Logistic Regression Using SAS®: Theory and Application

5.7. Contingency Table Analysis

As with binary logit analysis, the multinomial logit model can be easily applied to the analysis of contingency tables. Consider Table 5.3, which was tabulated from the 1991 General Social Survey (Agresti 1996).

Table 5.3. Belief in an Afterlife, by Gender and Race

			Belief in Afterlife
		Yes	Undecided	No
White	Female	371	49	74
	Male	250	45	71
Black	Female	64	9	15
	Male	25	5	13

The dependent variable—belief in an afterlife—has three categories, which we’ll treat as unordered. Here’s how to fit the multinomial logit model with CATMOD:

DATA my.afterlif; INPUT white female belief freq; DATALINES; 1 1 1 371 1 1 2 49 1 1 3 74 1 0 1 250 1 0 2 45 1 0 3 71 0 1 1 64 0 1 2 9 0 1 3 15 0 0 1 25 0 0 2 5 0 0 3 13 ; PROC CATMOD DATA=my.afterlif; ...