msboot {mstate} | R Documentation |
A generic nonparametric bootstrapping function for multi-state models.
msboot(theta, data, trans, B=5, id="id", verbose=0, ...)
theta |
A function of data , trans , and perhaps other
arguments, returning the value of the statistic to be bootstrapped; the output
of theta should be a scalar or numeric vector |
data |
The original data in long format, such as output from
msprep |
trans |
Transition matrix describing the states and transitions
in the multi-state model. See trans in msprep for
more detailed information |
B |
The number of bootstrap replications; the default is taken to be quite small (5) since bootstrapping can be time-consuming |
id |
Character string indicating which column identifies the subjects to be resampled |
verbose |
The level of output; default 0 = no output, 1 = print the replication |
... |
Any further arguments to the function theta |
The function msboot
samples randomly with replacement subjects
from the original dataset data
. The individuals are identified
with id
, and bootstrap datasets are produced by concatenating
all selected rows.
Matrix of dimension (length of output of theta) x B, with b'th column being the value of theta for the b'th bootstrap dataset
Marta Fiocco, Hein Putter <H.Putter@lumc.nl>
Fiocco M, Putter H, van Houwelingen HC (2008). Reduced-rank proportional hazards regression and simulation-based prediction for multi-state models. Statistics in Medicine 27, 4340–4358.
tmat <- trans.illdeath() data(ebmt1) covs <- c("score","yrel") msebmt <- msprep(time=c(NA,"rel","srv"),status=c(NA,"relstat","srvstat"), data=ebmt1,id="patid",keep=covs,trans=tmat) # define a function (this one returns vector of regression coef's) regcoefvec <- function(data,trans) { cx <- coxph(Surv(Tstart,Tstop,status)~score+strata(trans), data=data,method="breslow") return(coef(cx)) } regcoefvec(msebmt,tmat) set.seed(1234) msboot(theta=regcoefvec,data=msebmt,trans=tmat,id="patid")