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Generates cumulative density of diagnostic variable in positive and negative responses.
# S3 method for rocit
ksplot(
object,
col = c("#26484F", "#BEBEBE", "#FFA54F"),
lty = c(1, 1, 1),
legend = T,
legendpos = "bottomright",
values = T,
... = NULL
)If values = TRUE, then Cutoff, F(c), G(c), KS stat,
KS Cutoff are returned silently.
An object of class "rocit", returned by
rocit function.
Colors to be used for plot. Minimum three colors need to be supplied for F(c), G(c) and KS Stat mark.
Line types of the plots.
A logical value indicating whether legends to appear in the plot.
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.
A logical value, indicating whether values to be returned.
NULL. Used for S3 generic/method consistency.
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 $G(c)$.
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`)
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