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INTEREST: INteractive Tool for Exploring REsults from Simulation sTudies.

Alessandro Gasparini1, Tim P Morris2, Michael J Crowther1

  • 1Biostatistics Research Group Department of Health Sciences University of Leicester George Davies Centre University Road Leicester LE1 7RH United Kingdom.

Journal of Data Science, Statistics, and Visualisation
|January 26, 2022
PubMed
Summary
This summary is machine-generated.

Simulation studies are crucial for statistical method evaluation. The new INTEREST tool, an Interactive Tool for Exploring Results from Simulation Studies, simplifies the analysis and dissemination of complex simulation results.

Keywords:
Monte CarloRShinyreplicabilityreportingsimulation studyvisualisation

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Area of Science:

  • Statistical methodology
  • Computational statistics
  • Data science

Background:

  • Simulation studies are vital for evaluating statistical methods and informing clinical trial design.
  • Increasing complexity in simulation studies hinders clear dissemination of results.
  • Effective communication of simulation findings is essential for applied analysts and method developers.

Purpose of the Study:

  • To introduce INTEREST (Interactive Tool for Exploring Results from Simulation Studies), a novel tool designed to simplify the analysis and visualization of simulation study outcomes.
  • To provide researchers with a user-friendly platform for exploring complex simulation data.
  • To enhance the dissemination and accessibility of simulation study results.

Main Methods:

  • Developed using the R Shiny framework, INTEREST functions as a web app or standalone package.
  • The tool accepts simulation results in tidy data format from R, Stata, SAS, SPSS, or CSV.
  • Automatically estimates performance measures and Monte Carlo standard errors, presenting results in interactive tables and plots.

Main Results:

  • INTEREST facilitates focused investigation by allowing users to explore simulation parameters and estimands of interest.
  • Provides both tabular and graphical displays of results, including a wide variety of plot types.
  • Enables automatic estimation of performance measures and their associated uncertainties.

Conclusions:

  • INTEREST significantly aids in the investigation and reporting of simulation study results.
  • The tool empowers researchers to share detailed simulation findings and allows readers to explore them interactively.
  • INTEREST enhances the impact of simulation studies by improving the clarity and accessibility of their outcomes.