Proc MI FCS regression dummy coding

ccoman — Tue, 07 Jul 2020 14:54:41 GMT

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;

Re: Proc MI FCS regression dummy coding

SAS_Rob — Tue, 07 Jul 2020 15:29:43 GMT

No, it is not necessary to use dummy variables. The CLASS statement will do that automatically (using effects coding) for the FCS

topic Re: Proc MI FCS regression dummy coding in Statistical Procedures

Proc MI FCS regression dummy coding

Re: Proc MI FCS regression dummy coding