sim_data: Simulate data based on a model and parameter distributions
In vpc: Create Visual Predictive Checks

Description Usage Arguments Details Value See Also

Simulate data based on a model and parameter distributions

sim_data(
  design = cbind(id = c(1, 1, 1), idv = c(0, 1, 2)),
  model = function(x) {     return(x$alpha + x$beta) },
  theta,
  omega_mat,
  par_names,
  par_values = NULL,
  draw_iiv = "mvrnorm",
  error = list(proportional = 0, additive = 0, exponential = 0),
  n = 100
)

`design`	a design dataset. See example
`model`	A function with the first argument the simulation design, i.e. a dataset with the columns ... The second argument to this function is a dataset with parameters for every individual. This can be supplied by the user, or generated by this sim_data if theta and omega_mat are supplied.
`theta`	vector of fixed effect parameters
`omega_mat`	vector of between subject random effects, specified as lower triangle
`par_names`	A character vector linking the parameters in the model to the variables in the dataset. See example.
`par_values`	parameter values
`draw_iiv`	draw between subject random effects?
`error`	see example
`n`	number of simulations to perform