Replicate a simulation for Monte Carlo studies

Calls one of the simulate_* functions n times with successive seeds, returning the datasets as a list – for power, Type-I, or parameter-recovery studies.

Usage

sim_replicate(FUN, n, ..., seed = NULL)

Arguments

FUN: A simulator, e.g. simulate_rasch.
n: Number of datasets.
...: Arguments passed to FUN (the same each replicate).
seed: Seed of the first replicate (each subsequent one increments it). See rasch_rng for generator support.

Value

A list of class "rasch_sim_batch", one simulated dataset per element.

Examples

# 8 datasets with a planted DIF item; how often is it flagged?
batch <- sim_replicate(simulate_rasch, 4, n_persons = 300, n_items = 8,
                       dif = list(items = "I05", uniform = 0.8), n_groups = 2,
                       seed = 1)
# sim_apply() is resilient: a replicate the estimator refuses (e.g. a
# small or disconnected draw) contributes NA instead of aborting the run
flagged <- sim_apply(batch, function(d)
  dif_anova(rasch(d, id = "id", factors = "group"))$summary$uniform_DIF[5])
mean(flagged, na.rm = TRUE)
#> [1] 0.5