Specify a Backend-Independent Binary Model — specify_binary

Combines prepared binary data, a successful readiness audit, the restricted hierarchical formula, and validated family-specific priors. The returned object is not executable and performs no model fitting.

Usage

specify_binary_model(
  prepared,
  baseline = 0.5,
  intercept_scale = 1.5,
  coefficient_scale = 0.75,
  group_sd_scale = 1,
  correlation_eta = 2,
  student_df = 3
)

Arguments

prepared: A gp3bayes_binary_prepared object.
baseline: Plausible baseline event probability.
intercept_scale: Optional scale for the normal intercept prior.
coefficient_scale: Optional common scale for normal population-level coefficient priors, including the approved interaction.
group_sd_scale: Scale for half-Student-t group standard deviations.
correlation_eta: LKJ shape used when a random slope is requested.
student_df: Degrees of freedom for half-Student-t scale priors.

Value

A gp3bayes_binary_model_specification that also inherits from gp3bayes_model_specification.

Details

The specification retains the prepared data because backend-independent prior predictive simulation must reproduce the declared design. It contains no backend object, posterior draws, or fitted model.

Examples

simulation <- simulate_hierarchical_binary_data(
  n_participants = 12,
  trials_per_participant = 8,
  seed = 2026
)

contract <- create_model_contract(
  family = "binary",
  outcome_col = "selected",
  participant_col = "participant_id",
  item_col = "item_id",
  trial_col = "trial_id",
  condition_col = "condition"
)

prepared <- prepare_hierarchical_binary_data(
  simulation$data,
  contract,
  condition_levels = c("control", "treatment")
)

specification <- specify_binary_model(
  prepared,
  baseline = 0.35
)

specification
#> <gp3bayes_binary_model_specification>
#>   Formula: selected ~ condition + (1 | participant_id) + (1 | item_id)
#>   Fixed formula: selected ~ condition
#>   Baseline probability: 0.35
#>   Readiness: ready_with_warnings
#>   Fitting engine: none
#>   Backend dependency: none
#>   Fit performed: FALSE