sep.pooled: Pooled population sensitivity

In RSurveillance: Design and Analysis of Disease Surveillance Activities

Description

Calculates population sensitivity (sep) and population specificity (spp) assuming pooled sampling and allowing for imperfect sensitivity and specificity of the pooled test

Usage

sep.pooled(r, k, pstar, pse, psp = 1)

Arguments

r	number of pools sampled (scalar or vector)
k	pool size (scalar or vector of same length as r)
pstar	design prevalence (scalar or vector of same length as r)
pse	pool-level sensitivity (scalar or vector of same length as r)
psp	pool-level specificity (scalar or vector of same length as r)

Value

list of 2 elements, vector of sep values and vector of spp values

Examples

# examples for sep.pooled
sep.pooled(60, 5, 0.01, 1, 1)
sep.pooled(4, 10, 0.1, 0.9, 1)
sep.pooled(1:10*5, 5, 0.02, 0.9, 0.99)
sep.pooled(10, 5, 0.05, c(0.8, 0.9, 0.95, 0.99), 1)

Example output

$sep
[1] 0.9509591

$spp
[1] 1

$sep
[1] 0.9706771

$spp
[1] 1

$sep
 [1] 0.3946345 0.6335326 0.7781533 0.8657016 0.9187004 0.9507840 0.9702064
 [8] 0.9819640 0.9890816 0.9933904

$spp
 [1] 0.9509900 0.9043821 0.8600584 0.8179069 0.7778214 0.7397004 0.7034477
 [8] 0.6689718 0.6361855 0.6050061

$sep
[1] 0.8641780 0.8973573 0.9110379 0.9207757

$spp
[1] 1

RSurveillance documentation built on July 2, 2020, 2:33 a.m.