sep.hp {RSurveillance} | R Documentation |
Hypergeometric (HerdPlus) population sensitivity for imperfect test
Description
Calculates population sensitivity for a finite population and allowing for imperfect test sensitivity and specificity, using Hypergeometric distribution
Usage
sep.hp(N, n, c = 1, se, sp = 1, pstar)
Arguments
N |
population size (scalar or vector of same length as n) |
n |
sample size (scalar or vector) |
c |
The cut-point number of positives to classify a cluster as positive, default=1, if positives < c result is negative, >= c is positive (scalar) |
se |
test unit sensitivity (scalar) |
sp |
test unit specificity, default=1 (scalar) |
pstar |
design prevalence as a proportion (scalar) |
Value
a vector of population-level sensitivities
Examples
# examples of sep.hp
sep.hp(150, 1:5*10, 2, 0.9, 0.98, 0.1)
sep.hp(150, 30, 2, 0.9, 0.98, 15)
sep.hp(150, 30, 1, 0.9, 0.98, 15)
sep.hp(150, 30, 1, 0.9, 0.98, 0.1)
[Package RSurveillance version 0.2.1 Index]