vcov.fitfrail {frailtySurv} | R Documentation |
Compute variance/covariance matrix for fitfrail model
Description
Compute the variance/covariance matrix for fitfrail estimated parameters. This can be performed by a an asymptotically-normal and consistent variance estimator or a weighted bootstrap. The resulting covariance matrix is cached in the fitted object and later retrieved if the same arguments to vcov.fitfrail
are supplied.
Usage
## S3 method for class 'fitfrail'
vcov(object, boot=FALSE, B=100, Lambda.times=NULL, cores=0, ...)
Arguments
object |
a |
boot |
logical value, whether to use a weighted bootstrap. If boot == FALSE, a consistent estimator is used and the cumulative baseline hazard variance will not be estimated. |
B |
number of repetitions in the weighted bootstrap. |
Lambda.times |
time points where the variance/covariance should be evaluated. If Lambda.times == NULL, then the points where the cumulative baseline hazard increases (where failures occur) are used. |
cores |
number of cores to use when computing the covariance matrix in parallel |
... |
extra arguments are not used |
Value
variance/covariance matrix for the fitfrail model parameters
See Also
Examples
## Not run:
dat <- genfrail(N=200, K=2, beta=c(log(2),log(3)),
frailty="gamma", theta=2,
censor.rate=0.35,
Lambda_0=function(t, tau=4.6, C=0.01) (C*t)^tau)
fit <- fitfrail(Surv(time, status) ~ Z1 + Z2 + cluster(family),
dat, frailty="gamma")
# boot=TRUE will give the weighted bootstrap variance estimates
COV <- vcov(fit, boot=FALSE)
COV
## End(Not run)