My way of remembering formulas for specificity and sensitivity is that sPecificity has false Positive in it and seNsitivity has false Negative. Then the other variable is the opposite.

So the formula for sPecificity = true negative / (false Positive + true negative)

• In this case, the true negative (tested negative and are actually normal) = 113
• False positive (tested positive but are actually normal) = 1

Specificity = (113) / (113+1) = 113/114 = 0.99123 = 99.123%

NOTE: Negative and positive predictive value have the name of the variables used in them!

• Negative predictive value = true negative / (true negative + false negative)
• Positive predictive value = true positive / (true positive + false positive)

FA2020 p257