Bootstrap for Indirect Equating — leunbach_indirect

Performs parametric bootstrapping for indirect equating to assess standard errors of the indirect equated scores.

Usage

leunbach_indirect_bootstrap(
  fit_ab,
  fit_bc,
  direction_ab = c("1to2", "2to1"),
  direction_bc = c("1to2", "2to1"),
  nsim = 1000,
  conf_level = 0.95,
  see_type = c("rounded", "expected"),
  method = c("optimize", "newton"),
  parallel = TRUE,
  n_cores = NULL,
  verbose = FALSE,
  seed = NULL
)

Arguments

fit_ab: A leunbach_ipf object for the A-B equating
fit_bc: A leunbach_ipf object for the B-C equating
direction_ab: Direction for A-B equating: "1to2" or "2to1"
direction_bc: Direction for B-C equating: "1to2" or "2to1"
nsim: Number of bootstrap samples (default: 1000)
conf_level: Confidence level for intervals (default: 0.95)
see_type: Type of SEE calculation: "rounded" or "expected"
method: Optimization method: "optimize" (default) or "newton"
parallel: Use parallel processing if mirai is available (default: TRUE)
n_cores: Number of cores for parallel processing
verbose: Print progress messages
seed: Random seed for reproducibility

Value

A list of class "leunbach_indirect_bootstrap" containing:

indirect_eq: The observed indirect equating object
Bootstrap results and standard errors
Bootstrap p-values for LR and Gamma tests for both equatings