Vignettes

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 getAnalysisResults() function provides an easy way to perform an analysis with critical values that are calculated subsequently during the stages of the trial.

This R Markdown document describes how to simulate design characterics for survival design under complex settings (incl. non-proportional hazards) in rpact.

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.

This R Markdown document provides examples for designing trials with continuous endpoints using rpact.

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.

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

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.

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

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

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