I am trying to assess sample size via bootstrap analysis. The goal is to compare the outcome of an intervention in a group of patients, to a known (good) outcome of x%. I want to test if the new intervention would perform better or equal to the old intervention. Sp basically I have a one sample comparison to known proportion, non-inferiority analysis. lets say the non-inferiority margin is 3% and given the resources I can only apply the new intervention on 25-50 patients.

I am assuming the best way to do this is to get the results of the intervention on maximum possible between 25-50 and then get an estimate of the outcome via bootstrap resampling and see if the lower limit of bs based 95% CI is higher than the (x-3)% .
a) would this be correct approach
b) is there an optimal sample size for this bs analysis and how do iI estimate in STATA
c) if I was not limited by resources then how do I estimate sample size for a one-sample non-inferior comparison of mean/proportion to a known or standard mean/proportion. I there a stata code for that.

Thanks
Ashar