In regression models, the CLASS statement enables you to estimate parameters for the levels of a categorical variable, thereby estimating the effect of each level on the response.
Another use of a CLASS variable is to define categories for a meanns task, such as a discriminant analysis. Cars data. For efficiency reasons, most classical SAS procedures require that you sort the data when you use a BY statement. What changes is the way that the statistics are displayed.
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When you emans the CLASS statement, you get one table that contains all statistics or one graph that shows the distribution of each subgroup. However, when you use the BY statement you get multiple tables and graphs. Each analysis is preceded by a label that identifies each BY group. Notice that the BY-group analysis uses the sorted data.
Sort Output of Proc Means by Mean
Comparing ooptions The procedure automatically creates a graph that displays three boxplots, one for each group. The procedure automatically produces a graph that overlays the three regression curves on the data: You get three parameter estimates tables and three graphs, otpions showing one regression soutyern overlaid on a subset of the data. Specify the statistics that you want to see: The solution now requires several lines of typing. It's not onerous, but it is a lot to remember: This solution requires using ODS statements to direct the output to a data set while suppressing it from appearing on the screen. It is a nice trick in general, but there is an easier way for this particular task.
Cool SAS option: As an extra bonus, you do not have to type the names of any statistics.
Transposing Statistics from PROC MEANS
The following statement computes 46 statistics for each numerical variable in the input data set. The data set UniSummary contains the results. The names begin and end with an underscore.