sep.rb.hypergeo: Hypergeometric risk-based population sensitivity

In RSurveillance: Design and Analysis of Disease Surveillance Activities

Description

Calculates risk-based population sensitivity with a single risk factor, using the hypergeometric method (assuming a finite and known population size), allows for unit sensitivity to vary among risk strata

Usage

sep.rb.hypergeo(pstar, rr, N, n, se)

Arguments

pstar	design prevalence (scalar)
rr	relative risk values (vector of values corresponding to the number of risk strata)
N	Population size per risk category (vector same length as rr and ppr)
n	sample size per risk category (vector same length as rr and ppr)
se	unit sensitivity, can vary among risk strata (fixed value or a vector the same length as rr, ppr, n)

Value

list of 3 elements, a scalar of population-level sensitivity a vector of EPI values and a vector of corresponding adjusted risks

Examples

# examples for sep.rb.bin
sep.rb.hypergeo(0.1, c(5, 3, 1), c(10, 10, 80), c(5, 5, 5), 0.9)
sep.rb.hypergeo(0.1, c(5, 1), c(15, 140), c(10, 5), c(0.95, 0.9))
sep.rb.hypergeo(0.1, c(5, 1), c(23, 180), c(10, 5), c(0.9, 0.9))
sep.rb.hypergeo(0.01, c(5, 1), c(100, 900), c(90, 50), c(0.9, 0.9))

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