vcov.fitfrail function

Compute variance/covariance matrix for fitfrail model

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.

## S3 method for class 'fitfrail'
vcov(object, boot=FALSE, B=100, Lambda.times=NULL, cores=0, ...)

Arguments

• object: a fitfrail object
• 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

Returns

variance/covariance matrix for the fitfrail model parameters

See Also

fitfrail

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)