Check readiness of a Gazepoint-derived dataset for Bayesian or advanced models — check_gazepoint_bayesian

Performs lightweight structural checks before Bayesian, GAMM, HDDM, or other advanced modelling workflows. The function does not fit any model.

Usage

check_gazepoint_bayesian_readiness(
  data,
  outcome,
  subject,
  trial = NULL,
  time = NULL,
  condition = NULL,
  metric_type = "continuous",
  baseline_window = NULL,
  min_observations_per_subject = 10,
  max_missing_trial_prop = 0.2
)

Arguments

data: A data frame.
outcome: Name of the outcome column.
subject: Name of the subject/participant column.
trial: Optional trial column.
time: Optional time column.
condition: Optional condition column.
metric_type: Character scalar describing the planned metric/model type.
baseline_window: Optional numeric vector of length two.
min_observations_per_subject: Minimum number of observations expected per subject.
max_missing_trial_prop: Maximum acceptable missingness proportion per subject-trial cell before a warning is raised.

Value

A data frame of checks, status values, and messages.