simMultistate: Simulation of illness-death model

In mets: Analysis of Multivariate Event Times

Simulation of illness-death model

Description

Simulation of illness-death model

Usage

simMultistate(
  n,
  cumhaz,
  cumhaz2,
  death.cumhaz,
  death.cumhaz2,
  rr = NULL,
  rr2 = NULL,
  rd = NULL,
  rd2 = NULL,
  gap.time = FALSE,
  max.recurrent = 100,
  dependence = 0,
  var.z = 0.22,
  cor.mat = NULL,
  cens = NULL,
  ...
)

Arguments

n	number of id's
cumhaz	cumulative hazard of going from state 1 to 2.
cumhaz2	cumulative hazard of going from state 2 to 1.
death.cumhaz	cumulative hazard of death from state 1.
death.cumhaz2	cumulative hazard of death from state 2.
rr	relative risk adjustment for cumhaz
rr2	relative risk adjustment for cumhaz2
rd	relative risk adjustment for death.cumhaz
rd2	relative risk adjustment for death.cumhaz2
gap.time	if true simulates gap-times with specified cumulative hazard
max.recurrent	limits number recurrent events to 100
dependence	0:independence; 1:all share same random effect with variance var.z; 2:random effect exp(normal) with correlation structure from cor.mat; 3:additive gamma distributed random effects, z1= (z11+ z12)/2 such that mean is 1 , z2= (z11^cor.mat(1,2)+ z13)/2, z3= (z12^(cor.mat(2,3)+z13^cor.mat(1,3))/2, with z11 z12 z13 are gamma with mean and variance 1 , first random effect is z1 and for N1 second random effect is z2 and for N2 third random effect is for death
var.z	variance of random effects
cor.mat	correlation matrix for var.z variance of random effects
cens	rate of censoring exponential distribution
...	Additional arguments to lower level funtions

Details

simMultistate with different death intensities from states 1 and 2

Must give cumulative hazards on some time-range

Author(s)

Thomas Scheike

Examples

########################################
## getting some rates to mimick 
########################################
data(base1cumhaz)
data(base4cumhaz)
data(drcumhaz)
dr <- drcumhaz
dr2 <- drcumhaz
dr2[,2] <- 1.5*drcumhaz[,2]
base1 <- base1cumhaz
base4 <- base4cumhaz
cens <- rbind(c(0,0),c(2000,0.5),c(5110,3))

iddata <- simMultistate(10000,base1,base1,dr,dr2,cens=cens)
dlist(iddata,.~id|id<3,n=0)
 
### estimating rates from simulated data  
c0 <- phreg(Surv(start,stop,status==0)~+1,iddata)
c3 <- phreg(Surv(start,stop,status==3)~+strata(from),iddata)
c1 <- phreg(Surv(start,stop,status==1)~+1,subset(iddata,from==2))
c2 <- phreg(Surv(start,stop,status==2)~+1,subset(iddata,from==1))
###
par(mfrow=c(2,3))
bplot(c0)
lines(cens,col=2) 
bplot(c3,main="rates 1-> 3 , 2->3")
lines(dr,col=1,lwd=2)
lines(dr2,col=2,lwd=2)
###
bplot(c1,main="rate 1->2")
lines(base1,lwd=2)
###
bplot(c2,main="rate 2->1")
lines(base1,lwd=2)
 

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