param_conditionalPowerSimulation

Parameter Description: Conditional Power

internal

Design and analysis of confirmatory adaptive clinical trials with continuous, binary, and survival endpoints according to the methods described in the monograph by Wassmer and Brannath (2016) <doi:10.1007/978-3-319-32562-0>. This includes classical group sequential as well as multi-stage adaptive hypotheses tests that are based on the combination testing principle.

Friedrich Pahlke

rpact

Confirmatory Adaptive Clinical Trial Design and Analysis

Gernot Wassmer

Till Jensen

Stephen Schueuerhuis

param_conditionalPowerSimulation function

<dl><dt>conditionalPower</dt>
<dd>If <code>conditionalPower</code> together with <code>minNumberOfSubjectsPerStage</code> and
<code>maxNumberOfSubjectsPerStage</code> (or <code>minNumberOfEventsPerStage</code> and <code>maxNumberOfEventsPerStage</code>
for survival designs) is specified, a sample size recalculation based on the specified conditional power is performed.
It is defined as the power for the subsequent stage given the current data. By default,
the conditional power will be calculated under the observed effect size. Optionally, you can also specify <code>thetaH1</code> and
<code>stDevH1</code> (for simulating means), <code>pi1H1</code> and <code>pi2H1</code> (for simulating rates), or <code>thetaH1</code> (for simulating
hazard ratios) as parameters under which it is calculated and the sample size recalculation is performed.</dd></dl>

Arguments

Parameter Description: Conditional Power — param_conditionalPowerSimulation

<dl>

<dt>conditionalPower</dt>
<dd>If <code>conditionalPower</code> together with <code>minNumberOfSubjectsPerStage</code> and
<code>maxNumberOfSubjectsPerStage</code> (or <code>minNumberOfEventsPerStage</code> and <code>maxNumberOfEventsPerStage</code>
for survival designs) is specified, a sample size recalculation based on the specified conditional power is performed.
It is defined as the power for the subsequent stage given the current data. By default,
the conditional power will be calculated under the observed effect size. Optionally, you can also specify <code>thetaH1</code> and
<code>stDevH1</code> (for simulating means), <code>pi1H1</code> and <code>pi2H1</code> (for simulating rates), or <code>thetaH1</code> (for simulating
hazard ratios) as parameters under which it is calculated and the sample size recalculation is performed.</dd>

</dl>