|#||Title Sort descending||Category||Endpoint||Summary|
|6||An Example to Illustrate Boundary Re-Calculations during the Trial with rpact||Planning||Survival||
This R Markdown document provides an example for updating the group sequential boundaries when using an alpha-spending function approach based on observed information rates in rpact. Since version 3.1 of rpact, an additional option in the
|7||Analysis of a Group Sequential Trial with a Survival Endpoint using rpact||Analysis||Survival|
|21||Analysis of a Multi-Arm Design with a Binary Endpoint using rpact||Analysis||Categorical||Multi-arm|
|11||Comparing Sample Size and Power Calculation Results for a Group Sequential Trial with a Survival Endpoint: rpact vs. gsDesign||Planning||Survival|
|8||Defining Accrual Time and Accrual Intensity with rpact||Utilities||Survival|
|1||Defining Group Sequential Boundaries with rpact||Planning||Categorical, Continuous, Survival|
|26||Delayed Response Designs with rpact||Planning||Categorical, Continuous, Survival||
This R Markdown document provides a brief introduction to group sequential designs with delayed responses as proposed by Hampson and Jennison (2013). It is shown how this is implemented in rpact. Examples for designing trials with delayed responses using the software are provided. We also describe an alternative approach that directly uses the α-spending approach to derive the decision boundaries.
|3||Designing Group Sequential Trials with a Binary Endpoint with rpact||Planning||Categorical|
|2||Designing Group Sequential Trials with Two Groups and a Continuous Endpoint with rpact||Planning||Continuous|
|4||Designing Group Sequential Trials with Two Groups and a Survival Endpoint with rpact||Planning||Survival|
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