Error Asymmetry: How FDA Decides Which Mistakes Matter More
Most statistical frameworks treat errors symmetrically. A false positive is bad. A false negative is bad. Control one, tolerate the other, and let the math do the rest. Clinical reality is not that tidy. Approving an ineffective therapy and withholding a potentially effective one are both errors, but they do