n.pfree {RSurveillance} | R Documentation |
Sample size to achieve desired (posterior) probability of freedom
Description
Calculates the sample size required to achieve a given value for probability of disease freedom
Usage
n.pfree(pfree, prior, p.intro, pstar, se, N = NA)
Arguments
pfree |
desired probability of freedom (scalar or vector) |
prior |
prior probability of freedom before surveillance (scalar or vector of same length as pfree) |
p.intro |
probability of introduction for time period (scalar or vector of same length as pfree) |
pstar |
design prevalence (scalar or vector of same length as pfree) |
se |
unit sensitivity (scalar or vector of same length as pfree) |
N |
population size (scalar or vector of same length as pfree) |
Value
a list of 3 elements, the first a vector of sample sizes and the second a corresponding vector of population sensitivity values and the third a vector of adjusted priors
Examples
# examples for n.pfree
n.pfree(0.95, 0.5, 0.01, 0.05, 0.9)
n.pfree(0.95, 0.5, 0.01, 0.05, 0.9, N=300)
n.pfree(pfree = c(0.9, 0.95, 0.98, 0.99), prior = 0.7, 0.01, 0.01, 0.8, 1000)
n.pfree(0.95, 0.7, 0.01, 0.1, 0.96)
[Package RSurveillance version 0.2.1 Index]