adjroc {adjROC}

adjroc

Description

computes adjusted sensitivity, adjusted specificity, or the crossing point between sensitivity and specificity for different thresholds

Usage

adjroc(
  score,
  class,
  method = "emp",
  sensitivity = NULL,
  specificity = NULL,
  plot = FALSE
)

Arguments

score

A numeric array of diagnostic score i.e. the estimated probability of each diagnosis

class

A numeric array of equal length of "score", including the actual class of the observations

method

Specifies the method for estimating the ROC curve. Three methods are supported, which are "empirical", "binormal", and "nonparametric"

sensitivity

numeric. Specify the threshold of sensitivity

specificity

numeric. Specify the threshold of specificity

plot

logical. if TRUE, the sensitivity and specificity will be plotted

Value

data.frame including cutoff point, and adjusted sensitivity and specificity based on the specified threshold

Examples

# random classification and probability score
score <- runif(10000, min=0, max=1)
class <- sample(x = c(1,0), 10000, replace=TRUE)

# calculate adjusted sensitivity, when specificity threshold is 0.90:
adjroc(score = score, class = class, specificity = 0.9, plot = TRUE)

# calculate adjusted specificity, when sensitivity threshold equals 0.9
adjroc(score = score, class = class, sensitivity = 0.9, plot = TRUE)

# calculate the meeting point between sensitivity and specificity
adjroc(score = score, class = class, plot = TRUE)