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mets (version 1.3.4)

sim.cif: Simulation of output from Cumulative incidence regression model

Description

Simulates data that looks like fit from fitted cumulative incidence model

Usage

sim.cif(cif,n,data=NULL,Z=NULL,drawZ=TRUE,cens=NULL,rrc=NULL,cumstart=c(0,0),...)

Arguments

cif

output form prop.odds.subdist or ccr (cmprsk), can also call invsubdist with with cumulative and linear predictor

n

number of simulations.

data

to extract covariates for simulations (draws from observed covariates).

Z

to use these covariates for simulation rather than drawing new ones.

drawZ

to random sample from Z or not

cens

specifies censoring model, if "is.matrix" then uses cumulative hazard given, if "is.scalar" then uses rate for exponential, and if not given then takes average rate of in simulated data from cox model.

rrc

possible vector of relative risk for cox-type censoring.

cumstart

to start cumulatives at time 0 in 0.

...

arguments for invsubdist

Author

Thomas Scheike

Examples

Run this code
data(bmt)

scif <-  cifreg(Event(time,cause)~tcell+platelet+age,data=bmt,cause=1,prop=NULL)
summary(scif)  
plot(scif)
################################################################
#  simulating several causes with specific cumulatives 
################################################################

cif1 <-  cifreg(Event(time,cause)~tcell+age,data=bmt,cause=1,prop=NULL)
cif2 <-  cifreg(Event(time,cause)~tcell+age,data=bmt,cause=2,prop=NULL)
# dd <- sim.cifsRestrict(list(cif1,cif2),200,data=bmt)
dd <- sim.cifs(list(cif1,cif2),200,data=bmt)
scif1 <-  cifreg(Event(time,cause)~tcell+age,data=dd,cause=1)
scif2 <-  cifreg(Event(time,cause)~tcell+age,data=dd,cause=2)
   
par(mfrow=c(1,2))   
plot(cif1); plot(scif1,add=TRUE,col=2)
plot(cif2); plot(scif2,add=TRUE,col=2)

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