Dear Allstaters,
I am a little bit puzzled about something and I was wondering if someone had
any suggestion related to this…
I have the concentration results of an assay which clinicians would like to
use in order to discriminate between subjects of CAD (Coronary Arterial
Disease) and subjects of no CAD.
The CAD group has 109 subjects and the no-CAD 53.
I try to perform logistic regression modelling for the probability of a
subject having CAD. However, the results are a little bit confusing.
Although, the model fits the data well and the p-value of the estimate of
the assay was highly significant (<0.001), the odds ratio of it came out to
be 1.004(1.002, 1.006)!!!
Therefore, I got confused.
Then, I implemented a ROC plot which gave me really nice plot of AUC of
0.895 (the two groups were found to have significantly different means with
the CAD group having bigger mean concentration than the no-CAD).
Then I thought that maybe it was the different group sizes (53 non-CAD
versus 109 CAD). I generated some data so that the group’s size would be
quite similar (106 non-Cad versus 109 CAD this time.) Again, the estimate of
the assay was found to be significant (P<0.001) but the odds ratio
1.004(1.003, 1.005).
I am thinking that these strange results could be due to the very high range
of concentrations I have to deal with, (47µg/ml-10307.40µg/ml).
Anybody has any suggestion..?
Ioanna
_________________________________________________________________
It's fast, it's easy and it's free. Get MSN Messenger today!
http://www.msn.co.uk/messenger
|