sep.freecalc: FreeCalc population sensitivity for imperfect test

Description Usage Arguments Value Examples

View source: R/freedom_functions_2.R

Description

Calculates population sensitivity for a finite population and allowing for imperfect test sensitivity and specificity, using Freecalc method

Usage

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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

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# 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)

RSurveillance documentation built on July 2, 2020, 2:33 a.m.