scholarly journals The Impact of the Community Built Environment on the Walking Times of Residents in a Community in the Downtown Area of Fuzhou

2019 ◽  
Vol 11 (3) ◽  
pp. 691
Author(s):  
Lizhen Zhao ◽  
Zhenjiang Shen ◽  
Yanji Zhang ◽  
Yan Ma
Keyword(s):  
Built Environment ◽  
Regression Models ◽  
Education Level ◽  
Linear Regression Models ◽  
Downtown Area ◽  
Point Of Interest ◽  
Independent Variable ◽  
And Gender ◽  
The Impact ◽  
Walking Time

By means of on-site and network investigation, we collected data relevant to residents of communities, point of interest (POI) data, and land-use data of Fuzhou. We set traffic walking time and leisure walking time as an independent variable, built environment as dependent variable, and gender, age, education level and income level as control variables. Six linear regression models were established using Statistical Product and Service Solutions (SPSS). The results showed that in the 5D (i.e., Density, Diversity, Design, Destination and Distance) elements of the built environment, the density was negatively correlated with the traffic walking time, whereas other elements were positively correlated with the walking time, but the degree of influence was different.

FAKTOR DETERMINAN PENYALURAN KREDIT BANK PERSERO

2018 ◽  
Vol 23 (1) ◽  
pp. 60-71
Author(s):  
Wigiyanti Masodah
Keyword(s):  
Interest Rate ◽  
Linear Regression ◽  
Interest Rates ◽  
Regression Models ◽  
Linear Regression Models ◽  
Negative Impacts ◽  
Main Activity ◽  
The Impact ◽  
The Given ◽  
Multiple Linear Regression Models

Offering credit is the main activity of a Bank. There are some considerations when a bank offers credit, that includes Interest Rates, Inflation, and NPL. This study aims to find out the impact of Variable Interest Rates, Inflation variables and NPL variables on credit disbursed. The object in this study is state-owned banks. The method of analysis in this study uses multiple linear regression models. The results of the study have shown that Interest Rates and NPL gave some negative impacts on the given credit. Meanwhile, Inflation variable does not have a significant effect on credit given. Keywords: Interest Rate, Inflation, NPL, offered Credit.

scholarly journals Non-Parametric Generalized Additive Models as a Tool for Evaluating Policy Interventions

Mathematics ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 299
Author(s):  
Jaime Pinilla ◽  
Miguel Negrín
Keyword(s):  
Linear Regression ◽  
Regression Models ◽  
Linear Trend ◽  
Generalized Additive Models ◽  
Additive Models ◽  
Linear Regression Models ◽  
Non Linear ◽  
Nonlinear Trends ◽  
The Impact ◽  
Non Parametric

The interrupted time series analysis is a quasi-experimental design used to evaluate the effectiveness of an intervention. Segmented linear regression models have been the most used models to carry out this analysis. However, they assume a linear trend that may not be appropriate in many situations. In this paper, we show how generalized additive models (GAMs), a non-parametric regression-based method, can be useful to accommodate nonlinear trends. An analysis with simulated data is carried out to assess the performance of both models. Data were simulated from linear and non-linear (quadratic and cubic) functions. The results of this analysis show how GAMs improve on segmented linear regression models when the trend is non-linear, but they also show a good performance when the trend is linear. A real-life application where the impact of the 2012 Spanish cost-sharing reforms on pharmaceutical prescription is also analyzed. Seasonality and an indicator variable for the stockpiling effect are included as explanatory variables. The segmented linear regression model shows good fit of the data. However, the GAM concludes that the hypothesis of linear trend is rejected. The estimated level shift is similar for both models but the cumulative absolute effect on the number of prescriptions is lower in GAM.

scholarly journals Profile of the Change in Depression during Proton-Pump Inhibitor Therapy in Patients with Gastroesophageal Reflux Disease: Influence of the Mucosal Break

2021 ◽  
Vol 18 (11) ◽  
pp. 5964
Author(s):  
Chia-Liang Wu ◽  
Chien-Lin Chen ◽  
Shu-Hui Wen
Keyword(s):  
Gastroesophageal Reflux Disease ◽  
Gastroesophageal Reflux ◽  
Proton Pump ◽  
Reflux Disease ◽  
Proton Pump Inhibitor Therapy ◽  
Linear Regression Models ◽  
Independent Variable ◽  
The Difference ◽  
Mucosal Break ◽  
The Impact

Given the frequent concomitance between depression and gastroesophageal reflux disease (GERD), it is important to evaluate the change of depression in patients with GERD, especially considering the presence of esophageal mucosal breaks (MB). This study aimed to examine the change in the levels of depression in patients with GERD during proton-pump inhibitors (PPI) therapy. We designed a prospective cohort study to explore the profile of the alteration in depression with respect to the impact of esophageal MB. This study recruited 172 eligible patients with GERD between February 2016 and May 2018. The change in depression was defined as the difference between the respective Taiwanese Depression Questionnaire (TDQ) scores obtained at baseline and after PPI therapy. Multivariate linear regression models were used to estimate the factors associated with the change in depression. The results revealed statistically significant improvements in the TDQ score (mean score: baseline = 13.2, after PPI therapy = 10.9, p < 0.01, Cohen’s d = 0.30) during PPI therapy for GERD. Moreover, the MB was an independent variable associated with changes in the TDQ score [B = 3.31, 95% confidence interval (CI): (1.12, 5.51), p < 0.01] and the improvement in depression [odds ratio = 0.38, 95% CI: (0.17, 0.86), p = 0.02]. Our findings revealed that depressive symptoms improved slightly following PPI therapy. Moreover, MB was an unfavorable prognostic factor for the improvement in depression.

scholarly journals Association between Anxiety, Quality of Life and Academic Performance of the Final-Year-Students in Latvia

2021 ◽  
Vol 18 (11) ◽  
pp. 5784
Author(s):  
Inta Zile ◽  
Ieva Bite ◽  
Indra Krumina ◽  
Valdis Folkmanis ◽  
Lilian Tzivian
Keyword(s):  
Quality Of Life ◽  
Longitudinal Study ◽  
Regression Models ◽  
Linear Regression Models ◽  
Academic Achievements ◽  
School Year ◽  
And Gender ◽  
Type Of School ◽  
Multiple Linear Regression Models

The main objective of this study was to investigate the association between final-year students’ anxiety level and quality of life (QOL) with their academic achievements. A longitudinal study was performed in regular schools and in high-rated gymnasiums at the beginning and at the end of the school year. Multiple linear regression models were built for the association between level of anxiety/QOL with academic achievements. Type of school and gender—but not the level of anxiety—were the main predictors of academic achievements of 287 adolescents (e.g., for mathematics, the effect estimates were: β = −1.71 [95% confidence interval −2.21; −1.21]; β = −0.50 [−0.95; −0.06], β = 0.09 [−0.02; 0.20] for the type of school, gender, and changes in level of anxiety, respectively). To conclude, particular efforts should be made to reduce the level of anxiety in girls, especially those that study in high-rated schools.

scholarly journals Impact of foreign direct investment on economic growth in the world during 1975–2015

2018 ◽  
Vol 20 (91) ◽  
pp. 28-32
Author(s):  
B. B. Brychka
Keyword(s):  
Economic Growth ◽  
Literature Review ◽  
Regression Models ◽  
Trade Openness ◽  
Positive Influence ◽  
Linear Regression Models ◽  
Average Value ◽  
Gdp Growth Rate ◽  
The World ◽  
The Impact

The study is concentrated on examination the impact of FDI on economic growth in the World during 1975–2015. The study consists of four consecutive parts, including introduction, literature review, model and methodology, data, empirical results and conclusion. Each part of the study is focused on its own goals. According to the results of the literature review, there is positive influence of FDI on economic growth in various countries. Economic growth is one of the most important goals of any country. The country image on the international level is dependent on its economic power. Economic growth provides an opportunity to improve the living standards in the country. Most researchers conclude that there is a positive influence of FDI on the countries’ economic growth. However, the impact of FDI is strong in developing countries. Moreover, this relationship is stronger in countries with higher educational and technological level, trade openness and development of the countries’ stock markets. Economists often build regression models to estimate the relationship between the variables. In order to find the impact of FDI on economic growth, we are going to apply linear regression models. We take two variables as indicators of the countries’ economic growth, including current GDP expressed in U.S dollars, and annual GDP growth rate. Taking into account that the World’s GDP in current U.S dollar is a factor variable with the mentioned resulting variables, the regression equation looks as follows: The R-squared of the built model is 0.99, indicating that roughly 100% of changes in the World’s GDP is caused by the chosen factors. As it is seen from the SAS output, the residuals of dependent variable and factors variables are distributed normally among its average value. Thus, non-normality is not observed in the model. Taking into account the coefficients of the factor variables, the log GDP is most sensitive to the changes in trade as a percent of GDP. The log GDP is not quite sensitive to the changes in FDI, since the coefficient of 0.000128 means that increasing of FDI by one unit increase the logarithmic value of GDP by $ 0.000128.

scholarly journals The effect of leadership style and job motivation on the performance of teachers

2021 ◽  
Vol 6 (2) ◽  
pp. 482
Author(s):  
Ramsiah Hiranah ◽  
Happy Fitria ◽  
Achmad Wahidy
Keyword(s):  
Leadership Style ◽  
Regression Models ◽  
Qualitative Data ◽  
Teacher Performance ◽  
Sampling Technique ◽  
Linear Regression Models ◽  
Profound Influence ◽  
Job Motivation ◽  
Study Techniques ◽  
The Impact

The main objective of this study is to define and explain the impact on teacher performance of the leadership style of the head of the Madrasah and job motivation simultaneously. Quantitative analysis is this form of study performed in this study. Techniques for qualitative data collection, questionnaires and documentation..“ Using different linear regression models, it was analyzed. With the help of the version 21 SPSS program. A saturated sampling technique was used in this analysis, where all 49 respondents were tested. From the following conclusions, the findings of data processing and interpretation are drawn: The principal's leadership style has a positive and important effect on the performance of teachers. Motivation for work has a positive and meaningful influence on the success of teachers. At the same time, the leadership style of madrasah principals and job motivation have a profound influence on teacher performance.

scholarly journals Evaluation of determinants of the serological response to the split-inactivated influenza vaccine

2021 ◽  
Author(s):  
Shaohuan Wu ◽  
Ted M. Ross ◽  
Michael A. Carlock ◽  
Elodie Ghedin ◽  
Hyungwon Choi ◽  
...  
Keyword(s):  
Influenza Vaccine ◽  
Regression Models ◽  
Seasonal Influenza ◽  
Vaccine Dose ◽  
Serological Response ◽  
Linear Regression Models ◽  
Negative Effects ◽  
Categorical Response ◽  
One Year ◽  
The Impact

AbstractThe seasonal influenza vaccine is only effective in half of the vaccinated population. To identify determinants of vaccine efficacy, we used data from >1,300 vaccination events to predict the response to vaccination measured as seroconversion as well as hemagglutination inhibition (HAI) levels one year after. We evaluated the predictive capabilities of age, body mass index (BMI), sex, race, comorbidities, prevaccination history, and baseline HAI titers, as well as vaccination month and vaccine dose in multiple linear regression models. The models predicted the categorical response for >75% of the cases in all subsets with one exception. Prior vaccination, baseline titer level, and age were the strongest determinants on seroconversion, all of which had negative effects. Further, we identified a gender effect in older participants, and an effect of vaccination month. BMI played a surprisingly small role, likely due to its correlation with age. Comorbidities, vaccine dose, and race had negligible effects. Our models can generate a new seroconversion score that is corrected for the impact of these factors which can facilitate future biomarker identification.

Baseline Ability Makes a Larger Contribution to Race Performance in High-School Sprinters Than Race Experience or Training Exposure

2016 ◽  
Vol 28 (4) ◽  
pp. 565-571 ◽  
Author(s):  
Kristine E. Lynch ◽  
Alun Thomas ◽  
Bryan Gibson
Keyword(s):  
High School ◽  
Athletic Performance ◽  
Regression Models ◽  
Linear Regression Models ◽  
High School Athletes ◽  
12Th Grade ◽  
And Gender ◽  
Race Performance ◽  
And Training ◽  
Dominant Influence

Purpose:There has long been a debate regarding the importance of talent versus training in athletic performance. In this study we sought to quantify their relative contributions to the race performance of high-school sprinters.Methods:Using race results from the athletic.net website, we identified high-school athletes who participated in at least one race in both 9th and 12th grade in the 100 m, 200 m or 400 m. Athletes with a record of racing before high school were excluded from the analyses. Using separate linear regression models for each event and gender, we analyzed the effect of baseline ability, race experience and training exposure on race time in the 12th grade.Results:35,909 athletes, running a total of 1,627,652 races, contributed to the final analyses. The proportion of variance (R2) in 12th grade race times accounted for by baseline ability ranged from 40% to 51% depending on the event, and was consistently higher for females than males. Race experience explained 3.6–4.4% of the variance and training exposure explained 0.8–1.7%.Conclusion:Although race experience and training exposure impact high-school sprinters’ performance, baseline ability is the dominant influence.

scholarly journals Medication Intake Is Associated with Lower Plasma Carotenoids and Higher Fat-Soluble Vitamins in the Cross-Sectional MARK-AGE Study in Older Individuals

2020 ◽  
Vol 9 (7) ◽  
pp. 2072
Author(s):  
Daniela Weber ◽  
Bastian Kochlik ◽  
Wolfgang Stuetz ◽  
Martijn E. T. Dollé ◽  
Eugène H. J. M. Jansen ◽  
...  
Keyword(s):  
Regression Models ◽  
Plasma Concentrations ◽  
Older Individuals ◽  
Linear Regression Models ◽  
Cross Sectional ◽  
Medication Intake ◽  
The One ◽  
Fat Soluble Vitamins ◽  
The Impact ◽  
Β Carotene

The regular use of medication may interfere with micronutrient metabolism on several levels, such as absorption, turnover rate, and tissue distribution, and this might be amplified during aging. This study evaluates the impact of self-reported medication intake on plasma micronutrients in the MARK-AGE Project, a cross-sectional observational study in 2217 subjects (age- and sex-stratified) aged 35–75 years from six European countries that were grouped according to age. Polypharmacy as possible determinant of micronutrient concentrations was assessed using multiple linear regression models adjusted for age-group, dietary fruit, vegetables, and juice intake, and other confounders. Younger participants reported taking fewer drugs than older participants. Inverse associations between medication intake and lutein (−3.31% difference per increase in medication group), β-carotene (−11.44%), α-carotene (−8.50%) and positive associations with retinol (+2.26%), α-tocopherol/cholesterol (+2.89%) and γ-tocopherol/cholesterol (+1.36%) occurred in multiple adjusted regression models. Combined usage of a higher number of medical drugs was associated with poorer status of carotenoids on the one hand and higher plasma concentrations of retinol, α- and γ-tocopherol on the other hand. Our results raise concerns regarding the safety of drug combinations via the significant and surprisingly multifaceted disturbance of the concentrations of relevant micronutrients.

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