fit_multimodal_trait_irt: Multimodal trait-model convenience wrapper

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

Multimodal trait-model convenience wrapper

Description

Extends the gaze/RT architecture to noncognitive or other latent traits by allowing caller-defined semantic labels. The statistical engine is delegated to ‘fit_joint_gaze_rt_irt()'; interpretation remains the researcher’s job.

Usage

fit_multimodal_trait_irt(
  data,
  response,
  rt,
  gaze,
  person,
  item,
  trait_label = "trait",
  process_label = "process",
  ...
)

Arguments

data	Input data frame or compatible tabular object.
response	Response variable or response-column name.
rt	Response-time variable or column name.
gaze	Gaze/process variable or column name.
person	Person or participant identifier column.
item	Item identifier, name, or item column.
trait_label	Value supplied to 'trait_label'; see Details for its model-specific role.
process_label	Value supplied to 'process_label'; see Details for its model-specific role.
...	Additional arguments passed to the selected model, engine, or method.

Value

An object of class "eye_joint_gaze_rt_irt", stored as a named list, with components "engine", "response_model", "rt_model", "gaze_model", "person_scores", "item_scores", "person_covariance", "item_covariance", "data_n", "gaze_family", "columns", "status", and additional components. It contains multimodal trait-model convenience wrapper and associated metadata or diagnostics needed to interpret the result.

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