Hello everyone,
Currently I'm trying to employ multiple imputation using PROC MI for missing categorical and continuous data. Do I need to dummy code my categorical predictors before using them in FCS regression? If, for example, I want to impute continuous variable 'weight' using categorical variable 'income' (low, medium high). When undertaking regular lineair regression it's not possible to use categorical predictors, but PROC MI does have a class statement, so that's why I am confused.
proc mi data=lib.test nimpute=5 seed=54321 out=mi class income; var bloodpressure income age weight height; fcs discrim (income = bloodpressure income age weight height / classeffects=include) nbiter =20 ; fcs reg (weight = bloodpressure income age height) nbiter =20 ; run;
No, it is not necessary to use dummy variables. The CLASS statement will do that automatically (using effects coding) for the FCS
No, it is not necessary to use dummy variables. The CLASS statement will do that automatically (using effects coding) for the FCS
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