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rpact: Confirmatory Adaptive Clinical Trial Design and Analysis

Using the Inverse Normal Combination Test for Analysing a Trial with Continuous Endpoint and Potential Sample Size Re-Assessment with rpact

Summary

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

1 Define the type of design to be used for the analysis

First, load the rpact package

library(rpact)
packageVersion("rpact") # version should be version 2.0.5 or later

## [1] '3.3.2'

In this vigentte, we want to illustrate a design where at interim stages we are able to perform data-driven sample size adaptations. For this purpose, we use the inverse normal combination test for combining the \(p\)-values from the stages of the trial. This type of design ensures that the Type I error rate is controlled.

We want to use a three stage design with O`Brien and Fleming boundaries and additionally want to consider futility bounds -0.5 and 0.5 for the test statistics at the first and the second stage, respectively. Accordingly,

# Example of an inverse normal combination test:
designIN <- getDesignInverseNormal(futilityBounds = c(-0.5, 0.5))

defines the design to be used for this purpose. By default, this is a design with equally spaced information rates and one sided \(\alpha = 0.025\). The critical values can be displayed on the \(z\)-value or the \(p\)-value scale:

plot(designIN, type = 1)