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Time Series Response Analyser v2.0: A Web-Based Tool for Transparent Summary Statistics From Discrete Time-Series

Benjamin J Narang1,2, Greg Atkinson3, Javier T Gonzalez4,5

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International Journal of Sport Nutrition and Exercise Metabolism
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PubMed
Summary

Time Series Response Analyser v2.0 is a new, free, open-source web tool for analyzing discrete time-series data in exercise and sport nutrition research. It enhances accessibility and transparency for reproducible research workflows.

Keywords:
area under the curvedata analysispostprandialreproducible researchtemporal response

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Area of Science:

  • Sport nutrition
  • Exercise metabolism
  • Physiological research

Background:

  • Discrete time-series data are crucial in sport nutrition and exercise metabolism research.
  • Current methods often rely on spreadsheet tools with limitations in maintenance, version control, and transparency.
  • Standardizing calculations like area under the curve is essential for accuracy.

Purpose of the Study:

  • To introduce Time Series Response Analyser v2.0 (TSRA v2.0), a web-based successor to a previous spreadsheet tool.
  • To improve accessibility, usability, and long-term maintainability of time-series data analysis.
  • To provide a transparent and reproducible analytical workflow for researchers.

Main Methods:

  • Development of a web-based application accessible via standard web browsers.
  • Implementation of a structured workflow: data setup, file interpretation screening, interactive analysis, and results export.
  • Retained core summary metrics from the original tool, expanding visualization and export options.

Main Results:

  • TSRA v2.0 offers improved accessibility and user-friendliness compared to spreadsheet-based tools.
  • The application supports both repeated-measures and independent-groups designs.
  • Enhanced visualization and export capabilities are included.

Conclusions:

  • TSRA v2.0 is a free, open-source, web-based application for discrete time-series analysis in exercise and sport science.
  • It promotes transparent and reproducible research by addressing limitations of previous tools.
  • The code-based platform facilitates future development and maintenance.