Logistic Regression Using SAS®: Theory and Application

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 happy	Pretty happy	Not too happy
1974	Married	473	493	93
	Unmarried	84	231	99
1984	Married	332	387	62
	Unmarried	150	347	117
1994	Married	571	793	112
	Unmarried	257	889	234

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 ...