summary.catpredi.survival {CatPredi}

Summary method for objects of class "catpredi.survival"

Description

Produces a summary of a "catpredi.survival" object. The following are printed: the call to the catpredi.survival() function; the estimated optimal cut points obtained with the method and concordance probability estimator selected and the estimated and bias corrected concordance probability for the categorised variable (whenever the argument correct.index is set to TRUE) .

Usage

## S3 method for class 'catpredi.survival'
summary(object, digits = 4, ...)

Arguments

object

an object of class "catpredi.survival" as produced by catpredi.survival()

digits

.

...

further arguments passed to or from other methods.

Value

Returns an object of class "summary.catpredi.survival" with the same components as the catpredi.survival function (see catpredi.survival).

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

See Also as catpredi.survival.

Examples

library(CatPredi)
library(survival)
set.seed(123)
#Simulate data
  n = 500
  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 optimal cut points using the AddFor algorithm
  res <- catpredi.survival (formula= Surv(SurvT,SurvS)~1, cat.var="X", cat.points = 2,
   data = dat, method = "addfor", conc.index = "cindex", range = NULL,
    correct.index = FALSE) 
  # Summary
  summary(res)