False Negative

This type of error involves the acceptance of the null hypothesis when it is actually false; in other words, it represents a failure to detect a real effect. It is also known as a Type II error or β error. These errors are particularly common in studies with relatively small sample sizes. In medicine, false-negative findings are cases in which a test fails to detect a condition when it is actually present. This is often studied within the framework of receiver operating characteristics (ROC) curves, which graphically represent the trade-off between false-negative and false-positive findings for a particular test or set of tests.