Hi
I am trying to make a simple logistic regression adjusted for one potential confounder ("Antibtiotics") on a small sample size (n=13).
All variables are binary. I need to adjust for one potential confounder; whether or not the person took ("Antibiotics").

I am "investigating" whether a bloo-value above/below a givet cut-off affects outcome, when adjusting for Antibiotics (yes/no).


My code:
logit Outcome i.Bloodvalue i.Antibiotics, or

The output:
Logistic regression Number of obs = 13
LR chi2(1) = 2.22
Prob > chi2 = 0.1361
Log likelihood = -6.9135667 Pseudo R2 = 0.1384

----------------------------------------------------------------------------------------------------------------------------------------------------
Outcome | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval]
---------------------------+-----------------------------------------------------------------------------------------------------------------------
1.Bloodvalue | 1 (empty)
1.Antibiotics | .125 .1822172 -1.43 0.154 .0071793 2.176401
_cons | 2 2.44949 0.57 0.571 .1813532 22.0564




I am aware that an adjusted regression of such a small sample size is problematic, but my question is:
- Why can't I get Stata to compute the Odss Ratio, Standard Error, P-value and CI for the bloodvalue
- All people with a value above the blood-value (n=3) cut-off experienced "Outcome", is that the problem? It worked fine with Fishers Exact Test

Stata IC 15.1

Kind Regards
Rasmus