rsurv: Simulate Survival Data

View source: R/rsurv.R

rsurvR Documentation

Simulate Survival Data

Description

Simulation Setup for Survival Data.

Usage

rsurv(N, model=c("A", "B", "C", "D", "tree"), gamma=NULL, fact=1, pnon=10,
      gethaz=FALSE)

Arguments

N

number of observations.

model

type of model.

gamma

simulate censoring time as runif(N, 0, gamma). Defaults to NULL (no censoring).

fact

scale parameter for model=tree.

pnon

number of additional non-informative variables for the tree model.

gethaz

logical, indicating wheather the hazard rate for each observation should be returned.

Details

Simulation setup similar to configurations used in LeBlanc and Crowley (1992) or Keles and Segal (2002) as well as a tree model used in Hothorn et al. (2004). See Hothorn et al. (2004) for the details.

Value

A data frame with elements time, cens, X1 ... X5. If pnon > 0, additional noninformative covariables are added. If gethaz=TRUE, the hazard attribute returns the hazard rates.

References

M. LeBlanc and J. Crowley (1992), Relative Risk Trees for Censored Survival Data. Biometrics 48, 411–425.

S. Keles and M. R. Segal (2002), Residual-based tree-structured survival analysis. Statistics in Medicine, 21, 313–326.

Torsten Hothorn, Berthold Lausen, Axel Benner and Martin Radespiel-Troeger (2004), Bagging Survival Trees. Statistics in Medicine, 23(1), 77–91.

Examples


library("survival")
# 3*X1 + X2
simdat <- rsurv(500, model="C")
coxph(Surv(time, cens) ~ ., data=simdat)


ipred documentation built on June 2, 2022, 5:07 p.m.