simRecurrent: Simulation of recurrent events data based on cumulative...

In mets: Analysis of Multivariate Event Times

Simulation of recurrent events data based on cumulative hazards

Description

Simulation of recurrent events data based on cumulative hazards

Usage

simRecurrent(
  n,
  cumhaz,
  death.cumhaz = NULL,
  gap.time = FALSE,
  cens = NULL,
  max.recurrent = 100,
  dhaz = NULL,
  dependence = 0,
  var.z = 2,
  cor.mat = NULL,
  ...
)

Arguments

n	number of id's
cumhaz	cumulative hazard of recurrent events
death.cumhaz	cumulative hazard of death
gap.time	if true simulates gap-times with specified cumulative hazard
cens	rate of exponential on total time i.e. on death time-scale
max.recurrent	limits number recurrent events to 100
dhaz	rate for death hazard if it is extended to time-range of first event
dependence	=0 independence, =1 all share same random effect with variance var.z =2 random effect exp(normal) with correlation structure from cor.mat, first random effect is z1 and shared for a possible second cause, second random effect is for death
var.z	variance of random effects
cor.mat	correlation matrix for var.z variance of random effects
...	Additional arguments to lower level funtions

Details

Must give hazard of death and recurrent events. Possible with two event types and their dependence can be specified but the two recurrent events need to have the same random effect, simRecurrentII more flexible !

Author(s)

Thomas Scheike

Examples

########################################
## getting some rates to mimick 
########################################

data(base1cumhaz)
data(base4cumhaz)
data(drcumhaz)
dr <- drcumhaz
base1 <- base1cumhaz
base4 <- base4cumhaz

 ######################################################################
 ### simulating simple model that mimicks data 
 ######################################################################
 rr <- simRecurrent(5,base1,death.cumhaz=dr)
 dlist(rr,.~id,n=0)

 rr <- simRecurrent(1000,base1,death.cumhaz=dr)
 par(mfrow=c(1,3))
 showfitsim(causes=1,rr,dr,base1,base1)

######################################################################
### simulating simple model 
### random effect for all causes (Z shared for death and recurrent) 
######################################################################

 rr <- simRecurrent(1000,base1,death.cumhaz=dr,dependence=1,var.gamma=0.4)
 ### marginals do fit after input after integrating out
 par(mfrow=c(2,2))
 showfitsim(causes=1,rr,dr,base1,base1)

mets documentation built on Jan. 17, 2023, 5:12 p.m.