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Create Simulation Design Grid

Source: R/design.R
create_design.Rd

Expand design factors into a tibble for simulation. Use named lists for analysis_model, fit_options, and pop_values_x elements (e.g. conditions, cross factors) to get readable label columns for grouping and summarization.

Usage

create_design(..., .labels = NULL, .seed = NULL)

run_multifactor(
  design,
  reps = 100,
  parallel = FALSE,
  workers = NULL,
  save_dir = NULL,
  extract = c("estimates", "convergence")
)

Arguments

...

Named arguments; vectors become grid factors, scalars are repeated. pop_values_x supports fixed params, conditions (bundles of dependent params), and cross factors (see expand_pop_values_x).

.labels

Optional named list of label vectors for unnamed varying factors: analysis_model, fit_options, conditions, lv_cov, etc. Example: .labels = list(conditions = c("weak","strong")).

.seed

Base seed; seed = .seed + row_number() per scenario.

Value

Tibble with one row per scenario; label columns (e.g. condition_label, analysis_model_label) when names or .labels are provided.

Functions

  • run_multifactor(): Run simulation over design grid (calls run_simulation).

See also

Other design: create_modelchoice_design(), expand_pop_values_x()

Examples

dvn <- dySEM::build_dvn(n_items_x = 3, x_stem = "x", x_delim2 = "_",
  distinguish_1 = "A", distinguish_2 = "B")
#> Error: 'build_dvn' is not an exported object from 'namespace:dySEM'
script <- dySEM::scriptCor(dvn, scaleset = "FF", lvname = "X",
  constr_dy_meas = c("loadings", "intercepts", "residuals"),
  constr_dy_struct = c("variances", "means"))
#> Error: object 'dvn' not found
design <- create_design(
  pop_model_x = "Cor",
  analysis_model = script,
  n_dyads = c(50, 100),
  n_items_x = 3,
  pop_values_x = list(
    intercepts = rep(0, 3),
    coresids = c(.1, .12, .08),
    conditions = list(
      weak = list(loadings_p1 = c(.75,.8,.55), loadings_p2 = c(.75,.8,.55),
                 residuals_p1 = c(.44,.36,.7), residuals_p2 = c(.44,.36,.7)),
      strong = list(loadings_p1 = c(.7,.83,.87), loadings_p2 = c(.7,.83,.87),
                   residuals_p1 = c(.49,.31,.24), residuals_p2 = c(.49,.31,.24))
    ),
    lv_cov = list(low = 0.3, med = 0.5, high = 0.8)
  ),
  .seed = 12345
)
#> Error: object 'script' not found