CatPredi (version 1.3)

comp.cutpoints.survival: 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.

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

See Also as catpredi.survival.

Examples

# NOT RUN {
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)
  
# }
# NOT RUN {
  # 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)
  
# }
# NOT RUN {
  
# }
# NOT RUN {
    
# }