se_auc {auctestr} | R Documentation |

## Compute standard error of AUC score, using its equivalence to the Wilcoxon statistic.

### Description

Compute standard error of AUC score, using its equivalence to the Wilcoxon statistic.

### Usage

```
se_auc(auc, n_p, n_n)
```

### Arguments

`auc` |
value of A' statistic (or AUC, or Area Under the Receiver operating characteristic curve) (numeric). |

`n_p` |
number of positive cases (integer). |

`n_n` |
number of negative cases (integer). |

### References

Hanley and McNeil, The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology (1982) 43 (1) pp. 29-36.

Fogarty, Baker and Hudson, Case Studies in the use of ROC Curve Analysis for Sensor-Based Estimates in Human Computer Interaction, Proceedings of Graphics Interface (2005) pp. 129-136.

### See Also

Other fbh method: `auc_compare`

,
`fbh_test`

### Examples

```
se_auc(0.75, 20, 200)
## standard error decreases when data become more balanced over
## positive/negative outcome class, holding sample size fixed
se_auc(0.75, 110, 110)
## standard error increases when sample size shrinks
se_auc(0.75, 20, 20)
```

[Package

*auctestr*version 1.0.0 Index]