summary.catpredi.survival: Summary method for objects of class "catpredi.survival"

In CatPredi: Optimal Categorisation of Continuous Variables in Prediction Models

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

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)

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