param_stratifiedAnalysis

For enrichment designs, typically a stratified analysis should be chosen.
For testing rates, also a non-stratified analysis based on overall data can be performed. 
For survival data, only a stratified analysis is possible (see Brannath et al., 2009), 
default is <code>TRUE</code>.

stratifiedAnalysis

Parameter Description: Stratified Analysis

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

param_stratifiedAnalysis function

<dl><dt>stratifiedAnalysis</dt>
<dd>For enrichment designs, typically a stratified analysis should be chosen.
For testing rates, also a non-stratified analysis based on overall data can be performed. 
For survival data, only a stratified analysis is possible (see Brannath et al., 2009), 
default is <code>TRUE</code>.</dd></dl>

Arguments

Parameter Description: Stratified Analysis — param_stratifiedAnalysis

<dl>

<dt>stratifiedAnalysis</dt>
<dd>For enrichment designs, typically a stratified analysis should be chosen.
For testing rates, also a non-stratified analysis based on overall data can be performed. 
For survival data, only a stratified analysis is possible (see Brannath et al., 2009), 
default is <code>TRUE</code>.</dd>

</dl>