Nominal/distractor IRT with option-level gaze — fit_nominal_gaze

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.