Even if Dr. Sonis’s suggestion of appropriate versus nonappropriate analyses were applicable, we would also like to take issue with his suggestion from a statistical viewpoint. There are two main points here. First, when looking at confounders, Dr. Sonis suggests that it is not the statistical significance of the confounder that matters, but its effect size. This is a potentially dangerous suggestion since random noise can strongly influence the size of an odds ratio, especially in small samples, when base rates are low, or when there are multiple variables involved. In the best of worlds with 40 subjects and just two binary predictors, both at 50:50, there are only 10 subjects in a cell. Not so long ago, statisticians looked at how random fluctuations affect outcomes in such situations and developed the significance test to tell if a particular result was likely a chance variation. Certainly, the size of an odds ratio should be considered, but there should be reasonable assurance that we are not looking at noise.