Hello, I have a question related to the topic of multiple imputation. I am hoping that you can help me out. I am trying to impute missing values in a dataset that has mostly categorical variables (binary, ordinal or nominal) and one continuous variable (age). I am using the discriminant FCS method for missing categorical variables (total 😎 and regpmm for one missing age (1). The other variables have no missing value. I am doing this in SAS 9.4 (SAS/Stat 14.1) and only set imputation number as 1, I tried to get the imputed data set quickly. This below code can be run without error information, however, it can't give me the final imputed data set, even after 1 day run. Did I include too many missing variables (total 9) in this model? Why it runs but no output after long time waiting, even I just set nimpute=1? What further model modification I can do to get final imputed data set? Thanks. Here is the example code I used: proc mi data=OUTPT.analysis MU0=35 minimum=0 maximum=108 round=1 nimpute=1 out=OUTPT.imputed; class SEX_C RACETH_C D_C P_C I_C BD_C DI_C LO_C TY_C IN_C FM_C PS_C ST_C SP_C SC_C PR_C HO_C; fcs regpmm(AGEYR_N/details); fcs discrim(RACETH_C/details classeffects=include); fcs discrim(SEX_C/details classeffects=include); fcs discrim(P_C/details classeffects=include); fcs discrim(I_C/details classeffects=include); fcs discrim(BD_C/details classeffects=include); fcs discrim(DI_C/details classeffects=include); fcs discrim(LO_C/details classeffects=include); fcs discrim(TY_C/details classeffects=include); var AGEYR_N SEX_C RACETH_C D_C P_C I_C BD_C DI_C LO_C TY_C IN_C FM_C PS_C ST_C SP_C SC_C PR_C HO_C TRE_N; run;
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