# Hierarchical Effect and Variance Atlases

The expanded group-level layer can inspect raw posterior deviations, rank uncertainty, and baseline latent variance partitioning.

    draws <- group_effect_draws_table(
      fit,
      groups = "participant_id",
      coefficients = "Intercept",
      ndraws = 1000
    )

    ranks <- group_effect_rank_probability_table(
      fit,
      group = "participant_id",
      coefficient = "Intercept"
    )

    partition <- random_intercept_variance_partition(fit)

    plot_group_effect_distribution(draws)
    plot_group_effect_rank_probability(ranks)
    plot_random_intercept_variance_partition(partition)

Rank probabilities and variance fractions remain descriptive posterior quantities; they do not establish substantive group importance or causal variance attribution.