If you're doing some analysis with categorical data and you're using a proc that does not support the CLASS statement, then you may need to create dummy variables.
I won't go into what dummy variables are, but how to create them using GLMMOD.
Problem: Create dummy variables for sex and age from sashelp.class dataset.
/*Run model within PROC GLMMOD for it to create design matrix Include all variables that might be in the model*/ proc glmmod data=sashelp.class outdesign=want outparm=p; class sex age; model weight = sex age height; run; /*Create rename statement automatically THIS WILL NOT WORK IF YOUR VARIABLE NAMES WILL END UP OVER 32 CHARS*/ data p; set p; if _n_=1 and effname='Intercept' then var='Col1=Intercept'; else var= catt("Col", _colnum_, "=", catx("_", effname, vvaluex(effname))); run; proc sql; select var into :rename_list separated by " " from p; quit; /*Rename variables*/ proc datasets library=work nodetails nolist; modify want; rename &rename_list; run;quit; proc print data=want; run;
The WANT dataset can now be used to model with the dummy variables present.
Here are some additional articles about how to create dummy variables in SAS. They contain discussion and examples:
A design matrix is a numeric matrix that representes all variables (continuous and categorical) in a regression model.