![]() ![]() So let's cut to the chase: If you want to generate dummy variables in SAS, use PROC GLMSELECT. I usually avoid saying "this is the best way" to do something in SAS.īut if you are facing an impending deadline, you are probably more interested in solving your problem and less interested in comparing five different ways to solve it. Why GLMSELECT is the best way to generate dummy variables You might not need to create the dummy variables yourself. If a procedure supports the CLASS statement, Procedure will internally create and use the dummy variables. Support the CLASS statement, which enables you to specify categorical variables and various encodings. Although the focus of this article is dummy variables, PROC GLMSELECT can create many kinds of manufactured effects such as spline effects and interaction effects.īefore creating dummy variables, as yourself if you really need them. These variables are part of the design matrix that is used for solving a linear regression model. The j_th dummy variable indicates the presence (1) or absence (0) of the j_th category. Given a categorical variable, X, that has k levels, you can generate k dummy variables. This article shows an example of generating dummy variables that have meaningful names, which are based on the name of the original variable and the categories (levels) of the variable.Ī dummy variable is a binary indicator variable. ![]() It is not necessary to write a SAS program to generate dummy variables. The simplest and easiest way to generate dummy variables in SAS is to use PROC GLMSELECT. Well-meaning responders offer all sorts of advice, including writing your own DATA step program, sometimes mixed with macro programming. On discussion forums, many SAS programmers ask about the best way to generate dummy variables for categorical variables.
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