Learn R Programming

epiR (version 2.0.68)

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)

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.

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.

Examples

Run this code
## 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, 4 from the medium risk area and 3 from 
## the low risk area.   

Run the code above in your browser using DataLab