In statistics, discrimination is the ability of a prediction (judgment scheme, statistical model, etc.) to distinguish between events and nonevents (or cases from controls, successes from failures, disease from nondisease, etc.). In the simplest form, a prediction scheme focuses on a single event with two possible states and assigns some estimate of the chance that one state will occur. This prediction comes from the set of cues and other factors, both measurable and immeasurable, available to the researcher.

Whether it is meteorologists forecasting the weather, business analysts predicting the rise and fall of the stock market, bookmakers predicting the big game, or physicians diagnosing disease, predictions have some degree of “correctness” relative to the actual occurrence of some unknown or future event. In medicine, we commonly ...