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

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6.5. Cumulative Logit Model: Contingency Tables

The cumulative logit model can be very useful in analyzing contingency tables. Consider Table 6.1, which was tabulated by Sloane and Morgan (1996) from the General Social Survey. Our goal is to estimate a model for the dependence of happiness on year and marital status.

Table 6.1. General Happiness by Marital Status and Year
  Very happyPretty happyNot too happy
1974Married47349393
 Unmarried8423199
1984Married33238762
 Unmarried150347117
1994Married571793112
 Unmarried257889234

Here’s the SAS program to read the table:

DATA happy; INPUT year married happy count; y84 = year EQ 2; y94 = year EQ 3; DATALINES; 1 1 1 473 1 1 2 493 1 1 3 93 1 0 1 84 1 0 2 231 1 0 3 99 2 1 1 332 2 1 2 387 2 1 3 62 2 0 1 150 ...

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