msboot {mstate}

Bootstrap function in multi-state models

Description

A generic nonparametric bootstrapping function for multi-state models.

Usage

msboot(theta, data, B = 5, id = "id", verbose = 0, ...)

Arguments

theta

A function of data 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

An object of class 'msdata', such as output from msprep

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

Details

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.

Value

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

Author(s)

Marta Fiocco, Hein Putter <[e-mail]>

References

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.

Examples

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) {
  cx <- coxph(Surv(Tstart,Tstop,status)~score+strata(trans),
          data=data,method="breslow")
  return(coef(cx))
}
regcoefvec(msebmt)
set.seed(1234)
msboot(theta=regcoefvec,data=msebmt,id="patid")