fbh_test {auctestr} | R Documentation |

## Apply z-test for difference between auc_1 and auc_2 using FBH method.

### Description

Apply z-test for difference between auc_1 and auc_2 using FBH method.

### Usage

```
fbh_test(auc_1, auc_2, n_p, n_n)
```

### Arguments

`auc_1` |
value of A' statistic (or AUC, or Area Under the Receiver operating characteristic curve) for the first group (numeric). |

`auc_2` |
value of A' statistic (or AUC, or Area Under the Receiver operating characteristic curve) for the second group (numeric). |

`n_p` |
number of positive observations (needed for calculation of standard error of Wilcoxon statistic) (numeric). |

`n_n` |
number of negative observations (needed for calculation of standard error of Wilcoxon statistic) (numeric). |

### Value

numeric, single aggregated z-score of comparison A'_1 - A'_2.

### References

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`

,
`se_auc`

### Examples

```
## Two models with identical AUC return z-score of zero
fbh_test(0.56, 0.56, 1000, 2500)
## Compare two models; note that changing order changes sign of z-statistic
fbh_test(0.56, 0.59, 1000, 2500)
fbh_test(0.59, 0.56, 1000, 2500)
```

*auctestr*version 1.0.0 Index]