Description Usage Arguments Examples

View source: R/plot_functions_main.R

Plot the components of the ROC curve –the true positive rates and false positive rates– by high risk thresholds.

1 2 3 4 5 6 | ```
plot_roc_components(x, cost.benefit.axis = TRUE, n.cost.benefits = 6,
cost.benefits, confidence.intervals, col = "black", lty.fpr = 2,
lty.tpr = 1, lwd = 2, xlim, ylim, xlab = "Risk Threshold", ylab,
cost.benefit.xlab = "Cost:Benefit Ratio", legend.position = c("topright",
"right", "bottomright", "bottom", "bottomleft", "left", "topleft", "top",
"none"), ...)
``` |

`x` |
decision_curve object to plot. Assumes output from function 'decision_curve' |

`cost.benefit.axis` |
logical (default TRUE) indicating whether to print an additional x-axis showing relative cost:benefit ratios in addition to risk thresholds. |

`n.cost.benefits` |
number of cost:benefit ratios to print if cost.benefit.axis = TRUE (default n.cost.benefit = 6). |

`cost.benefits` |
Character vector of the form c("c1:b1", "c2:b2", ..., "cn:bn") with integers ci, bi corresponding to specific cost:benefit ratios to print. Default allows the function to calculate these automatically. |

`confidence.intervals` |
logical indicating whether to plot confidence intervals. |

`col` |
vector of length two indicating the color for the true positive rates and false positive rates, respectively. |

`lty.fpr` |
linetype for the false positive rate curve. |

`lty.tpr` |
linetype for the true positive rate curve. |

`lwd` |
vector of linewidths. The first element corresponds to the tpr and the second to the fpr. |

`xlim` |
vector giving c(min, max) of x-axis. Defaults to c(min(thresholds), max(thresholds)). |

`ylim` |
vector giving c(min, max) of y-axis. |

`xlab` |
label of main x-axis. |

`ylab` |
label of y-axis. |

`cost.benefit.xlab` |
label of cost:benefit ratio axis. |

`legend.position` |
character vector giving position of legend. Options are "topright" (default), "right", "bottomright", "bottom", "bottomleft", "left", "topleft", "top", or "none". |

`...` |
other options directly send to plot() |

1 2 3 4 5 6 7 8 9 | ```
data(dcaData)
set.seed(123)
baseline.model <- decision_curve(Cancer~Age + Female + Smokes,
data = dcaData,
thresholds = seq(0, .4, by = .001),
bootstraps = 25) #should use more bootstrap replicates in practice!
#plot using the defaults
plot_roc_components(baseline.model, xlim = c(0, 0.4), col = c("black", "red"))
``` |

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