Plots the conditional Bayesian power — the probability of meeting the decision criterion at each fixed effect size and sample size — as a filled contour surface.
plot_power_contour(
power_results,
power_metric = c("direction", "threshold", "rope"),
x_effect = NULL,
y_effect = "n",
facet_by = NULL,
power_threshold = 0.8,
show_threshold_line = TRUE,
title = NULL,
subtitle = NULL
)A ggplot object.
Output from a brms_inla_power function.
Which metric to plot: "direction", "threshold", or "rope".
Name of effect grid column for x-axis (default = first effect).
Name of effect grid column for y-axis (default = "n").
Optional effect grid column(s) to facet by.
Optional reference contour line for conditional power (default 0.8).
Logical; add a red contour at power_threshold.
Optional plot labels.
These plots display conditional Bayesian power — the probability of
meeting the decision criterion at a fixed effect size. For unconditional
assurance (averaged over a design prior on effect size), see
plot_assurance_curve().