In which scenario would you use the CLASS statement?

The CLASS statement is specifically designed to handle categorical variables in SAS procedures. When you use the CLASS statement, you can identify which variables in your dataset are categorical so that the procedure can appropriately analyze these variables. This is particularly important in statistical analysis because categorical variables often require different handling compared to continuous variables.

For instance, when performing ANOVA or regression analysis, including the CLASS statement allows SAS to understand that the specified variables represent different groups or categories rather than numerical values. This enables proper partitioning of the data and accurate computation of statistics relevant to those categories.

Using the CLASS statement is essential when you want to conduct group comparisons or examine the impact of factors that are not measured on a continuous scale, such as gender, treatment type, or other classifications. By specifying these variables, SAS can generate the necessary statistical outputs that reflect the differences among groups, which is a fundamental aspect of many analytic methods.

In contrast, defining numeric outcome variables, sampling from controlled studies, or calculating overall summary statistics doesn’t require a distinction between categorical variables and those that are continuous, which is the primary function and benefit of the CLASS statement.