rsu.sssep.rspool {epiR} R Documentation

## 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 `sep` representing the design prevalence. `pse` scalar or vector of the same length as `sep` representing the pool-level sensitivity. `psp` scalar or vector of the same length as `sep` 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.
```

[Package epiR version 2.0.38 Index]