sep.binom {RSurveillance} | R Documentation |
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
# 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)
[Package RSurveillance version 0.2.1 Index]