Here is the code I used to generate the imputed dataset:
proc surveyimpute data=zinc.otms method=hotdeck (selection=weighted) seed=123 ndonors=5;
cluster psu_no_ov;
strata newstrata;
weight nat_weight_bio;
cells sex area;
class cat_smoke sanitation handwashing drinkingwatersource caste alcohol_y_n edu_pat edu_mat;
var cat_smoke sanitation handwashing drinkingwatersource caste alcohol_y_n edu_pat edu_mat N_Mets1 N_Mets2 N_Mets3 N_Mets4 N_Mets5 N_Mets6 N_Mets7 crprt diet p_activity zns_unic sys1 sys2 sys3 dias1 dias2 dias3;
output out=zinc.imputed donorid=donor;
run;
data zinc.imputed;
set zinc.imputed;
if (ImpIndex = 0) then do; /* Include complete respondents */
do _Imputation_=1 to 5; /* in all imputations. */
output;
end;
end;
else do; /* Put incomplete respondents */
_Imputation_ = ImpIndex; /* in separate imputations. */
output;
end;
proc sort data=zinc.imputed;
by _Imputation_ UnitID;
run;
then I ran the following regression using the default varmethod=TSL:
proc surveyreg data=zinc.imputed;
by _imputation;
cluster psu_no_ov;
strata newstrata;
weight imp_wt;
class cat_zinc;
model N_Mets8 = cat_zinc / solution noint;
contrast 'contrasting example' cat_zinc -3 -1 1 3;
estimate 'overall mean' cat_zinc 0.25 0.25 0.25 0.25;
run;
Now, should I combine the results using PROC miANALYZE? OR Should I remove the by _imputation_ statement from the Proc surveyeg step and report the results without using procmianalyze?
