Specificity is defined as

Specificity is defined as

• A. Sensitivity = TP / (TP + FN)
• B. PPV = TP / (TP + FP)
• C. Specificity = TN / (TN + FP)
• D. NPV = TN / (TN + FN)

Answer: (C)

Specificity is the measure of how well a test identifies people who do not have the disease. It is defined as the number of true negatives divided by the sum of true negatives and false positives. In other words, among those who are disease-free, what proportion does the test correctly label as negative? A high specificity means few false positives, so a positive result from such a test strongly supports the presence of disease (useful for ruling in disease). The other metrics describe different ideas: sensitivity looks at true positives among those with disease; positive predictive value tracks the probability that a positive test really means disease; negative predictive value tracks the probability that a negative test really means no disease.

Specificity is the measure of how well a test identifies people who do not have the disease. It is defined as the number of true negatives divided by the sum of true negatives and false positives. In other words, among those who are disease-free, what proportion does the test correctly label as negative? A high specificity means few false positives, so a positive result from such a test strongly supports the presence of disease (useful for ruling in disease). The other metrics describe different ideas: sensitivity looks at true positives among those with disease; positive predictive value tracks the probability that a positive test really means disease; negative predictive value tracks the probability that a negative test really means no disease.