n.freedom {RSurveillance} | R Documentation |
Freedom sample size
Description
Calculates sample size for demonstrating freedom or detecting disease using the appropriate method, depending on whether or not N provided (hypergeometric if N provided, binomial otherwise), assuming imperfect test sensitivity, perfect test specificity and representative sampling
Usage
n.freedom(N = NA, sep = 0.95, pstar, se = 1)
Arguments
N |
population size, default = NA (unknown) (scalar or vector of same length as sep) |
sep |
desired population sensitivity (scalar or vector) |
pstar |
specified design prevalence as proportion or integer (scalar or vector of same length as sep) |
se |
unit sensitivity (scalar or vector of same length as sep) |
Value
vector of sample sizes, NA if N is specified and n>N
Examples
# examples for n.freedom - checked
n.freedom(NA, sep=0.95, pstar=0.01, se=1)
n.freedom(500, sep=0.95, pstar=0.01, se=1)
n.freedom(N=c(100, 500, 1000, 5000, 10000, 100000, NA), sep=0.95, pstar=0.01, se=1)
n.freedom(500, sep=0.95, pstar=0.01, se=c(0.5, 0.6, 0.7, 0.8, 0.9, 0.99, 1))
[Package RSurveillance version 0.2.1 Index]