rchaz: Simulation of Piecewise constant hazard model (Cox).

In mets: Analysis of Multivariate Event Times

Simulation of Piecewise constant hazard model (Cox).

Description

Simulates data from piecwise constant baseline hazard that can also be of Cox type. Censor data at highest value of the break points.

Usage

rchaz(
  cumhazard,
  rr,
  n = NULL,
  entry = NULL,
  cum.hazard = TRUE,
  cause = 1,
  extend = FALSE
)

Arguments

cumhazard	cumulative hazard, or piece-constant rates for periods defined by first column of input.
rr	relative risk for simulations, alternatively when rr=1 specify n
n	number of simulation if rr not given
entry	delayed entry time for simuations.
cum.hazard	specifies wheter input is cumulative hazard or rates.
cause	name of cause
extend	to extend piecewise constant with constant rate. Default is average rate over time from cumulative (when TRUE), if numeric then uses given rate.

Details

For a piecewise linear cumulative hazard the inverse is easy to compute with and delayed entry x we compute

\Lambda^{-1}(\Lambda(x) + E/RR)

, where RR are the relative risks and E is exponential with mean 1. This quantity has survival function

P(T > t | T>x) = exp(-RR (\Lambda(t) - \Lambda(x)))

.

Author(s)

Thomas Scheike

Examples

chaz <-  c(0,1,1.5,2,2.1)
breaks <- c(0,10,   20,  30,   40)
cumhaz <- cbind(breaks,chaz)
n <- 100
X <- rbinom(n,1,0.5)
beta <- 0.2
rrcox <- exp(X * beta)

pctime <- rchaz(cumhaz,n=1000,cum.hazard=FALSE)
pctimecox <- rchaz(cumhaz,rrcox,cum.hazard=FALSE)

mets documentation built on May 29, 2024, 3:51 a.m.