# Combine variables for Simple Correspondence Analysis

Stat > Multivariate > Simple Correspondence Analysis > Combine

If you entered 3 or 4 worksheet columns in Categorical variables on the main dialog box, you can cross the variables to form the rows and/or the columns of a two-way contingency table. Crossing variables allows you to use this analysis to evaluate data from three-way and four-way contingency tables.

You can cross the first two variables to form rows and/or the last two variables to form columns. To only cross variables for either rows columns, you must enter three categorical variables on the main dialog box. To cross variables for both rows and columns, you must enter four categorical variables on the main dialog box.

Define Rows of Contingency Table Using

Select one of the following options to define the rows:

• First variable: Use the first column that you entered on the main dialog box to form the rows of the contingency table. Select this option if you do not want to cross variables to form the rows.
• First 2 variables crossed: Cross the categories in the first two columns that you entered on the main dialog box to form the rows of the contingency table.
Define Columns of Contingency Table Using

Select one of the following options to define the columns:

• Last variable: Use the last column that you entered on the main dialog box to form the columns of the contingency table. Select this option if you do not want to cross variables to form the columns.
• Last 2 variables crossed: Cross the categories in the last two columns that you entered on the main dialog box to form the columns of the contingency table.

The following example shows row crossing. Column crossing is similar. Suppose you have two variables. The row variable, Gender, has two levels: male and female. The column variable, Age, has three levels; young, middle aged, elderly.

Crossing Gender with Age creates 2 x 3 = 6 rows in a two-way contingency table, as follows:
 Female Elderly Female Middle aged Female Young Male Elderly Male Middle aged Male Young
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