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Hi,
I need help in interpreting multinomial logistic regression. Please find attached my SAS output.
Exposure pills is number of pills prescribed which is continuous.
Outcome pillsconsumed is pills consumed in categories. It is divided in three categories:
0: no pills consumed,
1: 1-10 pills consumed
2: 10+ pills consumed
My code is
proc logistic data=new;
class pillsconsumed (ref = "0") /param=reference;
model pillsconsumed = pills / link = glogit;
run;
Thanks a lot in advance.
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An increase of 1 pill prescribed is associated with a 1.033 fold increased odds of consuming 1-10 pills compared with no pills.
An increase of 1 pill prescribed is associated with a 1.053 fold increased odds of consuming 10+ pills compared with no pills.
But this analysis seems a bit odd practically speaking. Maybe agreement (ie, kappa)?
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An increase of 1 pill prescribed is associated with a 1.033 fold increased odds of consuming 1-10 pills compared with no pills.
An increase of 1 pill prescribed is associated with a 1.053 fold increased odds of consuming 10+ pills compared with no pills.
But this analysis seems a bit odd practically speaking. Maybe agreement (ie, kappa)?
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Thank you very much! Our dataset has pills consumed in categories and not continuous that is why we had to analyze this way.
thanks