Developed for practical use: below you find a collection of practical examples and use-cases, the so-called rpact vignettes.
In addition to these public open access vignettes, our RPACT SLA customers have access to exclusive vignettes on special topics such as the analysis of multi-stage data with covariates from raw data.
|#||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||
This R Markdown document provides examples how to analyse a survival trial and provide inference throughout and at the end of the trial with rpact.
|21||Analysis of a Multi-Arm Design with a Binary Endpoint using rpact||Analysis||Categorical||
This R Markdown document shows how to analyse and interpret multi-arm designs for testing proportions with rpact.Multi-arm
|11||Comparing Sample Size and Power Calculation Results for a Group Sequential Trial with a Survival Endpoint: rpact vs. gsDesign||Planning||Survival||
This R Markdown document provides an example that illustrates how to compare sample size and power calculation results of the two different R packages rpact and gsDesign.
|8||Defining Accrual Time and Accrual Intensity with rpact||Utilities||Survival||
This R Markdown document provides a technical view on the different alternatives to define accrual time and accrual intensity with rpact.
|1||Defining Group Sequential Boundaries with rpact||Planning||Categorical, Continuous, Survival||
This R Markdown document provides example code for the the definition of the most commonly used group-sequential boundaries in rpact.
|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||
This R Markdown document provides examples for designing trials with binary endpoints using rpact.
|2||Designing Group Sequential Trials with Two Groups and a Continuous Endpoint with rpact||Planning||Continuous||
This R Markdown document provides examples for designing trials with continuous endpoints using rpact.
|4||Designing Group Sequential Trials with Two Groups and a Survival Endpoint with rpact||Planning||Survival||
This R Markdown document provides examples for designing trials with survival endpoints using rpact.
Presentation for the U.S. Food and Drug Administration (FDA), March 3, 2022, 9:00am - 11:00am…
Presentation for Lantheus, January 18, 2022.
“rpact is by far the easiest to use.”
(Professor Daniel Lakens, Human-Technology Interaction Group, Eindhoven University of Technology, The Netherlands)
“We regularly use rpact for the design of group-sequential and adaptive trials at our company. The package is continuously evolving and includes state-of-the-art methods such as estimation of…
“[…] it is an incredibly accessible and useful tool for sequential analyses. […] I think your rpact package and shiny app might be a bit of a game-changer on this front, as it makes the required…
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