Statistical analysis of medical time series
Abstract
Statistical analysis of data sets is a necessary component of any medical research. Modern methods of mathematical statistics and statistical application suites provide extensive capabilities for analysis of random values. However, when a data set is represented by a series of data ordered by time, or when structure and order of data are essential components of research, special approaches to statistical analysis become necessary.Presented in this article are special statistical methods developed by the authors for analysis of a time series: Time Series Mann-Whitney M-test is an analogue of the known nonparametric Mann-Whitney U-test for two Time Series with an equal number of elements; Nominal Time Series Measure is a statistical estimator of dynamics of a nominal series consisting of «0» (no) and «1» (yes); Time Series Entropy EnRE is a specially developed robust formula for a Time Series, intended for calculation of nonlinear stochastic measure of order or disorder, popular in various researches. Presented methods are accompanied by a detailed demonstration of capacity for statistical analysis of medical Time Series: Analysis of growth dynamics of boys and girls aged 6–7–8 years (data by World Health Organization); analysis of the number of seizures and choice of anti-epileptic drugs (data by The National Society for Epilepsy); Time series entropy EnRE for Detecting Congestive Heart Failure by standard 5-minutesHeart Rate Variability samples (data by Massachusetts Institute of Technology – Boston’s Beth Israel Hospital RR database). It has been noted that, in every case, using the named special methods for statistical analysis of medical Time Series allows one to avoid errors in interpreting results received through statistical methods and substantially increases the accuracy of statistical analysis of medical Time Series
Downloads
References
Mercedes de Onis et al. (2007). Development of a WHO growth reference for school-aged children and adolescents.Bulletin of the World Health Organization, 85, 660–667. https://doi.org/10.2471/BLT.07.043497
Goldberger, A.L. et al. (2000).Physiobank, physiotoolkit, and physionet: Components of a new research resource for complex physiologic signals. Circulation, 101, 215–220. https://doi.org/10.1161/01.cir.101.23.e215
Mann, H.B., Whitney, D.R. (1947). On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other. Annals of Mathematical Statistics, 18(1),50–60. https://doi.org/10.1214/aoms/1177730491.
Neal, A., Parra-Henao, G. (2007).Uses of entropy in medical research.Revista CES MEDICINA, 21(1), 65–75. https://www.redalyc.org/pdf/2611/261120984008.pdf
Boregowda, S., Handy, R., Sleeth, D., Merryweather, A. (2016). Measuring Entropy Change in a Human Physiological System.Journal of Thermodynamics, 1, 1–8. https://doi.org/10.1155/2016/4932710.
Humeau-Heurtier, A. (ed.) (2016).Special Issue «Multiscale Entropy and Its Applications in Medicine and Biology».Entropy, 17–18, 88.
Martynenko, A., Raimondi, G., Budreiko, N. (2019). Robust Entropy Estimator for Heart Rate Variability.Journal of Clinical Informatics and Telemedicine, 14 (15), 67–73. https://doi.org/10.31071/kit2019.15.06
Chengyu, L., Rui, G. (2017).Multiscale Entropy Analysis of the Differential RR Interval Time Series Signal and Its Application in Detecting Congestive Heart Failure.Entropy, 19, 251. https://doi.org/10.3390/e19060251
The Journal of V. N. Karazin Kharkiv National University, series Medicine has following copyright terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work’s authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal’s published version of the work, with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
