RSurveillance (version 0.2.1)

sep.binom: Binomial Population sensitivity

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

# NOT RUN {
# 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)
# }