run_eyeprocess_irt_ability_sbc: Run simulation-based calibration for known-item IRT ability...

In eyeprocess: Harmonize Eye-Tracking, Pupillometry, Biometrics, and Psychometric Process Data

Run simulation-based calibration for known-item IRT ability scoring

Description

Simulates abilities from the declared normal prior, responses from the known item-response model, and posterior draws from the same grid-based scoring algorithm used by 'eyeprocess_irt_eap_score()'. This validates computational calibration of the scoring workflow under the declared generative model; it does not establish empirical adequacy or construct validity.

Usage

run_eyeprocess_irt_ability_sbc(
  items,
  replications = 200L,
  posterior_draws = 99L,
  theta_grid = seq(-5, 5, length.out = 401),
  prior_mean = 0,
  prior_sd = 1,
  interval = 0.95,
  seed = 20260811L,
  D = 1
)

Arguments

items	Item-parameter data frame or item collection.
replications	Number of simulation or validation replications.
posterior_draws	Number of posterior draws generated per SBC replication.
theta_grid	Grid of latent-trait values used for numerical scoring or integration.
prior_mean	Mean of the normal latent-trait prior.
prior_sd	Standard deviation of the normal latent-trait prior.
interval	Central posterior interval probability used for coverage assessment.
seed	Random-number seed for reproducible execution.
D	Logistic scaling constant.

Value

An object of class "eye_irt_sbc_evidence", stored as a named list, with components "diagnostics", "ecdf_deviation", "n", "n_draws". It contains simulation-based calibration for known-item IRT ability scoring and associated metadata or diagnostics needed to interpret the result.

eyeprocess documentation built on Sept. 28, 2026, 5:08 p.m.