auc.para.frequentist {auRoc} R Documentation

## AUC by Frequentist Parametric Methods

### Description

Obtain the point estimate and the confidence interval of the AUC using some frequentist parametric methods.

### Usage

```   auc.para.frequentist(x, y, conf.level=0.95,
dist=c("normalDV", "normalEV", "exponential"),
method=c("lrstar", "lr", "wald", "RG1", "RG2"))
```

### 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. `dist` the name of a parametric distribution. `normalEV` stands for normal distributions with equal variance; `normalDV` stands for normal distributions with unequal variances; `exponential` stands for exponential distributions. The default is `normalDV`. It can be abbreviated. `method` a method used to construct the CI. `lrstar` uses the likelihood ratio test based on higher-order asymptotic results; `lr` uses the signed log-likelihood ratio test; `wald` uses the Wald test; `RG1` is the approximate "t" solution to the Behrens-Fisher problem; `RG2` is the normal approximation to `RG1`. `RG1` and `RG2` are for normal distributions. The default is `lrstar`. It can be abbreviated.

### Details

Use a variety of frequentist methods for different parametric models to estimate the AUC.

### 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 then that from class N.

Dai Feng

### References

Giuliana Cortese and Laura Ventura (2013) Accurate higher-order likelihood inference on P(Y < X). Computational Statistics 28(3) 1035-1059

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

Benjamin Reiser and Irwin Guttman (1986) Statistical inference for Pr(Y < X): The normal case. Technometrics 28(3) 253-257

### Examples

```
#Example 1
data(petBrainGlioma)
y <- subset(petBrainGlioma, grade==1, select="FDG", drop=TRUE)
x <- subset(petBrainGlioma, grade==2, select="FDG", drop=TRUE)
auc.para.frequentist(x, y, dist="exp")

#Example 2
data(petBrainGlioma)
y <- subset(petBrainGlioma, grade==1, select="ACE", drop=TRUE)
x <- subset(petBrainGlioma, grade==2, select="ACE", drop=TRUE)
auc.para.frequentist(x, y, method="RG1")

```

[Package auRoc version 0.2-1 Index]