comp.cutpoints: Selection of optimal number of cut points

In CatPredi: Optimal Categorisation of Continuous Variables in Prediction Models

Selection of optimal number of cut points

Description

Compares two objects of class "catpredi".

Usage

comp.cutpoints(obj1, obj2, V = 100)

Arguments

obj1	An object inheriting from class "catpredi" for k number of cut points
obj2	An object inheriting from class "catpredi" for k+1 number of cut points
V	Number of bootstrap resamples. By default V=100

Value

This function returns an object of class "comp.cutpoints" with the following components:

AUC.cor.diff

the difference of the bias corrected AUCs for the two categorical variables.

icb.auc.diff

bootstrap based confidence interval for the bias corrected AUC difference.

Author(s)

Irantzu Barrio, Maria Xose Rodriguez-Alvarez and Inmaculada Arostegui.

References

I Barrio, I Arostegui, M.X Rodriguez-Alvarez and J.M Quintana (2017). A new approach to categorising continuous variables in prediction models: proposal and validation. Statistical Methods in Medical Research, 26(6), 2586-2602.

See Also

catpredi

Examples

library(CatPredi)
set.seed(127)
#Simulate data
n = 100
#Predictor variable
xh <- rnorm(n, mean = 0, sd = 1)
xd <- rnorm(n, mean = 1.5, sd = 1)
x <- c(xh, xd)
#Response
y <- c(rep(0,n), rep(1,n))
# Data frame
df <- data.frame(y = y, x = x)


  # Select 2 optimal cut points using the AddFor algorithm. Correct the AUC
    res.backaddfor.k2 <- catpredi(formula = y ~ 1, cat.var = "x", cat.points = 2,
                                  data = df, method = "backaddfor", range=NULL, correct.AUC=TRUE,
                                  control=controlcatpredi(grid=100))
  # Select 3 optimal cut points using the AddFor algorithm. Correct the AUC
    res.backaddfor.k3 <- catpredi(formula = y ~ 1, cat.var = "x", cat.points = 3,
                                  data = df, method = "backaddfor", range=NULL, correct.AUC=TRUE,
                                  control=controlcatpredi(grid=100))

  # Select optimal number of cut points
    comp <-  comp.cutpoints(res.backaddfor.k2, res.backaddfor.k3, V = 100)
 

CatPredi documentation built on May 8, 2026, 9:07 a.m.