R: Simulate Survival Data

rsurv {ipred} | R 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)

[Package ipred version 0.9-9 Index]