sep.binom: Binomial Population sensitivity

In RSurveillance: Design and Analysis of Disease Surveillance Activities

Description

Calculates population sensitivity for detecting disease, assuming imperfect test sensitivity and specificity and representative sampling, using binomial distribution (assumes large or unknown population size and that cut-point number of reactors for a positive result = 1)

Usage

sep.binom(n, pstar, se = 1, sp = 1, dig = 5)

Arguments

n	sample size = number of units tested (integer), scalar or vector
pstar	design prevalence as a proportion (scalar or vector of same length as n)
se	unit sensitivity of test (proportion), default = 1 (scalar or vector of same length as n)
sp	unit specificity of test (proportion), default = 1 (scalar or vector of same length as n)
dig	number of digits for rounding of results

Value

vector of population-level sensitivities

Examples

# examples for sep.binom - checked
sep.binom(n=300, pstar = 0.02, se = 0.92)
tested<- seq(10,100, by=10)
prev<- 0.05
sens<- 0.9
sep.binom(tested, prev, sens)

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