sebootjack: Simulate (Robust) Standard Errors using a bootstrap procedure...

In HansTierens/MMixCure: Fit a Multilevel Mixture Cure with Correlated Random Effects in Incidence and Latency

Description

Calculate (Robust) Standard Errors using either a bootstrap procedure or a Jackknife estimate.

Usage

sebootjack(
  fit,
  data,
  method = c("boot", "jack"),
  k = 1,
  nboot = 100,
  nmax = 1000
)

Arguments

fit	A fitted model of class smcure.
data	The dataset on which the fitted model was fit.
method	Either 'boot' for a bootstrap procedure, or 'jack' for a jackknife procedure.
k	the number of observations to omit from the dataset for the leave-k-out Jackknife estimate on the standard errors. Default = 1, for al leave-one-out jackknife procedure.
nboot	Number of iterations in the sampling-resampling procedure of the bootstrap estimator.
nmax	Maximum number of resampling iterations for the bootstrap and jackknife estimators.

HansTierens/MMixCure documentation built on Dec. 31, 2020, 12:59 p.m.