plot_assurance_with_robustness

Compares assurance results from multiple scenarios by showing the range
("ribbon") of values across scenarios for each sample size and effect grid variable.

Provides tools for Bayesian power analysis and assurance calculations using the statistical frameworks of 'brms' and 'INLA'. Includes simulation-based approaches, support for multiple decision rules (direction, threshold, ROPE), sequential designs, and visualisation helpers. Methods are based on Kruschke (2014, ISBN:9780124058880) "Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan", O'Hagan & Stevens (2001) <doi:10.1177/0272989X0102100307> "Bayesian Assessment of Sample Size for Clinical Trials of Cost-Effectiveness", Kruschke (2018) <doi:10.1177/2515245918771304> "Rejecting or Accepting Parameter Values in Bayesian Estimation", Rue et al. (2009) <doi:10.1111/j.1467-9868.2008.00700.x> "Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations", and Bürkner (2017) <doi:10.18637/jss.v080.i01> "brms: An R Package for Bayesian Multilevel Models using Stan".

Tony Myers

powerbrmsINLA

Bayesian Power Analysis Using 'brms' and 'INLA'

plot_assurance_with_robustness function

<dl><dt>power_results_list</dt>
<dd>Named list of results objects from <code>brms_inla_power</code> or sequential/two-stage variants.</dd>
<dt>metric</dt>
<dd>Which assurance metric to compute: "precision", "direction", "threshold", or "bf".</dd>
<dt>x_effect</dt>
<dd>Name of effect grid column for x-axis (default: first detected grid column).</dd>
<dt>facet_by</dt>
<dd>Optional effect grid column(s) to facet by.</dd>
<dt>precision_target</dt>
<dd>CI width target if metric="precision".</dd>
<dt>p_star</dt>
<dd>Posterior probability threshold for "direction"/"threshold".</dd>
<dt>bf_threshold</dt>
<dd>BF10 threshold for "bf".</dd>
<dt>effect_filters</dt>
<dd>Optional named list for filtering rows (e.g. list(treatment=0)).</dd>
<dt>effect_weights</dt>
<dd>Optional named numeric vector for averaging over grid values.</dd>
<dt>show_individual_scenarios</dt>
<dd>Logical; if TRUE, overlay each scenario's curve.</dd>
<dt>title, subtitle</dt>
<dd>Optional plot labels.</dd></dl>

Arguments

Plot Assurance with Robustness Ribbon (Multi-Effect Grid Friendly) — plot_assurance_with_robustness

<dl>

<dt>power_results_list</dt>
<dd>Named list of results objects from <code>brms_inla_power</code> or sequential/two-stage variants.</dd>


<dt>metric</dt>
<dd>Which assurance metric to compute: "precision", "direction", "threshold", or "bf".</dd>


<dt>x_effect</dt>
<dd>Name of effect grid column for x-axis (default: first detected grid column).</dd>


<dt>facet_by</dt>
<dd>Optional effect grid column(s) to facet by.</dd>


<dt>precision_target</dt>
<dd>CI width target if metric="precision".</dd>


<dt>p_star</dt>
<dd>Posterior probability threshold for "direction"/"threshold".</dd>


<dt>bf_threshold</dt>
<dd>BF10 threshold for "bf".</dd>


<dt>effect_filters</dt>
<dd>Optional named list for filtering rows (e.g. list(treatment=0)).</dd>


<dt>effect_weights</dt>
<dd>Optional named numeric vector for averaging over grid values.</dd>


<dt>show_individual_scenarios</dt>
<dd>Logical; if TRUE, overlay each scenario's curve.</dd>


<dt>title, subtitle</dt>
<dd>Optional plot labels.</dd>

</dl>

plot_assurance_with_robustness: Plot Assurance with Robustness Ribbon (Multi-Effect Grid Friendly)

Description

Usage

Value

Arguments