|#||Title||Category Sort descending||Endpoint||Summary|
|5||Simulation-Based Design of Group Sequential Trials with a Survival Endpoint with rpact||Planning||Survival||Power simulation|
|11||Comparing Sample Size and Power Calculation Results for a Group Sequential Trial with a Survival Endpoint: rpact vs. gsDesign||Planning||Survival|
|2||Designing Group Sequential Trials with Two Groups and a Continuous Endpoint with rpact||Planning||Continuous|
|26||Delayed Response Designs||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.
|12||Supplementing and Enhancing rpact’s Graphical Capabilities with ggplot2||Planning||Continuous||Power simulation|
|20||Simulating Multi-Arm Designs with a Continuous Endpoint||Planning||Continuous||Power simulation, Multi-arm|
|7||Analysis of a Group Sequential Trial with a Survival Endpoint||Analysis||Survival|
|13||Using the Inverse Normal Combination Test for Analysing a Trial with Continuous Endpoint and Potential Sample Size Re-Assessment||Analysis||Continuous|
|21||Analysis of a Multi-Arm Design with a Binary Endpoint||Analysis||Categorical||Multi-arm|
|10||How to Create Admirable Plots with rpact||Utilities||Categorical, Continuous, Survival||Sample size, Power simulation, Power|
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