I was wondering if anyone could help point me in the right direction with a problem I'm having with the MIAnalyze procedure. I created a multiple imputations data set with 5 imputations and now would like to combine the results using MIAnalyze. I first ran a proc logistic with a class statement (as all my covariates are categorical) and then ran the MIanalyze procedure. I keep getting an error message that "the variable cat_matchage is not in the covb= data set." I think the reason is that the new data set now has broken down cat_matchage into the various levels (i.e. cat_matchage1, cat_matchage2, etc.). Code below:
class
infection (PARAM=REF REF='0')
cat_matchage(PARAM=REF REF='1')
mrace(PARAM=REF REF='White Non Hispanic')
meduc (PARAM=REF REF='<High School')
fincome(PARAM=REF REF='<$35,000')
msmokmo(PARAM=REF REF='NA')
momAgeBirth(PARAM=REF REF='<25');
model uni_regout(event="1")= infection cat_matchage mrace fincome meduc msmokmo momagebirth/ covb;
by _imputation_;
format meduc feduc educationnewf. fincome mincome incomenewf.;
where reachdata=2;
ods output parameterestimates=MI.infection covB=MI.covbinfection;
run;
modeleffects intercept cat_matchage mrace meduc fincome msmokmo momAgeBirth;
run;
Any guidance would be much appreciated thanks!
It seems to me that this situation comes up on a fairly regular basis, and it has to do with the structure of the covb matrix, especially with CLASS variables. I think an answer was presented, but basically MIANALYZE does not play well with covariance matrices with categorical values. I think an answer from Tech Support made its way on here about six months ago, but I cannot google it out today. So, I would recommend opening a ticket with Tech Support, and when a satisfactory result is obtained, please post it back here.
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