A Tool to Explore Discrete-Time Data: The Time Series Response Analyser

Benjamin J. Narang, Greg Atkinson, Javier T. Gonzalez, James A. Betts

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The analysis of time series data is common in nutrition and metabolism research for quantifying the physiological responses to various stimuli. The reduction of many data from a time series into a summary statistic(s) can help quantify and communicate the overall response in a more straightforward way and in line with a specific hypothesis. Nevertheless, many summary statistics have been selected by various researchers, and some approaches are still complex. The time-intensive nature of such calculations can be a burden for especially large datasets and may, therefore, introduce computational errors, which are difficult to recognize and correct. In this short commentary, we introduce a newly-developed tool that automates many of the processes commonly used by researchers for discrete-time series analysis, with particular emphasis on how the tool may be implemented within nutrition and exercise science research.
Original languageEnglish
JournalInternational Journal of Sport Nutrition and Exercise Metabolism
Publication statusAccepted/In press - 3 Jul 2020

Bibliographical note

Accepted author manuscript version reprinted, by permission, from International Journal of Sport Nutrition and Exercise Metabolism, 2020 (ahead of print). © Human Kinetics, Inc.

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