<Tr> <Td_colspan="2"> </Td> <Td> Sensitivity = TP / (TP + FN) = 20 / (20 + 10) ≈ 67% </Td> <Td> Specificity = TN / (FP + TN) = 1820 / (180 + 1820) = 91% </Td> </Tr> <Ul> <Li> False positive rate (α) = type I error = 1 − specificity = FP / (FP + TN) = 180 / (180 + 1820) = 9% </Li> <Li> False negative rate (β) = type II error = 1 − sensitivity = FN / (TP + FN) = 10 / (20 + 10) = 33% </Li> <Li> Power = sensitivity = 1 − β </Li> <Li> Likelihood ratio positive = sensitivity / (1 − specificity) = 0.67 / (1 − 0.91) = 7.4 </Li> <Li> Likelihood ratio negative = (1 − sensitivity) / specificity = (1 − 0.67) / 0.91 = 0.37 </Li> </Ul> <Li> False positive rate (α) = type I error = 1 − specificity = FP / (FP + TN) = 180 / (180 + 1820) = 9% </Li> <Li> False negative rate (β) = type II error = 1 − sensitivity = FN / (TP + FN) = 10 / (20 + 10) = 33% </Li>

How to calculate false positive rate from sensitivity and specificity