boot.roc {adjROC}  R Documentation 
boot.roc
Description
computes bootstrap AUC and AUCPR for the ROC curve
Usage
boot.roc(
score,
class,
metric = "AUC",
n = 100,
method = "emp",
event_level = "first"
)
Arguments
score 
A numeric array of diagnostic score i.e. the estimated probability of each diagnosis 
class 
A numeric array of equal length of 
metric 
character. specify the metric of interest which can be

n 
number of bootstrap samples. 
method 
Specifies the method for estimating the ROC curve. Three methods
are supported, which are 
event_level 
character. only needed for bootstrapping AUCPR. this
argument specifies which level of the "class" should be
considered the positive event. the values can only be

Value
list including mean and CI of bootstrap value (sensitivity, specificity, or the crossing point) and the bootstrap data.
Examples
# random classification and probability score
score < runif(10000, min=0, max=1)
class < sample(x = c(1,0), 10000, replace=TRUE)
# calculate bootstrap AUC of the ROC curve
boot.roc(score = score, class = class, n = 100, metric = "AUC")
# calculate bootstrap AUCPR of the ROC curve
boot.roc(score = score, class = class, n = 100, metric = "AUCPR")