGIT: the generalized logit function. PROC LOGISTIC fits the generalized logit model where each nonreference category is contrasted with the reference category. You can use the response variable option REF= to specify the reference category.
LOGIT: the log odds function. PROC LOGISTIC fits the binary logit model when there are two response categories and fits the cumulative logit model when there are more than two response categories.
PROBIT: the inverse standard normal distribution function. PROC LOGISTIC fits the binary probit model when there are two response categories and fits the cumulative probit model when there are more than two response categories.