Plots the conditional power for precision (proportion of runs where CI width <= target) vs. a chosen effect grid variable across sample size(s). Supports faceting, effect filtering, and weights.
plot_precision_assurance_curve(
power_results,
precision_target,
x_effect = NULL,
facet_by = NULL,
effect_filters = NULL,
effect_weights = NULL,
title = NULL,
subtitle = NULL
)A ggplot object.
List returned by brms_inla_power*.
Numeric; credible interval width threshold for success.
Name of effect grid column for x-axis (default: first grid column).
Optional effect grid column(s) for faceting.
Optional named list for filtering rows, e.g. list(treatment=0).
Optional named numeric vector for weights over selected x_effect values.
Optional plot labels.
These plots display conditional Bayesian power — the probability of
achieving the precision criterion at a fixed effect size. For unconditional
assurance (averaged over a design prior on effect size), see
plot_assurance_curve().