Hmmm, thanks. The EFFECTPLOT statement is powerful. However, I don't understand one thing.
proc logistic data=d202ps_3;
class obesity_status(REF='0') genderC(REF='0') AF(REF='0') Hypertension(REF='0') CHF(REF='0') akiC(ref='0') ddiC(REF='0') indicationC(REF='0') CYP2C9code(REF='0') VKORC1Code(REF='0');
model firstInrAttain(event='1') = obesity_status Weight__kg_ ageY genderC AF Hypertension CHF serumAlb akiC ddiC indicationC CYP2C9code VKORC1Code / clodds=both clparm=both;
effectplot slicefit(x=ageY sliceby=obesity_status=0 1 2) / clm noobs;
run;
and
proc logistic data=d202ps_3;
class /*obesity_status(REF='0')*/ genderC(REF='0') AF(REF='0') Hypertension(REF='0') CHF(REF='0') akiC(ref='0') ddiC(REF='0') indicationC(REF='0') CYP2C9code(REF='0') VKORC1Code(REF='0');
model firstInrAttain(event='1') = obesity_status Weight__kg_ ageY genderC AF Hypertension CHF serumAlb akiC ddiC indicationC CYP2C9code VKORC1Code / clodds=both clparm=both;
effectplot slicefit(x=ageY sliceby=obesity_status=0 1 2) / clm noobs;
run;
The two produced obviously different graphs. The only difference in the code is whether obesity_status was listed as class/category variable. Also, if I treat obesity_status as a class variable, I cannot define its levels in the EFFECTPLOT analysis (i.e., it has 4 levels but I prefer to use only three levels.) Thanks.
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