plot ROC including AUC significance — plot

Plot the complete ROC curve and the corresponding AUCs.

Usage

plot_rROC(
  x,
  col_rzAUC = "#999999",
  part = c("high", "low"),
  part_colors = default_part_colors,
  split_roc_score = FALSE
)

Arguments

x: rROC result from simple_rROC, simple_rROC_interpret or rROC.
col_rzAUC: Color for rzAUC points if split_roc_score=FALSE
part: "high", "low" or multiple
part_colors: Colors for the part
split_roc_score: Shoult the ROC score (rzAUC) be a separate plot ("TRUE") or inside the ROC curve plot ("FALSE")

Value

List of multiple ggplot elements, always "roc", if split_roc_score=TRUE also a single "rzAUC" plot

Examples

# See also test-plot_rROC()
data(aSAH, package = "pROC")
simple_rROC_res <- simple_rROC(
    response = aSAH$outcome,
    predictor = aSAH$ndka
)
#> Positive label not given, setting to last level of factor: Poor
single_rROC <- simple_rROC_interpret(simple_rROC_res)
plot_rROC(
    single_rROC,
    split_roc_score = TRUE
)
#> $roc

#> 
#> $rzAUC

#> 
plot_rROC(
    single_rROC,
    split_roc_score = FALSE
)
#> Warning: Multiple parts given, plot only the first (high)
#> $roc
#> Warning: All aesthetics have length 1, but the data has 110 rows.
#> ℹ Please consider using `annotate()` or provide this layer with data containing
#>   a single row.

#> 
plot_rROC(
    single_rROC,
    split_roc_score = FALSE,
    part = "high"
)
#> $roc
#> Warning: All aesthetics have length 1, but the data has 110 rows.
#> ℹ Please consider using `annotate()` or provide this layer with data containing
#>   a single row.

#> 
plot_rROC(
    single_rROC,
    split_roc_score = FALSE,
    part = "low"
)
#> $roc
#> Warning: All aesthetics have length 1, but the data has 110 rows.
#> ℹ Please consider using `annotate()` or provide this layer with data containing
#>   a single row.

#>