You can fit a model to a binomial (two level) response by specifying the DIST=BINOMIAL option in the MODEL statement. The default link function is the logit link yielding a logistic model. Specify LINK=PROBIT in the MODEL statement to request a probit model or LINK=CLOGLOG to use the complementary log log link (useful when the shape of the model is not symmetric). By default, the lower response level is modeled as in the LOGISTIC and PROBIT procedures. Use the DESCENDING option in the MODEL statement to reverse the response order and model the higher level. Always check the Response Profile table to verify that the desired order is used.

You can also use PROC GENMOD to fit a model to ordinal multinomial response data (that is, categorical response data with more than two levels that are ordered) by specifying the DIST=MULTINOMIAL option in the MODEL statement. PROC GENMOD cannot model an unordered (nominal) multinomial response. With this option, GENMOD fits a model that treats the response as an ordinal variable by modeling a set of cumulative response probabilities through a link function (LINK=CLOGIT for cumulative logits, LINK=CPROBIT for cumulative probits, or LINK=CLOGLOG for cumulative complementary log-log functions). The default cumulative logit link fits the same model that PROC LOGISTIC or PROC PROBIT fits by default to multinomial data. The cumulative logit link produces a ordinal logistic model assuming proportional odds. A test of this assumption is not available in PROC GENMOD as it is in PROC LOGISTIC. Specify LINK=CPROBIT in the MODEL statement to request an ordinal probit model. By default, the probabilities of lower response levels are modeled as in the LOGISTIC and PROBIT procedures. Use the DESCENDING option in the MODEL statement to reverse the response order and model the probabilities of the higher levels. Always check the Response Profile table to verify that the desired order is used.

If your multinomial response is not ordered (is nominal, rather than ordinal), you can use the LINK=GLOGIT option in the MODEL statement of PROC LOGISTIC or PROC GLIMMIX to fit a generalized logit model appropriate for a nominal response.