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rmcorrShiny: A web and standalone application for repeated measures correlation.

Laura R Marusich1, Jonathan Z Bakdash2,3

  • 1U.S. Army Combat Capabilities Development Command Army Research Laboratory South at the University of Texas at Arlington, Arlington, TX, 76019, USA.

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Summary

This study introduces rmcorrShiny, a new tool for calculating repeated measures correlation (rmcorr). It offers a user-friendly interface for analyzing paired data, avoiding common statistical pitfalls.

Keywords:
Shinycorrelationmultilevel modelingregressionrepeated measuresrepeated measures correlationstatisticswithin-participants

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Area of Science:

  • Statistics
  • Psychology
  • Biostatistics

Background:

  • Traditional correlation methods often assume data independence, which is violated in repeated measures.
  • Analyzing dependent repeated measures data as independent can lead to inaccurate conclusions and reduced statistical power.
  • Existing methods like aggregation or separate models may obscure patterns and decrease power.

Purpose of the Study:

  • To introduce rmcorrShiny, a web and standalone application for calculating repeated measures correlation (rmcorr).
  • To enhance the accessibility of rmcorr analysis through a graphical user interface.
  • To provide a straightforward solution for analyzing within-individual associations in paired measures across multiple individuals.

Main Methods:

  • Development of a Shiny application for calculating repeated measures correlation (rmcorr).
  • Implementation of a graphical interface for performing and visualizing rmcorr analysis.
  • The tool is designed for paired measures from multiple individuals with repeated assessments.

Main Results:

  • rmcorrShiny provides accessible computation and visualization of repeated measures correlation.
  • The application facilitates accurate analysis of within-individual associations, unlike methods assuming independence.
  • It offers a solution to the limitations of traditional methods when dealing with dependent data.

Conclusions:

  • rmcorrShiny democratizes the use of repeated measures correlation (rmcorr) analysis.
  • The tool addresses the critical need for appropriate statistical methods for dependent repeated measures data.
  • It enables researchers to obtain more reliable insights from their paired data analyses.