plot.tout

Takes an object of class <code>tout</code> and plots sampling distributions under the
null and alternative hypotheses, highlighting which portions correspond
to stop, pause, and go outcomes.

Find the optimal decision rules (AKA progression criteria)
and sample size for clinical trials with three (stop/pause/go)
outcomes. Both binary and continuous endpoints can be accommodated,
as can cases where an adjustment is planned following a pause outcome.
For more details see Wilson et al. (2024) <doi:10.1186/s12874-024-02351-x>.

Duncan Wilson

tout

Optimal Sample Size and Progression Criteria for Three-Outcome
Trials

plot.tout function

<dl><dt>x</dt>
<dd>object of class <code>tout</code> as produced by <code>tout_design().</code></dd>
<dt>...</dt>
<dd>further arguments passed to or from other methods.</dd></dl>

Arguments

Plot sampling distributions of three-outcome designs — plot.tout

<dl>

<dt>x</dt>
<dd>object of class <code>tout</code> as produced by <code>tout_design().</code></dd>


<dt>...</dt>
<dd>further arguments passed to or from other methods.</dd>

</dl>

plot.tout: Plot sampling distributions of three-outcome designs

Description

Usage

Value

Arguments