sep.freecalc {RSurveillance} | R Documentation |
FreeCalc population sensitivity for imperfect test
Description
Calculates population sensitivity for a finite population and allowing for imperfect test sensitivity and specificity, using Freecalc method
Usage
sep.freecalc(N, n, c = 1, se, sp = 1, pstar)
Arguments
N |
population size (scalar) |
n |
sample size (scalar) |
c |
The cut-point number of positives to classify a cluster as positive, default=1, if positives < c result is negative, >= c is positive (scalar) |
se |
test unit sensitivity (scalar) |
sp |
test unit specificity, default=1 (scalar) |
pstar |
design prevalence as a proportion - assumed or target prevalence for detection of disease in the population (scalar) |
Value
population-level sensitivity
Examples
# examples of sep.freecalc
sep.freecalc(150, 30, 2, 0.9, 0.98, 0.1)
sep.freecalc(150, 30, 1, 0.9, 0.98, 0.1)
[Package RSurveillance version 0.2.1 Index]