Joint graded-response, RT, and process reference model — fit_joint_graded_rt_process

Extends the 2026 graded-response/RT direction with an optional gaze/process channel. The bundled reference engine uses proportional-odds plus crossed RT and process submodels; it is explicitly experimental rather than a claim to reproduce the published SAEM estimator.

Usage

fit_joint_graded_rt_process_irt(
  data,
  response = "response",
  rt = "rt",
  process = "fixation_count",
  person = "participant_id",
  item = "item_id",
  engine = c("reference", "brms"),
  process_family = c("negative_binomial", "poisson", "gaussian"),
  iter = 2000,
  chains = 4,
  cores = 1,
  seed = 1,
  ...
)

Arguments

data: Input data frame or compatible tabular object.
response: Response variable or response-column name.
rt: Response-time variable or column name.
process: Process variable or column name.
person: Person or participant identifier column.
item: Item identifier, name, or item column.
engine: Estimation engine.
process_family: Distributional family for the process channel.
iter: Number of estimation iterations.
chains: Number of Bayesian chains.
cores: Number of processor cores.
seed: Random-number seed.
...: Additional arguments passed to the selected model, engine, or method.