06-27-2014 02:54 PM
I have a a data set where the dependent variable has 4 levels (low, low-medium, medium, and high) with three independent continuous variables.
So my code currently looks like this:
proc logistic data=updated;
model groupedSet = bioMarker age bmi;
the output gives me 3 intercepts, which is great, but only gives me 1 estimate and odds ratio estimate for the bioMarker, age, and bmi. Is there a way to see what the predicted probability is for the bioMarker at each level of the groupedSet? I understand the main problem is because it is a continuous variable. So is there any way around that? I've been trying to find some papers on it but am have bad luck so far.
06-27-2014 02:58 PM
You can use the estimate statement or the odds ratio statement.
Here's an example of the estimate statement:
06-27-2014 03:26 PM
Thank you for the link Reeza,
In the example they have the 'paired' variable either be 0 or 1 (a categorical variable). Mine, however, is continuous. Should I just pick the cutoff points as the same as the cutoff points for the dependent variable or just leave it as it is? Also if I wanted to standardize for age and bmi in this estimate would I set this to be 0 or 1?
something like this?
estimate "pr prb groupedSet = 1" intercept 1 bioMarker 1 age 1 bmi 1 \ ilink category = '1';
estimate "pr prb groupedSet = 2" intercept 1 bioMarker 1 age 1 bmi 1 \ ilink category = '2';
estimate "pr prb groupedSet = 3" intercept 1 bioMarker 1 age 1 bmi 1 \ ilink category = '3';