Fit a gaze-informed missingness IRT diagnostic — fit_gaze_informed_missingness

Fits a transparent two-part reference model: (1) whether an item response is missing and (2) the observed response, both conditional on a supplied latent trait (or a clearly labelled person-score proxy), item, and visual exposure. This is a diagnostic bridge to joint MNAR/process IRT, not a substitute for a fully joint latent missingness model.

Usage

fit_gaze_informed_missingness_irt(
  data,
  response = "response",
  person = "participant_id",
  item = "item_id",
  gaze_exposure = "gaze_exposure",
  theta = NULL,
  reached = NULL
)

Arguments

data: Long person-item data.
response: Response column; missing values identify omissions.
person, item: Person and item identifiers.
gaze_exposure: Non-negative visual-exposure measure.
theta: Optional latent-trait column. If `NULL`, a smoothed person proportion-correct logit is used as an explicit proxy.
reached: Optional reached/not-reached indicator.

Value

An `eye_gaze_informed_missingness_irt` object.