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
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
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.

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.

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.

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.

20 Simulating multi-arm designs with a continuous endpoint Planning Continuous

This R Markdown document provides examples for simulating multi-arm multi-stage (MAMS) designs for testing means with rpact.

Power simulation, Multi-arm
19 How to create one- and multi-arm simulation result plots with rpact Planning Categorical, Continuous, Survival

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

Power simulation, Multi-arm
8 Defining accrual time and accrual intensity with rpact Planning Survival

This R Markdown document provides a technical view on the different alternatives to define accrual time and accrual intensity with rpact.

Events

Training Courses for GKM on November 12th and FGK on November 15th, 2021, Munich, Germany.

15
Nov -

Online Training Course for FGK and GKM, Munich, Germany.

09
Nov -

rpact, an R Package for Confirmatory Adaptive Group Sequential Designs, Academia Meets Industry…

07
Oct -

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…