TY - JOUR
T1 - A Tool to Explore Discrete-Time Data: The Time Series Response Analyser
T2 - Time Series Response Analyser
AU - Narang, Ben
AU - Atkinson, G
AU - Gonzalez, Javier
AU - Betts, James
PY - 2020/9/30
Y1 - 2020/9/30
N2 - 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.
AB - 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.
U2 - 10.1123/IJSNEM.2020-0150
DO - 10.1123/IJSNEM.2020-0150
M3 - Article
VL - 30
SP - 374
EP - 381
JO - International Journal of Sport Nutrition and Exercise Metabolism
JF - International Journal of Sport Nutrition and Exercise Metabolism
SN - 1526-484X
IS - 5
ER -