compute.threshold.pooledROC.BB {AROC} | R Documentation |

## Pooled ROC-based threshold values.

### Description

Estimates pooled ROC-based threshold values using the Bayesian bootstrap estimator proposed by Gu et al. (2008).

### Usage

```
compute.threshold.pooledROC.BB(object, FPF = 0.5)
```

### Arguments

`object` |
An object of class |

`FPF` |
Numeric vector with the FPF at which to calculate the pooled ROC-based threshold values. Atomic values are also valid. |

### Value

As a result, the function provides a list with the following components:

`thresholds` |
A matrix with the posterior mean and posterior 2.5% and 97.5% quantiles of the pooled ROC-based threshold values. The matrix has as many rows as different FPFs. |

`FPF` |
the supplied FPF argument |

`TPF` |
TPFs corresponding to the estimated threshold. In addition to the posterior mean, the 95% pointwise credible band is also returned. |

### References

Gu, J., Ghosal, S., and Roy, A. (2008). Bayesian bootstrap estimation of ROC curve. Statistics in Medicine, **27**, 5407–5420.

### See Also

### Examples

```
library(AROC)
data(psa)
# Select the last measurement
newpsa <- psa[!duplicated(psa$id, fromLast = TRUE),]
# Log-transform the biomarker
newpsa$l_marker1 <- log(newpsa$marker1)
m0_BB <- pooledROC.BB(y0 = newpsa$l_marker1[newpsa$status == 0],
y1 = newpsa$l_marker1[newpsa$status == 1], p = seq(0,1,l=101), B = 5000)
### Threshold values for a fixed FPF
th_m0_BB <- compute.threshold.pooledROC.BB(m0_BB, FPF = 0.1)
th_m0_BB$threshold
```

*AROC*version 1.0-4 Index]