gaze_diffusion_spec: Define a gaze-informed diffusion model

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

Define a gaze-informed diffusion model

Description

Part of the research-scale validation, advanced-model, interoperability, storage, adapter, or reproducibility programme. Experimental model functions remain subject to declared evidence gates.

Usage

gaze_diffusion_spec(response = "score", response_time = "response_time",
  participant = "participant_id", item = "item_id", drift_features = character(),
  boundary_features = character(), nondecision_features = character(),
  starting_features = character(), censor_column = NULL, contaminant = TRUE,
  engine = c("baseline", "stan", "ez_regression", "diffIRT", "brms"),
  gaze_features = NULL, chains = 4L, parallel_chains = min(4L, chains),
  iter_warmup = 1000L, iter_sampling = 1000L, adapt_delta = 0.97, max_treedepth = 13L)

Arguments

response	Binary response column.
response_time	Response-time column in seconds.
participant	Participant identifier.
item	Item identifier.
drift_features	Features assigned a priori to drift rate.
boundary_features	Features assigned a priori to boundary separation.
nondecision_features	Features assigned a priori to non-decision time.
starting_features	Features assigned a priori to starting-point bias.
censor_column	Optional censoring column with 'observed', 'left', or 'right'.
contaminant	Whether to estimate a uniform contaminant mixture.
engine	Baseline approximation or Stan Wiener model.
gaze_features	Value for 'gaze_features'. See the function description and relevant article for constraints.
chains	Stan controls.
parallel_chains	Stan controls.
iter_warmup	Stan controls.
iter_sampling	Stan controls.
adapt_delta	Stan controls.
max_treedepth	Stan controls.

Value

The documented eyeprocess object, data frame, plot, report path, or adapter result.

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