print.PowerResultsOptimalConditionalError

Print an overview of exact power results.

Design and analysis of confirmatory adaptive clinical trials using the optimal conditional error framework according to Brannath and Bauer (2004) <doi:10.1111/j.0006-341X.2004.00221.x>. An extension to the optimal conditional error function using interim estimates as described in Brannath and Dreher (2024) <doi:10.48550/arXiv.2402.00814> and functions to ensure that the resulting conditional error function is non-increasing are also available.

Morten Dreher

optconerrf

Optimal Monotone Conditional Error Functions

Werner Brannath

Cornelia Ursula Kunz

Johanna zur Verth

print.PowerResultsOptimalConditionalError function

<dl><dt>x</dt>
<dd>Power results object of class <code>PowerResultsOptimalConditionalError</code></dd>
<dt>...</dt>
<dd>Additional arguments required for generic compatibility</dd></dl>

Arguments

Print power results — print.PowerResultsOptimalConditionalError

<dl>

<dt>x</dt>
<dd>Power results object of class <code>PowerResultsOptimalConditionalError</code></dd>


<dt>...</dt>
<dd>Additional arguments required for generic compatibility</dd>

</dl>

print.PowerResultsOptimalConditionalError: Print power results

Description

Usage

Value

Arguments