R: Simulate Observed Data

simobs {simcausal}

R Documentation

Simulate Observed Data

This function simulates observed data from a DAG object.

simobs(
  DAG,
  n,
  wide = TRUE,
  LTCF = NULL,
  rndseed = NULL,
  rndseed.reset.node = NULL,
  verbose = getOption("simcausal.verbose")
)

`DAG`	A DAG objects that has been locked with set.DAG(DAG). Observed data from this DAG will be simulated.
`n`	Number of observations to sample.
`wide`	A logical, if TRUE the output data is generated in wide format, if FALSE, the output longitudinal data in generated in long format
`LTCF`	If forward imputation is desired for the missing variable values, this argument should be set to the name of the node that indicates the end of follow-up event. See the vignette, `sim` and `doLTCF` for additional details.
`rndseed`	Seed for the random number generator.
`rndseed.reset.node`	When `rndseed` is specified, use this argument to specify the name of the `DAG` node at which the random number generator seed is reset back to `NULL` (simulation function will call `set.seed(NULL)`). Can be useful if one wishes to simulate data using the set seed `rndseed` only for the first K nodes of the DAG and use an entirely random sample when simulating the rest of the nodes starting at K+1 and on. The name of such (K+1)th order `DAG` node should be then specified with this argument.
`verbose`	Set to `TRUE` to print messages on status and information to the console. Turn this off by default using options(simcausal.verbose=FALSE).

A data.frame where each column is sampled from the conditional distribution specified by the corresponding DAG object node.