accuracy.dorf {binGroup} | R Documentation |

## Accuracy measures for informative Dorfman testing

### Description

Calculate the accuracy measures for each individual in a pool used with informative Dorfman testing.

### Usage

```
accuracy.dorf(p, se, sp)
```

### Arguments

`p` |
a vector of each individual's probability of infection. |

`se` |
the sensitivity of the diagnostic test. |

`sp` |
the specificity of the diagnostic test. |

### Details

This function calculates the pooling sensitivity, pooling specificity, pooling positive predictive value, and pooling negative predictive value for each individual belonging to a pool of size greater than or equal to one used with informative Dorfman testing. Calculations of these measures are done using the equations presented in McMahan et al. (2012).

### Value

a list containing:

`PSe` |
a vector containing each individual's pooling sensitivity. |

`PSp` |
a vector containing each individual's pooling specificity. |

`PPV` |
a vector containing each individual's pooling positive predictive value. |

`NPV` |
a vector containing each individual's pooling negative predictive value. |

### Author(s)

This function was originally written by Christopher S. McMahan for McMahan et al. (2012). The function was obtained from http://chrisbilder.com/grouptesting.

### References

McMahan, C., Tebbs, J., Bilder, C. (2012).
“Informative Dorfman Screening.”
*Biometrics*, **68**(1), 287–296.
ISSN 0006341X, doi: 10.1111/j.1541-0420.2011.01644.x.

### See Also

http://chrisbilder.com/grouptesting

Other Informative Dorfman functions: `characteristics.pool`

,
`inf.dorf.measures`

,
`opt.info.dorf`

, `opt.pool.size`

,
`pool.specific.dorf`

,
`thresh.val.dorf`

### Examples

```
# This example takes less than 1 second to run.
# Estimated running time was calculated using a
# computer with 16 GB of RAM and one core of an
# Intel i7-6500U processor.
set.seed(8135)
p.vec <- p.vec.func(p=0.02, alpha=1, grp.sz=10)
accuracy.dorf(p=p.vec[1:3], se=0.90, sp=0.90)
```

*binGroup*version 2.2-1 Index]