With VAR statement input, the rows of the contingency table correspond to the observations of the input data set, and the columns correspond to the VAR statement variables. The values of the variables typically contain the table frequencies. The table in Figure 30.3 could be created with VAR statement input by using the following statements:

   data Ages;
      input Sex $ Old Young;
      datalines;
   Female  2 2
   Male    4 3
   ;
   
   proc corresp data=Ages dimens=1 observed short;
      var Old Young;
      id Sex;
   run;

Only nonnegative values are accepted. Negative values are treated as missing, causing the observation to be excluded from the analysis. The values are not required to be integers. Row labels for the table are specified with an ID variable. Column labels are constructed from the variable name or variable label if one is specified. When you specify multiple correspondence analysis (MCA), the row and column labels are the same and are constructed from the variable names or labels, so you cannot include an ID statement. With MCA, the VAR statement must list the variables in the order in which the rows occur. An example is the table in Figure 30.6, which was created with the following TABLES statement.

      tables Hair Height Sex Age;

This table could have been created with a VAR statement as follows:

   proc corresp data=table nvars=4 mca;
      var Blond Brown White Short Tall Female Male Old Young;
   run;

You must specify the NVARS= option in order to specify the number of original categorical variables with the MCA option. The option NVARS= is needed to find boundaries between the subtables of the Burt table. If is the sum of all elements in the Burt table , then is the number of rows in the binary matrix . The sum of all elements in each diagonal subtable of the Burt table must be .

To enter supplementary observations, include a WEIGHT statement with negative weights for those observations. Specify the SUPPLEMENTARY statement to include supplementary variables. You must list supplementary variables in both the VAR and SUPPLEMENTARY statements.