Sensitivity and Specificity calculation
Arguments
- sensitivity
Numeric. P(+|P), the probability of a positive test result given that the result is truly positive.
- specificity
Numeric. P(-|N), the probability of a negative test result given that the result is truly negative.
- prevalence
Numeric. P(P), the probability of truly positive results in the population.
- TP
Integer. True positive count.
- TN
Integer. True negative count.
- FP
Integer. False positive count.
- FN
Integer. False negative count.
Examples
post = prob_input(sensitivity=.9, specificity=.97, prevalence=.008)
post
#> P(P|+) P(N|+) P(N|-) P(P|-)
#> 0.1948051948 0.8051948052 0.9991692972 0.0008307028
# Assume there are 2957 positive cases and 77043 negative cases.
# The code below computes TP, FP, TN, FN
counts = post * c(2957, 2957, 77043, 77043)
counts
#> P(P|+) P(N|+) P(N|-) P(P|-)
#> 576.03896 2380.96104 76979.00017 63.99983
confusion_input(TP=576, FP=2381, TN=76979, FN=64)
#> N prevalence sensitivity specificity
#> 8.000000e+04 8.000000e-03 9.000000e-01 9.699975e-01