Conditional censored-normal calibration for bounded process measurements — fit_censored_normal_process

Fits the 2026 censored-normal response form item-by-item conditional on a supplied latent score. This is a useful calibration/diagnostic engine for bounded continuous process variables such as AOI proportions. It is NOT the paper's full marginal EM estimator and should therefore remain experimental.

Usage

fit_censored_normal_process_irt(
  response_matrix,
  theta,
  lower = 0,
  upper = 1,
  control = list(maxit = 1000)
)

Arguments

response_matrix: Person x item bounded continuous matrix.
theta: Supplied person latent scores on the calibration scale.
lower, upper: Observable bounds.
control: `optim()` control list.

Value

An object of class "eye_censored_normal_process_irt", stored as a named list, with components "coefficients", "fits", "theta", "lower", "upper", "engine", "status", "citation", "caveat". It contains conditional censored-normal calibration for bounded process measurements and associated metadata or diagnostics needed to interpret the result.