ksplot.rocit {ROCit}

KS Plot

Description

Generates cumulative density of diagnostic variable in positive and negative responses.

Usage

## S3 method for class 'rocit'
ksplot(
  object,
  col = c("#26484F", "#BEBEBE", "#FFA54F"),
  lty = c(1, 1, 1),
  legend = T,
  legendpos = "bottomright",
  values = T,
  ... = NULL
)

Arguments

object

An object of class "rocit", returned by rocit function.

col

Colors to be used for plot. Minimum three colors need to be supplied for F(c), G(c) and KS Stat mark.

lty

Line types of the plots.

legend

A logical value indicating whether legends to appear in the plot.

legendpos

Position of the legend. A single keyword from "bottomright", "bottom", "bottomleft", "left", "topleft", "top", "topright", "right" and "center", as in legend. Ignored if legend is FALSE.

values

A logical value, indicating whether values to be returned.

...

NULL. Used for S3 generic/method consistency.

Details

This function plots the cumulative density functions $F(c)$ and $G(c) of the diagnostic variable in the negative and positive populations. If the positive population have higher value then negative curve ($F(c)$) ramps up quickly. The KS statistic is the maximum difference of $F(c)$ and $G(c)$.

Value

If values = TRUE, then Cutoff, F(c), G(c), KS stat, KS Cutoff are returned silently.

Note

Customized plots can be made by using the returned values of the function.

Examples

data("Diabetes")
logistic.model <- glm(as.factor(dtest)~chol+age+bmi,
                      data = Diabetes,family = "binomial")
class <- logistic.model$y
score <- qlogis(logistic.model$fitted.values)
# -------------------------------------------------------------
roc_emp <- rocit(score = score, class = class) # default method empirical
# -------------------------------------------------------------
kplot1 <- ksplot(roc_emp)
message("KS Stat (empirical) : ", kplot1$`KS stat`)
message("KS Stat (empirical) cutoff : ", kplot1$`KS Cutoff`)