simScenPrevSensSpec {bootComb} | R Documentation |

## Simulation scenario for adjusting a prevalence for sensitivity and specificity.

### Description

This is a simulation to compute the coverage of the confidence interval returned by bootComb() in the case of adjusting a prevalence estimate for estimates of sensitivity and specificity.

### Usage

```
simScenPrevSensSpec(
B = 1000,
p,
sens,
spec,
nExp,
nExpSens,
nExpSpec,
alpha = 0.05,
assumeSensSpecExact = FALSE
)
```

### Arguments

`B` |
The number of simulations to run. Defaults to 1e3. |

`p` |
The true value of the prevalence parameter. |

`sens` |
The true value of the assay sensitivity parameter. |

`spec` |
The true value of the assay specificity parameter |

`nExp` |
The size of each simulated experiment to estimate |

`nExpSens` |
The size of each simulated experiment to estimate |

`nExpSpec` |
The size of each simulated experiment to estimate |

`alpha` |
The confidence level; i.e. the desired coverage is 1-alpha. Defaults to 0.05. |

`assumeSensSpecExact` |
Logical; indicates whether coverage should also be computed for the situation where sensitivity and specificity are assumed to be known exactly. Defaults to FALSE. |

### Value

A list with 2 or 4 elements, depending whether `assumeSensSpecExact`

is set to FALSE or TRUE:

`estimate` |
A single number, the proportion of simulations for which the confidence interval contained the true prevalence parameter value. |

`conf.int` |
A confidence interval of coverage 1-alpha for the coverage estimate. |

`estimate.sensSpecExact` |
Returned only if |

`conf.int.sensSpecExact` |
Returned only if |

### Examples

```
simScenPrevSensSpec(p=0.15,sens=0.85,spec=0.90,nExp=300,nExpSens=600,nExpSpec=400,B=100)
# B value only for convenience here
# Increase B to 1e3 or 1e4 (be aware this may run for some time).
```

*bootComb*version 1.1.2 Index]