Prepare Simulated Outcomes for Model Fitting — prepare_outcome

Build a fitting data set and formula metadata from an mlsim_data object that contains an outcome generator.

Usage

prepare_outcome_fit(
  sim,
  outcome = NULL,
  target = c("auto", "generic", "brmcoda"),
  drop_incomplete = TRUE,
  ...
)

Arguments

sim: An mlsim_data object returned by simulate_data().
outcome: Optional name of the outcome generator to prepare. Required when sim contains more than one outcome generator.
target: Fitting target. "generic" returns ordinary data and formulas; "brmcoda" prepares compositional outcomes with complr(); "auto" chooses "brmcoda" for compositional outcomes and "generic" otherwise.
drop_incomplete: Logical; if TRUE, remove rows with missing values in the generated fitting formulas.
...: Additional arguments passed to complr() when target = "brmcoda".

Value

An mlsim_fit_prep object containing fitting data, formulas, helper-column names, term maps, residual-correlation metadata, and target specific objects such as complr for brmcoda.

Details

Outcome formulas can contain simulation helpers such as lag1(), within(), between(), and ar1(). prepare_outcome_fit() maps those helpers to concrete columns suitable for fitting and records a term map from simulation terms to fitting terms.

Examples

sim <- simulate_data(
  n_groups = 2,
  n_per_group = 3,
  seed = 20,
  generators = list(
    x = gen_normal("x"),
    y = gen_outcome(y ~ lag1(x), residual_cov = matrix(0, 1, 1, dimnames = list("y", "y")))
  )
)
prep <- prepare_outcome_fit(sim)
prep$formula
#> y ~ lag_x
#> <environment: 0x55663ede2518>
prep$helper_columns
#> [1] "lag_x"