epiR: rsu.sssep.rbsrg – R documentation

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rsu.sssep.rbsrg

Sample size to achieve a desired surveillance system sensitivity assuming risk-based sampling and a single sensitivity value for each risk group

Description

Sample the size to achieve a desired population sensitivity assuming risk-based sampling, a single sensitivity value for each risk group and perfect test specificity.

Usage

rsu.sssep.rbsrg(pstar, rr, ppr, spr, se.p, se.u)

Arguments

`pstar`	scalar, representing the design prevalence.
`rr`	vector, defining the relative risk values for each strata in the population.
`ppr`	vector of length `rr`, defining the population proportions in each strata.
`spr`	vector of length `rr` representing the planned surveillance proportion for each strata in the population.
`se.p`	scalar (0 to 1) representing the desired surveillance system (population-level) sensitivity.
`se.u`	scalar (0 to 1) or vector of the same lengthe as `rr` representing the sensitivity of the diagnostic test applied at the unit level.

Value

A list of comprised of four elements:

`n`	a vector listing the required sample sizes for each (risk) strata.
`total`	scalar, representing the total sample size.
`epinf`	a vector listing the effective probability of infection estimates.
`adj.risk`	a vector listing the adjusted risk estimates.

Examples

## EXAMPLE 1:
## A cross-sectional study is to be carried out to confirm the absence of 
## disease using risk based sampling. Assume a population level design 
## prevalence of 0.10 and there are 'high', 'medium' and 'low' risk areas  
## where the risk of disease in the high risk area compared with the low risk 
## area is 5 and the risk of disease in the medium risk area compared with 
## the low risk area is 3. The proportions of the population at risk in the 
## high, medium and low risk area are 0.10, 0.10 and 0.80, respectively.
## Half of your samples will be taken from individuals in the high risk area,
# 0.30 from the medium risk area and 0.20 from the low risk area. You intend 
## to use a test with diagnostic sensitivity of 0.90 and you'd like to take 
## sufficient samples to return a population sensitivity of 0.95. How many 
## units need to be sampled to meet the requirements of the study?

rsu.sssep.rbsrg(pstar = 0.10, rr = c(5,3,1), ppr = c(0.10,0.10,0.80), 
   spr = c(0.50,0.30,0.20), se.p = 0.95, se.u = 0.90)

## A total of 14 units needs to be sampled to meet the requirements of the 
## study: 7 from the high risk area, 5 from the medium risk area and 2 from 
## the low risk area.

epiR

Tools for the Analysis of Epidemiological Data

v2.0.19

GPL (>= 2)

Authors

Mark Stevenson <mark.stevenson1@unimelb.edu.au> and Evan Sergeant <evansergeant@gmail.com> with contributions from Telmo Nunes, Cord Heuer, Jonathon Marshall, Javier Sanchez, Ron Thornton, Jeno Reiczigel, Jim Robison-Cox, Paola Sebastiani, Peter Solymos, Kazuki Yoshida, Geoff Jones, Sarah Pirikahu, Simon Firestone, Ryan Kyle, Johann Popp, Mathew Jay and Charles Reynard.

Initial release

2021-01-12