TY - JOUR
T1 - A tool to explore discrete-time data
T2 - The time series response analyser
AU - Narang, Benjamin J.
AU - Atkinson, Greg
AU - Gonzalez, Javier T.
AU - Betts, James A.
N1 - Accepted author manuscript version reprinted, by permission, from International Journal of Sport Nutrition and Exercise Metabolism, 2020 (ahead of print). © Human Kinetics, Inc.
PY - 2020
Y1 - 2020
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 data sets and may, therefore, introduce computational errors, which are difficult to recognize and correct. In this short commentary, the authors 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 data sets and may, therefore, introduce computational errors, which are difficult to recognize and correct. In this short commentary, the authors 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.
UR - http://www.scopus.com/inward/record.url?scp=85090935785&partnerID=8YFLogxK
U2 - 10.1123/IJSNEM.2020-0150
DO - 10.1123/IJSNEM.2020-0150
M3 - Article
C2 - 32726749
AN - SCOPUS:85090935785
SN - 1526-484X
VL - 30
SP - 374
EP - 381
JO - International Journal of Sport Nutrition and Exercise Metabolism
JF - International Journal of Sport Nutrition and Exercise Metabolism
IS - 5
ER -