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;
run;
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.
Thanks.
You can use the estimate statement or the odds ratio statement.
Here's an example of the estimate statement:
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';
GPA was continuous.
You usually look for the estimate at the mean of the value but that depends on what you're looking for.
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