Application of the Regression Modeling Method in Assessing Changes and Predicting the Physical Status of the Russian Population
https://doi.org/10.18499/2225-7357-2019-8-1-9-13
Abstract
The aim of the study was to perform regression modeling of the physical status of the Russian population from 1917 to 2017 and to build a prognostic model until 2035.
Material and methods. The methodological approach was based on the methods of correlation and regression analysis, namely, on the construction of linear regression models. Data collection was based on the archival historical documents. Statistical data were processed using SPSS and Excel. The significance level was assumed to be 0.05.
Results. The basic regression models for each of the studied parameters were formulated in the study. In accordance with the given regression models, the authors made a forecast for all the studied parameters up to 2035.
Conclusion. This method can be considered as a promising methodological tool in the study of the dynamic series of relevant parameters in identifying not only the tendency, but also the hidden oscillatory component of the series.
About the Authors
A. N. Timonin
The Federal Research Centre of Biotechnology and Food Safety, Moscow
Russian Federation
Russian Federation
E. A. Burlyaeva
The Federal Research Centre of Biotechnology and Food Safety, Moscow
Russian Federation
Russian Federation
N. S. Nikitin
The Federal Research Centre of Biotechnology and Food Safety, Moscow
Russian Federation
Russian Federation
S. V. Klochkova
I.M. Sechenov First Moscow State Medical University, Moscow
Russian Federation
Russian Federation
D. B. Nikityuk
The Federal Research Centre of Biotechnology and Food Safety, Moscow
Russian Federation
Russian Federation
Dmitrii Nikityuk
Ust'inskii proezd, 2/14, Moscow, 109240
References
1. Владимирский Б. М., Горстко А. Б., Ерусалимский Я. М. Математика. Общий курс. СПб.: Лань; 2008. 532–645 [Vladimirskii BM, Gorstko AB, Erusalimskii YM. Matematika. Obshchii kurs. Saint Petersburg: Lan’; 2008] (in Russian).
2. Еськов В. М., Хадарцев А. А., Филатова О. Е., Хадарцева К. А., Литовченко О. Г. Проблема оценки эффективности лечения на основе кинематической характеристики вектора состояния организма. Вестник новых медицинских технологий. 2015; 22(1):143–152 [Eskov VM, Khadartsev AA, Filatova OE, Khadartseva KA, Litovchenko OG. The Problem of Assessing the Effectiveness of Treatment Based on the Kinematic Characteristics of the State Vector of the Body. Journal of New Medical Technologies. 2015 Feb 11;22(1):143–52] (in Russian). doi: 10.12737/9096
3. Каркищенко Н. Н. Основы биомоделирования. М.: ВПК. 2004. 608 [Karkishchenko NN. Osnovy biomodelirovaniya. Moscow: VPK; 2004] (in Russian).
4. Миронов Б. Н. Историческая социология России: учебник в 2 ч. 2-е изд. М.: Юрайт; 2018; 1: 105–162 [Mironov BN. Istoricheskaya sotsiologiya Rossii: uchebnik. 2nd ed. Moscow: Yurait; 2018.1] (in Russian).
5. Миронов Б. Н. Историческая социология России: учебник в 2 ч. 2-е изд. М.: Юрайт; 2018; 2. 98–126 [Mironov BN. Istoricheskaya sotsiologiya Rossii: uchebnik. 2nd ed. Moscow: Yurait; 2018.2] (in Russian).
6. Миронов Б. Н. Модернизация России в XVIIIXX вв. как конвергенционный проект. Социологические исследования. 2018; 6(410): 91–103 [Mironov BN. Modernization of Russia in XVIIIXX centuries as a convergence project. Sociological Studies (Socis). 2018;6(410):91–103] (in Russian).
7. Миронов Б. Н. Российская империя: от традиции к модерну. Санкт Петербург: Дмитрий Буланин; 2018; 1: 126–265 [Mironov BN. Rossiiskaya imperiya: ot traditsii k modernu. Saint Petersburg: Dmitrii Bulanin; 2018.1] (in Russian).
8. Миронов Б. Н. Российская империя: от традиции к модерну. Санкт Петербург: Дмитрий Буланин; 2018; 2: 201–312 [Mironov BN. Rossiiskaya imperiya: ot traditsii k modernu. Saint Petersburg: Dmitrii Bulanin; 2018.2] (in Russian).
9. Миронов Б. Н. Российская империя: от традиции к модерну. Санкт Петербург: Дмитрий Буланин; 2018; 3: 53–112 [Mironov BN. Rossiiskaya imperiya: ot traditsii k modernu. Saint Petersburg: Dmitrii Bulanin; 2018.3] (in Russian).
10. Миронов Б. Н. Управление этническим многообразием Российской империи. Санкт Петербург. 2017 [Mironov BN. Upravlenie etnicheskim mnogoobraziem Rossiiskoi imperii. Saint Petersburg: Dmitrii Bulanin; 2017] (in Russian).
11. Реброва О. Ю. Статистический анализ медицинских данных. Применение прикладных программ STATISTICA. М.: Медиа-Сфера; 2006. 21 [Rebrova OYu. Statisticheskii analiz meditsinskikh dannykh. Primenenie prikladnykh programm STATISTICA. Moscow: Media-Sfera; 2006] (in Russian).
12. Тарушкин В. Т., Тарушкин П. В., Тарушкина Л. Т. Интервальная и нечеткая линейная регрессия для ВВП России. Успехи современного естествознания. 2007; 5: 81 [Tarushkin VT, Tarushkin PV, Tarushkina LT. Interval’naya i nechetkaya lineinaya regressiya dlya VVP Rossii. Advances in Current Natural Sciences.2007;(5):81] (in Russian).
Review
For citations:
Timonin A.N., Burlyaeva E.A., Nikitin N.S., Klochkova S.V., Nikityuk D.B. Application of the Regression Modeling Method in Assessing Changes and Predicting the Physical Status of the Russian Population. Journal of Anatomy and Histopathology. 2019;8(1):9-13. (In Russ.) https://doi.org/10.18499/2225-7357-2019-8-1-9-13
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