sim_2x2: Simulate 2x2 data with autocorrelated errors
In dalejbarr/autocorr: Autocorrelation toolkit for multilevel data

Description Usage Arguments Details Value

Simulate 2x2 data with autocorrelated errors

sim_2x2(
  n_subj = 48,
  n_obs = 48,
  int = 0,
  A = 0,
  B = 0,
  AB = 0,
  rint = 0.5,
  rslp = 0.5,
  rcorr = 0.5,
  version = 0L,
  rand_fn = "shuffle",
  verbose = FALSE,
  extra_args = NULL
)

`n_subj`	Number of subjects to simulate. Must be a positive integer that is a multiple of 2.
`n_obs`	Number of observations per subject. Must be a positive even integer.
`int`	Intercept.
`A`	Main effect of A (within-subject factor).
`B`	Main effect of B (between-subject factor).
`AB`	AB interaction effect.
`rint`	Random intercept variance.
`rslp`	Random slope variance (for factor A).
`rcorr`	Random correlation.
`version`	How to generate residuals: either an integer representing the Scenario number (see `errsim`) or the name of a user-defined function.
`rand_fn`	Name of the function to randomize trial order (defaults to `shuffle`). This can be a user-supplied function; see `shuffle` for details on how this function should be constructed.
`verbose`	Whether the data frame should include GLM components.
`extra_args`	A list of extra arguments to be passed to a user-defined function to generate residuals.

When used with a user-defined function to generate residuals, the residuals for each subject will be standardized (i.e., converted to z-scores) before they are combined with other model components.

A data frame with n_subj * n_obs rows and either 9 or 12 columns depending on whether verbose is TRUE or FALSE respectively.