scholarly journals Investigating Contextual Effects on Burglary Risks: A Contextual Effects Model Built Based on Bayesian Spatial Modeling Strategy

2019 ◽  
Vol 8 (11) ◽  
pp. 488 ◽  
Author(s):  
Hongqiang Liu ◽  
Xinyan Zhu ◽  
Dongying Zhang ◽  
Zhen Liu
Keyword(s):  
Spatial Modeling ◽  
Deviance Information Criterion ◽  
Information Criterion ◽  
Contextual Effects ◽  
Independent Variables ◽  
Relative Contribution ◽  
Bayesian Spatial Modeling ◽  
Upper Level ◽  
Modeling Strategy ◽  
The Impact

A contextual effects model, built based on Bayesian spatial modeling strategy, was used to investigate contextual effects on neighborhood burglary risks in Wuhan, China. The contextual effects denote the impact of the upper-level area on the lower-level units of analysis. These effects are often neglected in Bayesian spatial crime analysis. The contextual effects model accounts for the effects of independent variables, overdispersion, spatial autocorrelation, and contextual effects. Both the contextual effects model and the conventional Bayesian spatial model were fitted to our data. Results showed the two models had almost the same deviance information criterion (DIC). Furthermore, they identified the same set of significant independent variables and gave very similar estimates for burglary risks. Nonetheless, the contextual effects model was preferred in the sense that it provides insights into contextual effects on crime risks. Based on the contextual effects model and the map decomposition technique, we identified, worked out, and mapped the relative contribution of the neighborhood characteristics and contextual effects on the overall burglary risks. The research contributes to the increasing literature on modeling crime data by Bayesian spatial approaches.

scholarly journals Effects of treatment classifications in network meta-analysis

2020 ◽  
Vol 1 (1) ◽  
pp. 12-24
Author(s):  
Aiwen Xing ◽  
Lifeng Lin
Keyword(s):  
Meta Analysis ◽  
Deviance Information Criterion ◽  
Model Performance ◽  
Information Criterion ◽  
Credible Interval ◽  
Odds Ratios ◽  
Credible Intervals ◽  
Treatment Comparisons ◽  
Meta Analyses ◽  
The Impact

Objectives Network meta-analysis is a popular tool to simultaneously compare multiple treatments and improve treatment effect estimates. However, no widely accepted guidelines are available to classify the treatment nodes in a network meta-analysis, and the node-making process was often insufficiently reported. We aim at empirically examining the impact of different treatment classifications on network meta-analysis results. Methods We collected nine published network meta-analyses with various disease outcomes; each contained some similar treatments that may be lumped. The Bayesian random-effects model was applied to these network meta-analyses before and after lumping the similar treatments. We estimated the odds ratios and their 95% credible intervals in the original and lumped network meta-analyses. We used the adjusted deviance information criterion to assess the model performance in the lumped network meta-analyses, and used the ratios of credible interval lengths and ratios of odds ratios to quantitatively evaluate the estimates’ changes due to lumping. In addition, the unrelated mean effect model was applied to examine the extents of evidence inconsistency. Results The estimated odds ratios of many treatment comparisons had noticeable changes due to lumping; many of their precisions were substantially improved. The deviance information criterion values reduced after lumping similar treatments in seven (78%) network meta-analyses, indicating better model performance. Substantial evidence inconsistency was detected in only one network meta-analysis. Conclusions Different ways of classifying treatment nodes may substantially affect network meta-analysis results. Including many insufficiently compared treatments and analysing them as separate nodes may not yield more precise estimates. Researchers should report the node-making process in detail and investigate the results’ robustness to different ways of classifying treatments.

Analisis Pengaruh Penerimaan Pajak Daerah Dan Retribusi Daerah Terhadap Pendapatan Asli Daerah Kabupaten/Kota Di Jawa Tengah

2015 ◽  
Vol 2 (1) ◽  
pp. 51-61
Author(s):  
Beta Asteria
Keyword(s):  
Local Government ◽  
Government Budget ◽  
Multiple Regressions ◽  
Independent Variables ◽  
Central Java ◽  
Directorate General ◽  
Fiscal Balance ◽  
Research Findings ◽  
Local Government Budget ◽  
The Impact

This research deals with the impact of Local Tax and Retribution Receipt to Local Government Original Receipt of Regency/City in Central Java from 2008 to 2012. This research utilizes the data of actual of local government budget from Directorate General of Fiscal Balance (Direktorat Jendral Perimbangan Keuangan). Methods of collecting data through census. The number of Regency/City in Central Java are 35. But the data consists of 33 of Regency/City In Central Java from 2008 to 2012. Total of samples are 165. Karanganyar Regency and Sukoharjo Regency were not included as samples of this research because they didn’t report the data of actual of local government budget to Directorate General of Fiscal Balance in 2009.The model used in this research is multiple regressions. The independent variables are Local Tax and Retribution Receipt, the dependent variable is Local Government Original Receipt. The research findings show that Local Tax and Retribution give the significant impact partially and simultaneusly on Local Government Original Receipt at real level 5 percent. All independent variables explain 91,90 percent of the revenue variability while the rest 8,10 percent is explained by other variables.Keywords: Local Tax, Retribution, and Local Government Original Receipt

Faktor-faktor yang Mempengaruhi Belanja Modal pada Kabupaten atau Kota di Provinsi Sumatera Selatan

2018 ◽  
Vol 2 (1) ◽  
pp. 140
Author(s):  
Gogor Mustawa Zais
Keyword(s):  
Multiple Regression ◽  
Capital Expenditure ◽  
Independent Variables ◽  
The Impact

ABSTRACT The objective of this study was to find out and analyze the impact of regional own revenue (PAD), general allocation fund (DAU) and special allocation fund (DAK) on capital expenditure (BM)  in regencies/towns in South  Sumatera Province  for a period of 2010 to 2014. The data were analyzed by using multiple regression. There were four variables in this research. A dependent variable was capital expenditure (BM) and independent variables were regional own revenue (PAD), general allocation fund (DAU) and special allocation fund (DAK). The results showed that the regional own revenue and special allocation fund variables have positive and significant impact on the capital expenditure. This means that the higher the regional own revenue and special allocation fund, the regencies/towns increased the capital expenditure are also higher. General allocation fund do not have a significant effect on the capital expenditure (BM) in regencies/towns in South Sumatera Province for a period of 2010 to 2014

PENGARUH KUALITAS PELAYANAN DAN KEPERCAYAAN TERHADAP LOYALITAS NASABAH PT BANK MANDIRI,Tbk CABANG JAKARTA KELAPA GADING BARAT

2015 ◽  
Vol 3 (3) ◽  
Author(s):  
Imam Wibowo ◽  
Santi Putri Ananda
Keyword(s):  
Linear Regression ◽  
Service Quality ◽  
Multiple Linear Regression ◽  
Analysis Tool ◽  
Positive Contribution ◽  
Homogeneous Population ◽  
Independent Variables ◽  
Research Population ◽  
The Impact

Purpose-To study the impact of the service quality and trust on customers loyalty of PT.Bank Mandiri,Tbk; Kelapa Gading Barat Branch. To improve the customers loyalty there are several factors that can influence them, such as service quality and trust. Methodology/approach-The research population was all customers PT.Bank Mandiri,Tbk;Kelapa Gading Barat Branch.According to the homogeneous population and based on the Gay and Diehl Theory, the samples taken were 50 people. Variables in this investigations consisted of: a).Independent Variables (exogenous): Service Quality (X1) and Trust (X2). b).The dependent variable (endogenous) Customers Loyalty (Y). Analysis tool being used is multiple linear regression which previously conducted validity and realiability. Findings-The result of investigations that service quality and trust simultaneously have a very strong contribution of 75,5% to the customers loyalty, and partially showed that service quality has significant and positive contribution to the customers loyalty of 64,8%. Partially, the trust variable has significant and positive contribution which amounted to 55,9% to the customers loyalty.

Capital Structure and Earnings per Share: An Empirical Analysis of Indian Corporate Sector

2015 ◽  
Vol 5 (3) ◽  
Author(s):  
Harvinder Singh Mand ◽  
Manjit Singh
Keyword(s):  
Capital Structure ◽  
Empirical Analysis ◽  
Corporate Sector ◽  
Independent Variables ◽  
Earnings Per Share ◽  
Panel Data Regression ◽  
Data Regression ◽  
The Impact ◽  
The Relationship ◽  
The Empirical Analysis

This paper intends to measure the impact of capital structure on EPS (earnings per share) in Indian corporate sector. Fifteen control variables along with capital structure have been selected to know their impact on EPS. Panel data regression has been applied to establish the relationship among dependent and independent variables. It is found from the empirical analysis that the relation of capital structure with EPS has been statistically insignificant in Indian corporate sector among all specific industries except telecommunication industry. The results are consistent with Modigliani-Miller approach.

Intervention Modeling

2017 ◽  
Author(s):  
Richard McCleary ◽  
David McDowall ◽  
Bradley J. Bartos
Keyword(s):  
Time Series ◽  
Autocorrelation Function ◽  
Moving Average ◽  
Intervention Model ◽  
Noise Component ◽  
Autoregressive Integrated Moving Average ◽  
Noise Function ◽  
Modeling Strategy ◽  
The Impact ◽  
True Structure

The general AutoRegressive Integrated Moving Average (ARIMA) model can be written as the sum of noise and exogenous components. If an exogenous impact is trivially small, the noise component can be identified with the conventional modeling strategy. If the impact is nontrivial or unknown, the sample AutoCorrelation Function (ACF) will be distorted in unknown ways. Although this problem can be solved most simply when the outcome of interest time series is long and well-behaved, these time series are unfortunately uncommon. The preferred alternative requires that the structure of the intervention is known, allowing the noise function to be identified from the residualized time series. Although few substantive theories specify the “true” structure of the intervention, most specify the dichotomous onset and duration of an impact. Chapter 5 describes this strategy for building an ARIMA intervention model and demonstrates its application to example interventions with abrupt and permanent, gradually accruing, gradually decaying, and complex impacts.

scholarly journals Assessing the Impact of Bank Concentration and Liquidity of Refah Bank Branches on Profitability during the Period1383-190

2014 ◽  
Vol 4 (1) ◽  
pp. 248
Author(s):  
Hossin Ostadi ◽  
Nastran Monsef
Keyword(s):  
Commercial Banks ◽  
Bank Capital ◽  
Factors Affecting ◽  
Bank Branches ◽  
Independent Variables ◽  
Bank Deposits ◽  
The Impact ◽  
Bank Concentration ◽  
Research Period

Profitability is an important factor to show this articledoeswhat is the role of the intermediary bank to collect your savings and allocation of loans.  Given the importance of profitability indicators in this study, the factors affecting the profitability of commercial banks in Iranare analyzedwith emphasis on the degree of centralization and bank deposits. Dependent variable is indicators of profitability (ROE, ROA) and bank deposits, bank size, bank capital, focus on liquidity and banking requirements are independent variables. Correlation analysis and OLS regression are used and the research period is 1381 to 1390 that the country's territory where bank branches.Our results indicate that the effect of bank size on profitability is positive and the increase in bank size on profitability is increased. Impact on the profitability of bank deposits is positive, ie increasing the profitability of bank deposits increased. Finally, the impact of bank concentration on profitability is positive. Increasing the bank's focus profitability increases. Moreover, the results adversely affect the liquidity of the index is profit. 

scholarly journals Be Aware of Burnout! The Role of Changes in Academic Burnout in Problematic Facebook Usage among University Students

2021 ◽  
Vol 18 (15) ◽  
pp. 8055
Author(s):  
Katarzyna Tomaszek ◽  
Agnieszka Muchacka-Cymerman
Keyword(s):  
Regression Coefficient ◽  
Population Sample ◽  
Cross Sectional ◽  
Academic Burnout ◽  
Independent Variables ◽  
Social Motive ◽  
Explained Variance ◽  
The Impact ◽  
The Relationship

Most previous research has examined the relationship between FB addiction and burnout level by conducting cross-sectional studies. Little is known about the impact of changes in burnout on FB addiction in an educational context. Through a two-way longitudinal survey of a student population sample (N = 115), this study examined the influence of changes in academic burnout over time and FB motives and importance (measured at the beginning and the end of the semester) on FB intrusion measured at the end of the academic semester. The findings show that: (1) increases in cynicism and in FB motives and importance significantly predicted time2 FB intrusion; (2) FB importance enhanced the prediction power of changes in the academic burnout total score, exhaustion and personal inefficacy, and reduced the regression coefficient of changes in cynicism; (3) the interaction effects between FB social motive use and changes in academic burnout, as well as between FB importance and personal inefficacy and exhaustion, accounted for a significant change in the explained variance of time2 FB intrusion. About 20–30% of the variance in time2 FB intrusion was explained by all the examined variables and by the interactions between them. The results suggest that changes in academic burnout and FB motives and importance are suppressive variables, as including these variables in the regression model all together changed the significance of the relationship between independent variables and FB intrusion.

scholarly journals The impact of the Nutri-Score front-of-pack nutrition label on purchasing intentions of unprocessed and processed foods: post-hoc analyses from three randomized controlled trials

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Manon Egnell ◽  
Pilar Galan ◽  
Morgane Fialon ◽  
Mathilde Touvier ◽  
Sandrine Péneau ◽  
...  
Keyword(s):  
Randomized Controlled Trials ◽  
Low Income ◽  
P Value ◽  
Controlled Trials ◽  
Nutrition Label ◽  
Randomized Controlled ◽  
Food Purchases ◽  
Relative Contribution ◽  
Processed Products ◽  
The Impact

Abstract Background The Nutri-Score summary graded front-of-pack nutrition label has been identified as an efficient tool to increase the nutritional quality of pre-packed food purchases. However, no study has been conducted to investigate the effect of the Nutri-Score on the shopping cart composition, considering the type of foods. The present paper aims to investigate the effect of the Nutri-Score on the type of food purchases, in terms of the relative contribution of unpacked and pre-packed foods, or the processing degree of foods. Methods Between September 2016 and April 2017, three consecutive randomized controlled trials were conducted in three specific populations – students (N = 1866), low-income individuals (N = 336) and subjects suffering from cardiometabolic diseases (N = 1180) – to investigate the effect of the Nutri-Score on purchasing intentions compared to the Reference Intakes and no label. Using these combined data, the proportion of unpacked products in the shopping carts, as well as the distribution of products across food categories taking into account the degree of processing (NOVA classification) were assessed by trials arm. Results The shopping carts of participants simulating purchases with the Nutri-Score affixed on pre-packed foods contained higher proportion of unpacked products – especially raw fruits and meats, i.e. with no FoPL –, compared to participants purchasing with no label (difference of 5.93 percentage points [3.88–7.99], p-value< 0.0001) or with the Reference Intakes (difference of 5.27[3.25–7.29], p-value< 0.0001). This higher proportion was partly explained by fewer purchases of pre-packed processed and ultra-processed products overall in the Nutri-Score group. Conclusions These findings provide new insights on the positive effect of the Nutri-Score, which appears to decrease purchases in processed products resulting in higher proportions of unprocessed and unpacked foods, in line with public health recommendations.

scholarly journals Optimizing Adsorption of 17α-Ethinylestradiol from Water by Magnetic MXene Using Response Surface Methodology and Adsorption Kinetics, Isotherm, and Thermodynamics Studies

Molecules ◽  
2021 ◽  
Vol 26 (11) ◽  
pp. 3150
Author(s):  
Mengwei Xu ◽  
Chao Huang ◽  
Jing Lu ◽  
Zihan Wu ◽  
Xianxin Zhu ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Quadratic Model ◽  
Adsorption Efficiency ◽  
Process Variables ◽  
Adsorption Time ◽  
Initial Concentration ◽  
Independent Variables ◽  
The Impact ◽  
Adsorbent Dose

Magnetic MXene composite Fe3O4@Ti3C2 was successfully prepared and employed as 17α-ethinylestradiol (EE2) adsorbent from water solution. The response surface methodology was employed to investigate the interactive effects of adsorption parameters (adsorption time, pH of the solution, initial concentration, and the adsorbent dose) and optimize these parameters for obtaining maximum adsorption efficiency of EE2. The significance of independent variables and their interactions were tested by the analysis of variance (ANOVA) and t-test statistics. Optimization of the process variables for maximum adsorption of EE2 by Fe3O4@Ti3C2 was performed using the quadratic model. The model predicted maximum adsorption of 97.08% under the optimum conditions of the independent variables (adsorption time 6.7 h, pH of the solution 6.4, initial EE2 concentration 0.98 mg L−1, and the adsorbent dose 88.9 mg L−1) was very close to the experimental value (95.34%). pH showed the highest level of significance with the percent contribution (63.86%) as compared to other factors. The interactive influences of pH and initial concentration on EE2 adsorption efficiency were significant (p < 0.05). The goodness of fit of the model was checked by the coefficient of determination (R2) between the experimental and predicted values of the response variable. The response surface methodology successfully reflects the impact of various factors and optimized the process variables for EE2 adsorption. The kinetic adsorption data for EE2 fitted well with a pseudo-second-order model, while the equilibrium data followed Langmuir isotherms. Thermodynamic analysis indicated that the adsorption was a spontaneous and endothermic process. Therefore, Fe3O4@Ti3C2 composite present the outstanding capacity to be employed in the remediation of EE2 contaminated wastewaters.

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