Getting started with rpact

Friedrich Pahlke

November 15, 2024

R package rpact – Getting started

Various learning concepts available:

The R Package rpact – Functional Range

Trial Designs

  • Fixed sample design
  • Group sequential designs
  • Adaptive designs using the inverse normal and Fisher’s combination test, and conditional error rate principle

Easy to understand R commands:

getDesignGroupSequential()
getDesignInverseNormal()
getDesignFisher()
getDesignConditionalDunnett()

Sample Size and Power Calculation

for

  • testing means (continuous endpoint)
  • testing rates (binary endpoint)
  • survival trials with flexible recruitment and survival time options
  • testing rates for count data

Easy to understand R commands:

getSampleSize[Means/Rates/Survival/Counts]()
getPower[Means/Rates/Survival/Counts]()

Example:

getSampleSizeMeans()
getPowerMeans()

Adaptive Analysis

for testing means, rates, and survival data

  • Calculates adjusted point estimates and confidence intervals
  • Some highlights:
    • Automatic boundary recalculations during the trial for analysis with alpha spending approach, including under- and over-running
    • Adaptive analysis tools for multi-arm trials
    • Adaptive analysis tools for enrichment design

Easy to understand R commands:

getStageResults()
getRepeatedConfidenceIntervals()
getAnalysisResults()

…

Simulation Tool

for means, rates, survival data, and count data

  • Assessment of adaptive sample size/event number recalculation strategies
  • Assessment of treatment selection strategies in multi-arm trials
  • Assessment of population selection strategies in enrichment designs

Easy to understand R commands:

getSimulation[MultiArm/Enrichment][Means/Rates/Survival/Counts]()

Example:

getSimulationMeans()
getSimulationMultiArmMeans()
getSimulationEnrichmentMeans()

\(\rightarrow\) rpact useful for conducting flexible simulations in clinical trial planning

The R Package rpact

Further information, installation, and usage:

RPACT Cloud

RPACT Cloud – Introduction

  • Graphical user interface
  • Web based usage without local installation on nearly any device
  • Provides an easy entry to rpact
  • Starting point for your R Markdown or Quarto reports
  • Helpful to learn/demonstrate the usage of rpact in a user friendly and intuitive way
  • Online available at cloud.rpact.com

RPACT Cloud – Start Page

RPACT Cloud – Design

RPACT Cloud – Reporting

RPACT Cloud – Export

RPACT Cloud – Design Comparison

End of “Getting started with rpact”