BookmarkSubscribeRSS Feed
🔒 This topic is solved and locked. Need further help from the community? Please sign in and ask a new question.
ccoman
Calcite | Level 5

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;
1 ACCEPTED SOLUTION

Accepted Solutions
SAS_Rob
SAS Employee

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

View solution in original post

1 REPLY 1
SAS_Rob
SAS Employee

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

sas-innovate-white.png

Special offer for SAS Communities members

Save $250 on SAS Innovate and get a free advance copy of the new SAS For Dummies book! Use the code "SASforDummies" to register. Don't miss out, May 6-9, in Orlando, Florida.

 

View the full agenda.

Register now!

What is ANOVA?

ANOVA, or Analysis Of Variance, is used to compare the averages or means of two or more populations to better understand how they differ. Watch this tutorial for more.

Find more tutorials on the SAS Users YouTube channel.

Discussion stats
  • 1 reply
  • 719 views
  • 1 like
  • 2 in conversation