During a study testing a new screening tool for a chronic disease, an individual is screened for the disease and the test comes back negative; however, in reality, the person does have the disease. The initial screening test is an example of a:
If the test result comes out to be negative for a condition that is actually existing in reality, then such a test result is said to be false negative.
This means when the negative test result is incorrect, it can be called as a false negative.
Thus, the result would have been correct if the result would have come out to be positive.
In statistics false negative is considered as a type II error in which a test is conducted to check for a single condition and the result comes out to be negative even when the condition exists.
In the given situation, the person has a chronic disease but the screening test shows that the person does not have the disease and hence, this is an example of false negative.
