Joint response, response-time, and gaze-process IRT — fit_joint_gaze_rt

The reference engine fits crossed person/item submodels for accuracy, log-response-time, and a gaze process, then returns person- and item-side latent-score covariance summaries. The `brms` engine uses multivariate formulas with shared group-level IDs so person/item random effects can be correlated across channels.

Usage

fit_joint_gaze_rt_irt(
  data,
  response = "response",
  rt = "rt",
  gaze = "fixation_count",
  person = "participant_id",
  item = "item_id",
  gaze_family = c("negative_binomial", "poisson"),
  engine = c("reference", "brms"),
  iter = 2000,
  chains = 4,
  cores = 1,
  seed = 1,
  ...
)

Arguments

data: Long person-by-item data.
response: Binary response variable.
rt: Positive response-time variable.
gaze: Gaze process variable, usually fixation count or dwell count.
person, item: Person and item identifiers.
gaze_family: Poisson or negative-binomial reference channel.
engine: `reference` or `brms`.
iter, chains, cores: Passed to brms.
seed: Random seed.
...: Additional arguments to the selected engine.

Value

An `eye_joint_gaze_rt_irt` object.