Final answer:
The negative predictive value of a test measures the probability that a person who tests negative for a disease or condition is truly not affected by the disease or condition. It helps assess the reliability of a negative test result.
Step-by-step explanation:
The negative predictive value of a test measures the probability that a person who tests negative for a disease or condition is truly not affected by the disease or condition. It helps assess the reliability of a negative test result. The negative predictive value can be calculated using the formula: NPV = TN / (TN + FN), where TN represents true negatives and FN represents false negatives.
The negative predictive value is interpreted as the percentage or probability of a negative test result correctly excluding the presence of a disease or condition in the tested individual. In other words, a higher negative predictive value indicates a greater certainty that an individual who tests negative is actually disease-free. However, it's important to consider other factors such as the test's sensitivity and specificity when interpreting the negative predictive value.