Vignettes

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 Category Sort ascending Endpoint Summary
17 How to create summaries with rpact Utilities Categorical, Continuous, Survival

This R Markdown document provides many different examples that illustrate the usage of the R generic function summary with rpact. This is a technical vignette and is to be considered mainly as a comprehensive overview of the possible summaries in rpact.

9 How to use R generics with rpact Utilities Categorical, Continuous, Survival

This R Markdown document provides many different examples that illustrate the usage of so-called R generic functions (short: R generics) with rpact, e.g., as.data.frame or summary.

12 Supplementing and enhancing rpact's graphical capabilities with ggplot2 Utilities Continuous

The aim of this R Markdown document is to give a brief description on how easy it is to supplement and enhance plots generated in rpact by use of the ggplot2 package and associated language.

Power simulation
10 How to create admirable plots with rpact Utilities Categorical, Continuous, Survival

This R Markdown document provides many different examples for creating plots with rpact and ggplot2, e.g. the plot arguments type and showSource will be illustrated.

Sample size, Power simulation, Power
13 Using the inverse normal combination test for analysing a trial with continuous endpoint and potential sample size reassessment Analysis Continuous

This R Markdown document provides an example for analysing trials with a continuous endpoint and sample size reassessment using rpact.

21 Analysis of a multi-arm design with a binary endpoint Analysis Categorical

This R Markdown document shows how to analyse and interpret multi-arm designs for testing proportions with rpact.

Multi-arm
18 How to create one- and multi-arm analysis result plots with rpact Analysis Categorical, Continuous, Survival

This R Markdown document provides many different examples for creating one- and multi-arm analysis result plots with rpact and ggplot2.

7 Analysis of a group-sequential trial with a survival endpoint 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.

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.

14 Planning a trial with binary endpoints with rpact Planning Categorical

This R Markdown document provides an example for planning a trial with a binary endpoint using rpact. It also illustrates the use of ggplot2 for illustrating the characteristics of a sample size recalculation strategy. Another example for planning a trial with binary endpoints can be found here.

Sample size, Power simulation
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.

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.

15 Planning a survival trial with rpact Planning Survival

This R Markdown document provides an example for planning a trial with a survival endpoint using rpact thereby illustrating the different ways of entering recruitment schemes. It also demonstrates the use of the survival simulation function.

Power simulation, Sample size

Events

Presentation for the U.S. Food and Drug Administration (FDA), March 3, 2022, 9:00am - 11:00am…

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Online Training Course for PPD, January 13, 2022.

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Testimonials

Daniel

TU/e

“rpact is by far the easiest to use.”
(Professor Daniel Lakens, Human-Technology Interaction Group, Eindhoven University of Technology, The Netherlands)

Director

Pharma

“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…

Daniel

TU/e

“[…] 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…