Which formula correctly defines specificity?

Which formula correctly defines specificity?

• A. True positives / (true positives + false positives).
• B. True negatives / (true negatives + false positives).
• C. False positives / (false positives + true negatives).
• D. True negatives / (true negatives + false negatives).

Answer: (B)

Specificity is the proportion of people without the condition who are correctly identified as negative by the test. It is calculated as true negatives divided by all people who do not have the condition (true negatives plus false positives). So the correct formula is true negatives divided by the sum of true negatives and false positives. A high specificity means the test yields few false positives. For context, the other formulas correspond to different measures: one uses true positives in the numerator, which is precision/positive predictive value; another uses false positives in the numerator, which is the false positive rate; another uses true negatives over (true negatives plus false negatives), which is the negative predictive value.

Specificity is the proportion of people without the condition who are correctly identified as negative by the test. It is calculated as true negatives divided by all people who do not have the condition (true negatives plus false positives). So the correct formula is true negatives divided by the sum of true negatives and false positives. A high specificity means the test yields few false positives.

For context, the other formulas correspond to different measures: one uses true positives in the numerator, which is precision/positive predictive value; another uses false positives in the numerator, which is the false positive rate; another uses true negatives over (true negatives plus false negatives), which is the negative predictive value.