comp.cutpoints.survival: 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.survival"

Usage

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

Arguments

obj1	An object inheriting from class "catpredi.survival" for k number of cut points
obj2	An object inheriting from class "catpredi.survival" 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.survival" with the following components:

CI.cor.diff

the difference of the bias corrected concordance probability for the two categorical variables.

icb.CI.diff

bootstrap based confidence interval for the bias corrected concordance probability difference.

Author(s)

Irantzu Barrio and Maria Xose Rodriguez-Alvarez.

References

I Barrio, M.X Rodriguez-Alvarez, L Meira-Machado, C Esteban and I Arostegui (2017). Comparison of two discrimination indexes in the categorisation of continuous predictors in time-to-event studies. SORT, 41:73-92

See Also

catpredi.survival

Examples

library(CatPredi)
library(survival)
set.seed(123)

#Simulate data
n = 300
tauc = 1
X <- rnorm(n=n, mean=0, sd=2)
SurvT <- exp(2*X + rweibull(n = n, shape=1, scale = 1))   + rnorm(n, mean=0, sd=0.25)
# Censoring time
CensTime <- runif(n=n, min=0, max=tauc)
# Status
SurvS <- as.numeric(SurvT <= CensTime)
# Data frame
dat <- data.frame(X = X, SurvT = pmin(SurvT, CensTime), SurvS = SurvS)

  # Select 2 optimal cut points using the AddFor algorithm. Correct the c-index
    res.k2 <- catpredi.survival (formula= Surv(SurvT,SurvS)~1, cat.var="X", cat.points = 2,
                                 data = dat, method = "addfor", conc.index = "cindex",
                                 range = NULL, correct.index = TRUE)
  # Select 3 optimal cut points using the AddFor algorithm. Correct the c-index
    res.k3 <- catpredi.survival (formula= Surv(SurvT,SurvS)~1, cat.var="X", cat.points = 3,
                                 data = dat, method = "addfor", conc.index = "cindex",
                                 range = NULL, correct.index = TRUE)
  # Select optimal number of cut points
    comp <-  comp.cutpoints.survival(res.k2, res.k3, V = 100)

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