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.

# Sort ascending Title Category Endpoint Summary
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.

23 Planning and Analyzing a Group-Sequential Multi-Arm Multi-Stage Design with Binary Endpoint using rpact Getting started Categorical

This R Markdown document provides an example of implementing, simulating and analyzing multi-arm-multi-stage (MAMS) designs for testing rates with rpact with special regards to futility bound determination, treatment arm selection and generic data analysis.

After exemplarily using the binary endpoint analysis module from rpact, an illustrative landmark analysis (comparison of empirical survival probabilities at specific time point) using Greenwoods standard error estimation is to be performed. Since rpact itself does not directly support this type of analysis, another packages’ functionality needs to be utilized to perform the survival probability and standard error estimation to eventually use the estimates as input for a hypothetical continuous endpoint dataset which subsequently is to be analyzed as such.

Multi-arm
22 Step-by-Step rpact Tutorial Getting started Categorical, Continuous, Survival

The R package rpact has been developed to design sequential and adaptive experiments. Many of the functions of the R package are available in an online Shiny app. For more information about rpact, including a quick start guide and manual, visit the rpact website. This step by step vignette accompanies the manuscript “Group Sequential Designs: A Tutorial” by Lakens, Pahlke, & Wassmer (2021).

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
20 Simulating Multi-Arm Designs with a Continuous Endpoint using rpact 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 Utilities 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, Planning
18 How to Create One- and Multi-Arm Analysis Result Plots with rpact Utilities Categorical, Continuous, Survival

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

Analysis
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.

16 Simulation of a Trial with a Binary Endpoint and Unblinded Sample Size Re-Calculation with rpact Planning Categorical

This R Markdown document provides examples for assessing trials with adaptive sample size re-calculation (SSR) using rpact. It also shows how to implement the promizing zone approach as proposed by Mehta and Pocock 2011 and further developed by Hsiao et al 2019 with rpact.

Power simulation
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…