Simulation of parametric survival model with an already-resampled dataset

Usage

surv_param_sim_pre_resampled(
  object,
  newdata.resampled,
  newdata.orig = NULL,
  censor.dur = NULL,
  coef.var = TRUE,
  na.warning = TRUE
)

object: A survreg class object. Currently accept exponential, lognormal, weibull, loglogistic, and gaussian distributions.
newdata.resampled: A required input, the already resampled dataset for simulation. This dataset must have: (a) rep variable indicating the #simulation groups, and (b) the same number of subjects per each rep
newdata.orig: An optional input needed for calculating KM and HR for the observed data.
censor.dur: A two elements vector specifying duration of events censoring. Censoring time will be calculated with uniform distribution between two numbers. No censoring will be applied if NULL is provided.
coef.var: Boolean specifying whether parametric bootstrap are performed on survival model coefficients, based on variance-covariance matrix. If FALSE, prediction interval only reflects inherent variability from survival events.
na.warning: Boolean specifying whether warning will be shown if newdata contain subjects with missing model variables.

A survparamsim object that contains the original survreg class object, newdata, and a data frame for predicted survival profiles.

See surv_param_sim() for additional details.