ROC | R Documentation |

The function computes and plots the empirical ROC (receiver operating characteristic) curve.

```
ROC(object, ...)
## Default S3 method:
ROC(object, se.d, scale = 1, length = 1000,
fig = TRUE, se.type = c("CI", "SE"), CI.alpha = 0.05, ...)
## S3 method for class 'anota'
ROC(object, length = 1000, fig = TRUE,
se.type = c("CI", "SE"), CI.alpha = 0.05, ...)
```

`object` |
the class of the object defines, which of the methods is
invoked. If obejct is a single element numeric vector it is taken as
a d-prime value and the default method is invoked. If the object is
of class |

`se.d` |
a unit length vector with the standard error of d-prime. If supplied confidence intervals or standard errors are plotted |

`scale` |
a unit length vector giving the ratio of scale (ie. standard deviation) of the latent distribution for the no-class items relative to that of the yes-class items |

`length` |
the length of the vectors to be plotted. Longer vectors gives more smooth curves. |

`fig` |
Should a plot be produced? |

`se.type` |
The type of band for the ROC curve, |

`CI.alpha` |
the type I level of the confidence interval of AUC |

`...` |
additional arguments to |

The function currently ignores the variance of the scale in the computation of the uncertainty of the ROC curve.

The function makes a plot of the ROC curve, and if `se.d`

is
supplied, standard errors or confidence intervals for the curve are
added to the plot.

The function also (invisibly) returns a list with the following components

`ROCx` |
x-coordinates to the ROC curve |

`ROCy` |
y-coordinates to the ROC curve |

If `se.d`

is supplied, the object also contains

`lower` |
y-coordinates to the lower limit |

`upper` |
y-coordinates to the upper limit |

Rune Haubo B Christensen

```
## ROC.default:
(mat <- matrix(c(8, 17, 1, 24), 2, byrow = TRUE))
(d.prime <- SDT(mat, "probit")[3])
ROC(d.prime)
## ROC.anota:
fm1 <- AnotA(8, 25, 1, 25)
ROC(fm1)
```

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