auc.nonpara.mw {CalibrationCurves} | R Documentation |

## AUC Based on the Mann-Whitney Statistic

### Description

Obtain the point estimate and the confidence interval of the AUC by various methods based on the Mann-Whitney statistic.

### Usage

```
auc.nonpara.mw(x, y, conf.level=0.95,
method=c("newcombe", "pepe", "delong",
"jackknife", "bootstrapP", "bootstrapBCa"),
nboot)
```

### Arguments

`x` |
a vector of observations from class P. |

`y` |
a vector of observations from class N. |

`conf.level` |
confidence level of the interval. The default is 0.95. |

`method` |
a method used to construct the CI. |

`nboot` |
number of bootstrap iterations. |

### Details

The function implements various methods based on the Mann-Whitney statistic.

### Value

Point estimate and lower and upper bounds of the CI of the AUC.

### Note

The observations from class P tend to have larger values than that from class N.

This help-file is a copy of the original help-file of the function `auc.nonpara.mw`

from the auRoc-package. It is important to note
that, when using `method="pepe"`

, the confidence interval is computed as documented in Qin and Hotilovac (2008) and that this is
different from the original function.

### References

Elizabeth R Delong, David M Delong, and Daniel L Clarke-Pearson (1988)
Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach.
*Biometrics*
**44** 837-845

Dai Feng, Giuliana Cortese, and Richard Baumgartner (2015)
A comparison of confidence/credible interval methods for
the area under the ROC curve for continuous diagnostic tests
with small sample size.
*Statistical Methods in Medical Research*
DOI: 10.1177/0962280215602040

Robert G Newcombe (2006)
Confidence intervals for an effect size measure based on the Mann-Whitney statistic. Part 2: asymptotic methods and evaluation.
*Statistics in medicine*
**25(4)** 559-573

Margaret Sullivan Pepe (2003)
The statistical evaluation of medical tests for classification and prediction.
*Oxford University Press*

Qin, G., & Hotilovac, L. (2008). Comparison of non-parametric confidence intervals for the area under the ROC curve of a continuous-scale
diagnostic test. *Statistical Methods in Medical Research*, **17(2)**, pp. 207-21

*CalibrationCurves*version 2.0.3 Index]