sim_outcome_joint_model: Simulate a survival and longitudinal outcome for a joint...
In NErler/simvalidator: Validation of Statistical Models via Simulation

View source: R/sim_outcome_joint_model.R

sim_outcome_joint_model

R Documentation

Simulate a survival and longitudinal outcome for a joint model

Description

Simulate a survival and longitudinal outcome for a joint model

Usage

sim_outcome_joint_model(
  data,
  formula,
  reg_coefs,
  resid_sd,
  beta_Bh0 = NULL,
  ranef_vcov,
  type,
  timevar = "time",
  basehaz_type = "splines",
  shape_wb = 1.2,
  mean_cens = 30,
  .tries = 5,
  .up = 500L,
  up_step = 500L,
  knots = NULL,
  knot_range = NULL,
  seed = NULL,
  no_obs_after_event = TRUE,
  no_subset = FALSE,
  progress_bar = FALSE,
  ...
)

Arguments

`data`	a `data.frame` containing covariate data
`formula`	a list of model formulas for the survival and longitudinal outcomes
`reg_coefs`	a list of regression coefficients with elements "surv" and "long". Each of the list elements is a (named) vector. If named, the names will be matched with the names of the design matrix that is created from `formula` and `data`.
`resid_sd`	vector of residual standard deviations for longitudinal outcomes
`beta_Bh0`	vector of coefficients for a spline specification of the baseline hazard
`ranef_vcov`	a random effects variance-covariance matrix or a named list of such matrices when there are more than two levels (and names being equal to the grouping variables)
`type`	vector of type specifications for longitudinal outcomes
`timevar`	character string giving the variable name of the time variable for the longitudinal outcome. Should be different from the name of the survival time variable.
`basehaz_type`	character string specifying the type of baseline hazard: `weibull` or `spline`
`shape_wb`	shape parameter of the weibull distribution
`mean_cens`	mean censoring time
`.tries`	integer; how often is the upper limit increased when looking for the root
`.up`	upper limit for the integration over the hazard
`up_step`	step with which `.up` is increased in case of failure
`knots`	knots for baseline hazard spline
`knot_range`	range of the knots for a spline baseline hazard; if knots are not available
`seed`	the seed value
`no_obs_after_event`	logical; should observations of the longitudinal outcome with times after the corresponding event/ censoring time be removed?
`no_subset`	logical; used for "debugging"
`progress_bar`	logical: should a progress bar be displayed
`...`	arguments passed to other functions