fit_nominal_gaze_irt: Nominal/distractor IRT with option-level gaze

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

Nominal/distractor IRT with option-level gaze

Description

The bundled estimator is a transparent two-stage process-augmented nominal model: participant ability may be supplied, or a shrinkage logit accuracy proxy is estimated; option-level gaze proportions then enter a multinomial response model. This is intended for validation and exploratory distractor research, not as a replacement for a fully latent nominal-response model.

Usage

fit_nominal_gaze_irt(
  data,
  response_option = "response_option",
  option_gaze,
  person = "participant_id",
  item = "item_id",
  ability = NULL,
  correct_option = NULL,
  add_item_effects = TRUE,
  ...
)

Arguments

data	Input data frame or compatible tabular object.
response_option	Column identifying the selected response option.
option_gaze	Character vector naming one gaze column per response option. Names should correspond to option labels when possible.
person	Person or participant identifier column.
item	Item identifier, name, or item column.
ability	Optional existing ability score column.
correct_option	Optional scalar or column name identifying correct option.
add_item_effects	Whether item effects are included.
...	Additional arguments passed to the selected model, engine, or method.

Value

An object of class "eye_nominal_gaze_irt", stored as a named list, with components "model", "baseline_model", "data", "option_gaze", "gaze_proportion_columns", "ability", "person", "item", "logLik_gain", "status", "note". It contains nominal/distractor IRT with option-level gaze and associated metadata or diagnostics needed to interpret the result.

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