Two-arm Analysis for Continuous Data with Covariates from Raw Data using rpact

Analysis
Means
This document provides an example for importing raw data from a csv file, calculating estimated adjusted (marginal) means (EMMs, least-squares means) for a linear model, and performing two-arm interim analyses with these data. In this vignette, the case of an analysis of covariance (ANCOVA) model is illustrated.
Author

Friedrich Pahlke Gernot Wassmer

Published

February 18, 2025

Introduction

This vignette shows how to use the function getDataset() as an utility function to process adjusted means and estimated standard deviations from raw data, how to convert the raw data into an rpact dataset, and finally how to use this information for the analysis at interim and the final stage. Essentially, this is through the use of the CRAN package emmeans that allows the extraction of least squares means from a specified model which is an ANCOVA model in this vignette.

Contents

Note

This is an exclusive vignette for RPACT SLA customers. To read the whole vignette please login to My Account at rpact.com.

  • Setup and raw data import
    • Load required packages
    • Read raw data from local csv file
    • Check data
  • Interim analyses
    • First look: analysis at stage 1
      • Check the getDataset result
      • Create and display the analysis results:
    • Second look: analysis at stage 2
    • Last look: analysis at stage 3
  • Multi-stage raw data import
  • Conclusions

System: rpact 4.1.1.9280, R version 4.4.2 (2024-10-31), platform: x86_64-pc-linux-gnu

To cite R in publications use:

R Core Team (2024). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/.

To cite package ‘rpact’ in publications use:

Wassmer G, Pahlke F (2025). rpact: Confirmatory Adaptive Clinical Trial Design and Analysis. R package version 4.1.1.9280, commit dd4318fc8bf1b2b9bb09b7830f814871b43bcef8, https://github.com/rpact-com/rpact.