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Logistic Regression Using SAS®: Theory and Application by Paul D. Allison

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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 
  YesUndecidedNo
WhiteFemale3714974
 Male2504571
BlackFemale64915
 Male25513

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; ...

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