## Types of Input Data

The data that PROC CATMOD analyzes are usually supplied
in one of two ways. First, you can supply raw data, where
each observation is a subject. Second, you can supply cell
count data, where each observation is a cell in a
contingency table. (A third way, which uses direct input of
the covariance matrix, is also available; details are given
in the "Inputting Response Functions and Covariances Directly" section.)
Suppose detergent preference is related to three other
categorical variables: water softness, water temperature,
and previous use of a brand of detergent. In the raw data
case, each observation in the input data set identifies
a given respondent in the study and contains
information on all four variables. The data set
contains the same number of observations as the survey had
respondents. In the cell count case, each observation
identifies a given cell in the four-way table of water
softness, water temperature, previous use of brand, and
brand preference. A fifth variable contains the number of
respondents in the cell. In the analysis, this fifth
variable is identified in a WEIGHT statement. The
data set contains the same number of observations as
the number of cross-classifications formed by the four
categorical variables. For more on this particular example,
see Example 22.1. For additional details, see
the section "Input Data Sets".

Most of the examples in this chapter use cell counts as
input and use a WEIGHT statement.

Copyright © 1999 by SAS Institute Inc., Cary, NC, USA. All rights reserved.