A Longitudinal Analysis of the Cognitive Function and Related Factors in Older Adults Using a Multilevel Growth Model

Objectives: The purpose of this study is to examine changes in the cognitive function of the elderly over time and to identify factors affecting the cognitive decline by dividing them into multidimensional factors such as socio-demographic factors, physical and mental health factors, hearing factors, and social contact factors.Methods: This study used the Korean Longitudinal Study of Aging (KLoSA). A multilevel growth model analysis was conducted on 992 elderly people aged 60 or older who had been measured repeatedly seven times from 2006 to 2018.Results: First, the results showed that the cognitive function of the elderly decreased linearly over the years. Second, the initial status of cognitive function decreased as the age increased and as education level and economic condition decreased. The change rate of the cognitive function increased as education level increased. Third, at each time point, depression level had a negative effect on cognitive function, and subjective hearing condition had a negative effect on cognitive function. These influences decreased over time.Conclusion: The lower the education level, the higher the depression level; and the worse the subjective hearing condition, the more likely the elderly are to experience cognitive decline. Because the impact on cognitive function is large in the early stages of depression and hearing loss, it is necessary to detect them early and to make appropriate intervention to prevent cognitive decline.

How Can Industrial Upgrading Improve China's Air Quality —Empirical Analysis Based on Multilevel Growth Model

With the rapid development of industrialization and urbanization in China, the ecological environment has been damaged, especially the air quality, which has brought troubles to the production and life of residents. China has taken various measures to improve air quality, and industrial upgrading is one of the measures. How can industrial upgrading improve air quality? This article uses the urban and provincial data from 2015 to 2018, adopts a multilevel growth model, and draws the following conclusions through empirical analysis.Companies aiming at economic profit and survival will eventually lead to overall industrial upgrades that have little effect on air improvement.Industrial structure adjustment under the effect of industrial upgrading can reduce air pollution and have a significant impact on the improvement of air quality.Industrial upgrading under the effect of time will inevitably reduce the impact on environmental pollution, which is conducive to the improvement of air quality.According to the empirical results, this paper puts forward some suggestions to improve the air quality.

The Effect of Green Characteristics in Reducing the Inventory of Unsold Housing in New Residential Developments—A Case of Gyeonggi Province, in South Korea

This study analyzes the effect of green characteristics on sales of unsold housing stock, using a multilevel growth model, in Gyeonggi Province, South Korea from 2012 to 2018. The green characteristics we estimated are external factors such as the proximity to urban parks and mountain trails located outside the housing complex and internal factors such as whether the area of communal open space within the complex exceeds a certain percentage. The results suggest that potential home-buyers are interested in green space inside rather than outside a housing complex in a suburban setting. Housing complexes with large enough communal open spaces had a 0.094 higher unsold unit ratio than complexes with small communal open spaces, but the surplus decreased more rapidly; the ratio declines by 0.028 per time unit. On the other hand, the results show no statistically significant effects of the distance to external green areas. This might be due to that public urban parks might not be an attraction to residents when forests and/or agricultural fields are in close proximity. The findings of this research will be utilized by construction companies and public institutions holding unsold units in improving their sales performance, not only in South Korea but also in other Asian regions showing a similar housing development pattern.

The effect of voters’ economic perception, Brexit and campaigns on the evaluation of party leaders over time

When and why do voters change their evaluation of party leaders? Voters’ evaluations of party leaders are an increasingly important determinant of electoral behaviour. Which factors influence these evaluations of party leaders? Do voters evaluate party leaders who hold the office of prime minister differently from other party leaders, and do electoral campaigns and issues change these evaluations? I use a multilevel growth model with panel data from the United Kingdom to analyse effects over time. I find that campaigns play a significant role and that voters’ stance on Brexit has a considerable time-varying effect. In addition, voters use economic performance as a valence signal for party leaders holding the office of prime minister and therefore hold them accountable for bad economic performance, especially during election campaigns. These findings show that the personalization of politics may endanger the democratic function of elections to a lesser extent than is commonly feared.

A multilevel analysis of change in hatred of academic work during high school: focusing on the sociocultural background of Korea

Development of academic hatred was examined at four time points across 7 months among 1,015 South Korean high school students. A multilevel growth model showed that the baseline of, and change in, academic hatred varied across individuals and classrooms. At the individual level, gender, parents’ academic pressure, depression, and test anxiety were related to the initial level of academic hatred; gender and test anxiety were associated with a decrease in academic hatred over time. At the class level, lower socio-economic status and higher teachers’ autonomy support were associated with a lower baseline of academic hatred, and higher teachers’ autonomy support decreased academic hatred. Influence mechanisms of protective and risk factors on students’ academic hatred can be considered for strategic and policy interventions.

Assessing Associations Between Changes in Risk and Subsequent Reoffending

Research on recidivism prediction has made important advances, but the same cannot be said of research assessing relationships between risk changes over time or after treatment and subsequent reoffending. In realistic criminal justice situations, data linking changes in risk to recidivism are often fraught with problems due to missing data, irregular intervals in repeat risk assessments, and individual differences such as age and risk levels. Traditional statistical methodologies such as ANCOVA for repeated measures are not suited for analyzing data with these features. We presented four types of statistical modeling techniques that can effectively accommodate these noisier data: conventional regression, conditional regression, two-stage, and joint models. The two-stage models consist of multilevel growth model and conventional regression. The joint models refer to structural equational models. Two example data sets were used to illustrate the application of these methodologies.

The Role of Judges in the Performance of Italian Courts

<p class="ber"><span lang="EN-US">The paper analyses the contribution judges make to the supply of justice in Italian district courts. A </span><span lang="EN-GB">Multilevel Growth Model (</span><span lang="EN-GB">MGM) </span><span lang="EN-US">was applied to the analysis. The results show several differences in productivity in Italian district courts, which may be linked to (i) differences in the contribution of judges (ii) poor rational organization of resources and/or (iii) a</span><span lang="EN-GB"> limited use of case management techniques. </span></p>