rsu.sssep.rspool {epiR}

Sample size to achieve a desired surveillance system sensitivity using pooled samples assuming representative sampling

Description

Calculates the required sample size to achieve a desired surveilance system sensitivity assuming representative sampling, imperfect pooled test sensitivity and imperfect pooled test specificity.

Usage

rsu.sssep.rspool(k, pstar, pse, psp, se.p)

Arguments

k

scalar or vector of the same length as sep representing the number of individual units that contribute to each pool (i.e., the pool size).

pstar

scalar or vector of the same length as se.p representing the design prevalence.

pse

scalar or vector of the same length as se.p representing the pool-level sensitivity.

psp

scalar or vector of the same length as se.p representing the pool-level specificity.

se.p

scalar or vector (0 to 1) representing the desired surveillance system (population-level) sensitivity.

Value

A vector of required sample sizes.

References

Christensen J, Gardner I (2000). Herd-level interpretation of test results for epidemiologic studies of animal diseases. Preventive Veterinary Medicine 45: 83 - 106.

Examples

## EXAMPLE 1:
## To confirm your country's disease freedom status you intend to use a test 
## applied at the herd level. The test is expensive so you decide to pool the 
## samples taken from individual herds. How many pooled samples of size 5 are 
## required to be 95% confident that you will have detected disease if 
## 1% of herds are disease-positive? Assume a diagnostic sensitivity and 
## specificity of 0.90 and 0.95 for the pooled testing regime. 

rsu.sssep.rspool(k = 5, pstar = 0.01, pse = 0.90, psp = 0.95, se.p = 0.95)

## A total of 32 pools (each comprised a samples from 5 herds) need to be 
## tested.