Hypergeometric (HerdPlus) population sensitivity for imperfect test

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Description

Calculates population sensitivity for a finite population and allowing for imperfect test sensitivity and specificity, using Hypergeometric distribution

Usage

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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

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# 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)

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