When you use the CLASS statement with the CDFPLOT, HISTOGRAM, PPPLOT, PROBPLOT, or QQPLOT statements, PROC UNIVARIATE creates comparative versions of the plots. You can use these plot statements with the CLASS statement to create one-way and two-way comparative plots. When you use one CLASS variable, PROC UNIVARIATE displays an array of component plots (stacked or side-by-side), one for each level of the classification variable. When you use two CLASS variables, PROC UNIVARIATE displays a matrix of component plots, one for each combination of levels of the classification variables. The observations in a given level are referred to collectively as a cell.

When you create a one-way comparative plot, the observations in the input data set are sorted by the method specified in the ORDER= option. PROC UNIVARIATE creates a separate plot for the analysis variable values in each level and arranges these component plots in an array to form the comparative plot with uniform horizontal and vertical axes. See Example 4.15.

When you create a two-way comparative plot, the observations in the input data set are cross-classified according to the values (levels) of these variables. PROC UNIVARIATE creates a separate plot for the analysis variable values in each cell of the cross-classification and arranges these component plots in a matrix to form the comparative plot with uniform horizontal and vertical axes. The levels of the first CLASS variable are the labels for the rows of the matrix, and the levels of the second CLASS variable are the labels for the columns of the matrix. See Example 4.16.

PROC UNIVARIATE determines the layout of a two-way comparative plot by using the order for the first CLASS variable to obtain the order of the rows from top to bottom. Then it applies the order for the second CLASS variable to the observations that correspond to the first row to obtain the order of the columns from left to right. If any columns remain unordered (that is, the categories are unbalanced), PROC UNIVARIATE applies the order for the second CLASS variable to the observations in the second row, and so on, until all the columns have been ordered.

If you associate a label with a CLASS variable, PROC UNIVARIATE displays the variable label in the comparative plot and this label is parallel to the column (or row) labels.

Use the MISSING option to treat missing values as valid levels.

To reduce the number of classification levels, use a FORMAT statement to combine variable values.