plot_sequential_monitor

Visualises a <code>sequential_analysis()</code> monitor: either the monitored
posterior probability across looks with the prespecified success and
futility boundaries, or the effect estimate with its credible interval
across looks.

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_sequential_monitor function

<dl><dt>monitor</dt>
<dd>A <code>"powerbrmsINLA_seq_monitor"</code> object.</dd>
<dt>type</dt>
<dd><code>"probability"</code> (default) or <code>"estimate"</code>.</dd>
<dt>title, subtitle</dt>
<dd>Optional plot annotations.</dd></dl>

Arguments

Plot a sequential analysis trajectory with stopping boundaries — plot_sequential_monitor

<dl>

<dt>monitor</dt>
<dd>A <code>"powerbrmsINLA_seq_monitor"</code> object.</dd>


<dt>type</dt>
<dd><code>"probability"</code> (default) or <code>"estimate"</code>.</dd>


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

</dl>

plot_sequential_monitor: Plot a sequential analysis trajectory with stopping boundaries

Description

Usage

Value

Arguments