R/sim-pc-hazard.R
sim.cif.Rd
Simulates data that looks like fit from fitted cumulative incidence model
sim.cif(cif,n,data=NULL,Z=NULL,drawZ=TRUE,cens=NULL,rrc=NULL,cumstart=c(0,0),...)
output form prop.odds.subdist or ccr (cmprsk), can also call invsubdist with with cumulative and linear predictor
number of simulations.
to extract covariates for simulations (draws from observed covariates).
to use these covariates for simulation rather than drawing new ones.
to random sample from Z or not
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.
possible vector of relative risk for cox-type censoring.
to start cumulatives at time 0 in 0.
arguments for invsubdist
data(bmt)
scif <- cifreg(Event(time,cause)~tcell+platelet+age,data=bmt,cause=1,prop=NULL)
summary(scif)
#>
#> n events
#> 408 161
#>
#> 408 clusters
#> coeffients:
#> Estimate S.E. dU^-1/2 P-value
#> tcell -0.596474 0.270388 0.275780 0.0274
#> platelet -0.426445 0.180628 0.187723 0.0182
#> age 0.343451 0.080236 0.086272 0.0000
#>
#> exp(coeffients):
#> Estimate 2.5% 97.5%
#> tcell 0.55075 0.32419 0.9356
#> platelet 0.65283 0.45819 0.9301
#> age 1.40980 1.20465 1.6499
#>
#>
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)