Simulate advanced response-process data — simulate_advanced_process

Generates accuracy, response time, process features, theory-defined strategy, dynamic AOI states, pupil trajectories, measurement error, missing process data, DIF, and local dependence for validation studies.

Usage

simulate_advanced_process_data(
  n_person = 100L,
  n_item = 20L,
  n_time = 30L,
  n_states = 3L,
  ability_speed_correlation = -0.3,
  gaze_effect = 0.35,
  feature_reliability = 0.7,
  missing_process = 0,
  state_misclassification = 0,
  pupil_ar1 = 0.6,
  luminance_effect = 0,
  dif_effect = 0,
  local_dependence = 0,
  seed = 1L
)

Arguments

n_person: Number of persons.
n_item: Number of items.
n_time: Pupil time bins.
n_states: Number of AOI states.
ability_speed_correlation: Correlation between ability and speed.
gaze_effect: Process-feature coefficient in the response model.
feature_reliability: Reliability of observed gaze features.
missing_process: Fraction of process observations set missing.
state_misclassification: Probability of AOI-state misclassification.
pupil_ar1: AR(1) coefficient for pupil noise.
luminance_effect: Effect of simulated luminance on pupil size.
dif_effect: Logit-scale DIF effect for the focal group on flagged items.
local_dependence: Shared testlet-effect standard deviation.
seed: Random seed.

Value

A list with trial data, state data, pupil data, and truth.