scholarly journals Time series analysis of intensive longitudinal data in psychosomatic research: A methodological overview

2020 ◽  
Vol 137 ◽  
pp. 110191
Author(s):  
Sigert Ariens ◽  
Eva Ceulemans ◽  
Janne K. Adolf
2018 ◽  
Author(s):  
Daniel McNeish

Technological advances have led to an increase in intensive longitudinal data and the statistical literature on modeling such data is rapidly expanding, as are software capabilities. Common methods in this area are related to time-series analysis, a framework that historically has received little exposure in psychology. There is a scarcity of psychology-based resources introducing the basic ideas of time-series analysis, especially for datasets featuring multiple people. We begin with basics of N=1 time-series analysis and build up to complex dynamic structural equation models available in the newest release of Mplus. The goal is to provide readers with a basic conceptual understanding of common models, template code, and result interpretation. We provide short descriptions of some advanced issues, but our main priority is to supply readers with a solid knowledge base so that the more advanced literature on the topic is more readily digestible to a larger group of researchers


2018 ◽  
Vol 3 (82) ◽  
Author(s):  
Eurelija Venskaitytė ◽  
Jonas Poderys ◽  
Tadas Česnaitis

Research  background  and  hypothesis.  Traditional  time  series  analysis  techniques,  which  are  also  used  for the analysis of cardiovascular signals, do not reveal the relationship between the  changes in the indices recorded associated with the multiscale and chaotic structure of the tested object, which allows establishing short-and long-term structural and functional changes.Research aim was to reveal the dynamical peculiarities of interactions of cardiovascular system indices while evaluating the functional state of track-and-field athletes and Greco-Roman wrestlers.Research methods. Twenty two subjects participated in the study, their average age of 23.5 ± 1.7 years. During the study standard 12 lead electrocardiograms (ECG) were recorded. The following ECG parameters were used in the study: duration of RR interval taken from the II standard lead, duration of QRS complex, duration of JT interval and amplitude of ST segment taken from the V standard lead.Research  results.  Significant  differences  were  found  between  inter-parametric  connections  of  ST  segment amplitude and JT interval duration at the pre and post-training testing. Observed changes at different hierarchical levels of the body systems revealed inadequate cardiac metabolic processes, leading to changes in the metabolic rate of the myocardium and reflected in the dynamics of all investigated interactions.Discussion and conclusions. It has been found that peculiarities of the interactions of ECG indices interactions show the exposure of the  functional changes in the body at the onset of the workload. The alterations of the functional state of the body and the signs of fatigue, after athletes performed two high intensity training sessions per day, can be assessed using the approach of the evaluation of interactions between functional variables. Therefore the evaluation of the interactions of physiological signals by using time series analysis methods is suitable for the observation of these processes and the functional state of the body.Keywords: electrocardiogram, time series, functional state.


Author(s):  
Addissie Melak

Economic growth of countries is one of the fundamental questions in economics. Most African countries are opening their economies for welcoming of foreign investors. As such Ethiopia, like many African countries took measures to attract and improve foreign direct investment. The purpose of this study is to examine the contribution of foreign direct investment (FDI) for economic growth of Ethiopia over the period of 1981-2013. The study shows an overview of Ethiopian economy and investment environment by the help of descriptive and econometric methods of analysis to establish empirical investigation for the contribution of FDI on Ethiopian economy. OLS method of time series analysis is employed to analyse the data. The stationary of the variables have been checked by using Augmented Dickey Fuller (ADF) Unit Root test and hence they are stationery at first difference. The co- integration test also shows that there is a long run relationship between the dependent and independent variables. Accordingly, the finding of the study shows that FDI, GDP per capita, exchange rate, total investment as percentage of GDP, inflow of FDI stock, trade as percentage of GDP, annual growth rate of GDP and liberalization of the economy have positive impact on Ethiopian GDP. Whereas Gross fixed domestic investment, inflows of FDI and Gross capital formation influence economic growth of Ethiopia negatively. This finding suggests that there should be better policy framework to attract and improve the volume of FDI through creating conducive environment for investment.


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