Multilevel Structural Modeling Research Articles

For Whom Does Education Convey Health Benefits? A Two-Generation and Life Course Approach.

Scholars of social determinants of health have long been interested in how parent's and own education influence health. However, the differing effects of parent's and own education on health-that is, for what socioeconomic group education conveys health benefits-are relatively less studied. Using multilevel marginal structural models, we estimate the heterogeneous effects of parent's and own education over the life course on two health measures. Our analysis considers both parent's and respondent's pre-education covariates, such as childhood health and socioeconomic conditions. We find that the protective effects of college completion against negative health outcomes are remarkably similar regardless of parent's (measured by father's or mother's) education. Meanwhile, parent's education has a larger effect when the average educational level is low in the population. Our results also reveal distinct life course patterns between health measures. We conclude by discussing the implications of our study for understanding the education-health relationship.

A Study of the Factors Influencing the Construction Risk of Steel Truss Bridges Based on the Improved DEMATEL–ISM

To enhance the safety management of steel-truss-bridge construction, an evaluation method based on the improved DEMATEL–ISM was proposed to analyze the risk factors involved in such construction. Decision Making Trial and Evaluation Laboratory (DEMATEL) is a method for systematic factor analysis that utilizes graph-theory and -matrix tools, allowing for the assessment of the existence and strength of relationships between elements by analyzing the logical and direct impact relationships among various elements in a system. The distinctive feature of Interpretative Structural Modeling (ISM) is the decomposing of complex systems into several subsystems (elements) and constructing the system into a multi-level hierarchical structural model through algebraic operations. Specifically, triangular fuzzy numbers are introduced initially to improve the direct influence matrix in the DEMATEL method, thereby reducing the subjectivity of expert evaluations. The degree of influence, influenced degree, centrality degree, and causality degree of each influencing factor are determined and ranked based on the above analysis. In response to the characteristics of top-push construction, 20 key factors were selected from four aspects: “human, material, environment, and management”. The top five identified influencing factors are displacement during pushing (X10), safety-management qualification (X18), local buckling (X14), overturning of steel beams (X13), and collision with bridge piers during guide beam installation (X7). Subsequently, corresponding solutions were proposed for different influencing factors. The results of the study offer targeted measures to enhance the safety management of steel truss bridge construction and provide a reference for accident prevention.

Multilevel atomic structural model for interstratified opal materials

The structure of opal has long fascinated scientists. It occurs in a number of structural states, ranging from amorphous to exhibiting features of stacking disorder. Opal-CT, where C and T signify cristobalite- and tridymite-like interstratification, represents an important link in the length scales between amorphous and crystalline states. However, details about local atomic (dis)order and arrangements extending to long-range stacking faults in opal polymorphs remain incompletely understood. Here, a multilevel modeling approach is reported that considers stacking states in correlation with the abundance of C and T segments as a high-level structural parameter (i.e. not each atom). Optimization accounting for inter-tetrahedral bond lengths and angles and the regularity of the silicate tetrahedra is included as lower levels of structural parameters. Together, a set of parameters with both coarse-grained and atomistic features for different levels of structural details is refined. Structural disorder at the ∼10–100 Å distance scale is evaluated using experimental pair distribution function and diffraction datasets, comparing peak intensities, widths and asymmetry. This work presents a complete multilevel structural description of natural opal-CT and explains many of the unusual features observed in X-ray powder diffraction patterns. This modeling approach can be adopted generally for analyzing layered materials and their assembly into 3D structures.

Analysis of the key influencing factors of China's cross-border e-commerce ecosystem based on the DEMATEL-ISM method.

Systematically analysing the relative importance and hierarchical relationships among the influencing factors of the cross-border e-commerce ecosystem holds rich theoretical value and practical significance for the development of this ecosystem. A total of 19 influencing factors covering four aspects affecting the cross-border e-commerce ecosystem are identified by means of the relevant literature, web pages, research, and discussions with relevant experts and scholars, and the decision-making trial and evaluation laboratory (DEMATEL) and interpretative structural modeling (ISM) method is used to analyse the cause-effect correlation of each factor and to obtain a cause-effect diagram and a multi-level recursive structure model. The results show that three factors, i.e., the e-commerce platform development level, cross-border e-commerce competitiveness, and the cross-border e-commerce transaction scale, have a greater degree of influence on the other influencing factors. Additionally, three factors, i.e., the information development level, GDP, and cross-border online shopping demand, are vulnerable to the influence of the other factors. The level of cross-border e-commerce platform development, cross-border e-commerce competitiveness, and inter-firm competition are the root factors and occupy an important position in the cross-border e-commerce ecosystem as influencing factors and influence the stability of the cross-border e-commerce ecosystem by affecting the other factors.

Evaluation mechanism of local universities’ faculty construction based on SOAP technology

Abstract Accelerating the construction of a high-quality faculty that can adapt to the development of schools is one of the important issues facing universities today. In this paper, we build a comprehensive evaluation system for university teachers based on SOAP technology and hierarchical analysis, adding new security feature elements to the extended namespace of SOAP messages to achieve the system’s ability to handle access control, data confidentiality, and integrity. The system uses hierarchical analysis to hierarchize complex problems, decomposing them into different constituent factors according to the problem and the goals to be achieved and aggregating and combining the factors at different levels according to their interconnectedness and affiliation to form a multi-level analysis structure model. Using this system to analyze the teaching evaluation of college teachers and the six factors of teaching, we get a combined 91.35 and 84.35 for teacher 1 and teacher 2, respectively. From the comparison results, we can see that the teaching effect of Teacher 1 is generally higher than the other five factors, and the teaching attitude of Teacher 1 is lower than the other five factors, which shows that the teaching of Teacher 1 can achieve a good teaching effect. Therefore, the comprehensive evaluation system of college teachers established in this paper based on SOAP technology and hierarchical analysis method has good practicality.

Pengaruh Inovasi Produk, Kualitas Pelayanan Elektronik Dan Citra Merk Terhadap Peningkatan Kepuasan Pelanggan Muslim (Studi pad PT. Shantika Bangun Perkasa)

This study aims to analyze the effect of product innovation, electronic service quality and brand image on increasing customer satisfaction at PT. Shantika Bangun Perkasa, the research model used in this study is a multilevel structural model and the SEM (Structural Equation Modeling) analysis technique operated through the AMOS program is used to test the hypotheses proposed so that in this study a minimum of 100 respondents were used as samples in the study. . So that from the research results it can be stated that there is a positive and significant influence between product innovation and brand image, and there is a positive and significant influence on electronic service quality and brand image and there is a significantly positive influence on brand image in customer satisfaction, and there is a significant positive simultaneous effect on product innovation and also on electronic service quality in customer satisfaction.

Risk Analysis of Airplane Upsets in Flight: An Integrated System Framework and Analysis Methodology

Generally, airplane upsets in flight are considered a precursor to loss of control in flight (LOC-I) accidents, and unfortunately LOC-I is classified as the leading cause of fatal accidents. To further explore the risk factors, causal relationships, and coupling mechanism of airplane upsets, this study proposed a risk analysis model integrating the Interpretative Structural Modeling (ISM) and Bayesian Network (BN). Seventeen key risk factors leading to airplane upsets were identified through the analysis of typical accident cases and the literature. The ISM approach was used to construct the multi-level interpretative structural model of airplane upsets, which could reveal the causal relationship among various risk factors and risk propagation paths. Then, taking 286 accident/incident investigation data as training samples, a data-driven BN model was established using machine learning for dependency intensity assessment and inference analysis. The results reveal that the interaction among risk factors of fatal accidents caused by airplane upsets is more significant than that of non-fatal accidents/incidents. Risk factors such as pilot-induced oscillations/airplane-pilot coupling and non-adherence to Standard Operating Procedures (SOPs)/neglect of cross-validation have a significant effect on airplane upsets in flight among seventeen risk factors. Moreover, this study also identifies the most likely set of risk factors that lead to fatal accidents caused by airplane upsets. The research results have an important theoretical significance and application value for preventing airplane upsets risk.

What is the driving mechanism for the carbon emissions in the building sector? An integrated DEMATEL-ISM model

Clarifying the critical driving factors and the driving mechanism for building carbon emissions is fundamental for carbon peak and carbon neutrality prediction. This study comprehensively identifies 23 representative factors using the literature research and questionnaire survey method. Then, by coupling the decision-making trial and evaluation laboratory (DEMATEL) method and the interpretive structural model (ISM), an integrated DEMATEL-ISM model is developed. The proposed model is further employed to quantify the causal relationships among the factors and establish a multi-level recursive structure model to determine the action mechanism of those drivers. The results show that the 11 cause factors, 12 effect factors and the three most important factors including the economic development level, building end-use energy consumption and end-use energy intensity are identified based on the calculated cause and center degree. Based on the obtained hierarchy, the 23 factors are divided into six levels, among which the population factors, the economic development, the urbanization level and the share of the tertiary sector are the root factors leading to the building carbon emissions. In comparison, policy factors are the most critical inhibiting factors. This study can not only promote the theory and model development for the driving mechanism of carbon emissions, but also help decision-makers develop scientific carbon reduction strategies.

Research on Financial Risk Path Identification of Chinese Energy Enterprises Based on ISM-MICMAC Model

As an important resource commodity related to the global economic lifeline, energy is the material basis for the survival and development of human society. With its identity as a major energy importer and consumer, China must ensure the stability of production and operation of energy enterprises, of which the identification and control of financial risks is of vital importance. Therefore, this paper first uses multiple risk identification methods to identify 9 external and 8 internal key risk factors affecting energy corporate finance in both external and internal dimensions, respectively. Then the ISM and MICMAC methods were used to construct a progressive multi-level structural model of the interactions of key risk factors, and the risk factors were classified by combining the driving power and dependence power of each key risk factor to reveal the interactions among the risk factors. The results showed that 5 partition levels were extracted from 17 risk factors according to ISM model and MICMAC analysis placed all factors into dependent quadrant and independent quadrant. This study reveals the internal relationship between risk factors and is of great significance to the financial risk identification and management of Chinese energy enterprises.

2360. Serum Cholesterol Variability and Mortality in PLWH On Lipid-Lowering Therapy

Abstract Background In people living with HIV (PLWH), consistent use of lipid lowering therapy (LLT) is associated with lower all-cause mortality and use of tenofovir disoproxil fumarate (TDF) with reduced serum cholesterol (C). In the general population, high cholesterol variability (CV) is independently associated with all-cause mortality. We explored the relationship between consistency of LLT/TDF exposure, cholesterol variability, and mortality in PLWH. Methods In a cohort of 15,860 PLWH who achieved undetectable viremia on ART between 2001 and 2011 we used multivariable Cox modeling, stratified by prevalent cardiovascular disease (CVD) to identify predictors of mortality and built multi-level marginal structural models for different LLT/TDF exposure levels based on percentage of days covered (PDC) over the past year, categorizing exposures into low (PDC < 50%), high (50–93%), and consistent (≥94%). The latter two were further subdivided into single and dual exposures for a composite LLT model where we explored effect sizes before and after inclusion of time-updated absolute C values and its 1-year coefficient of variation (CoV). We also examined the relationship between consistency of LLT/TDF use and C variability in a mixed linear model. Results During a median follow-up (f/u) of 4.3 years, there were 2,269 deaths. For 43% of f/u time patients were exposed to TDF, for 13% to non-statin LLT, and for 17% to statins. The hazard ratio (HR) of death for consistent use was 0.38, 95% confidence interval (CI) 0.32–0.45 for TDF, 0.40 (CI:0.28–0.58) for non-statin LLT, and 0.50 (CI:0.40–0.63) for statins (Fig 1). In the composite model, increasing LLT intensity was inversely associated with mortality risk but low C and high CV remained strong independent predictors of death. High HDL C values were protective (Table). The effect sizes for high LLT intensity and high HDL-CV moderately decreased when they were modeled jointly. Compared to unexposed patients, HDL CoV was significantly lower during consistent LLT exposures but higher for patients with low LLT exposure (Fig 2). Conclusion In PLWHA, intensity of LLT exposure is inversely related with all-cause mortality. The highest LLT intensity levels were associated with the lowest HDL-CV. This could serve as a partial explanation for the lower mortality. Disclosures Roger Bedimo, MD, Gilead Sciences: Advisor/Consultant|Janssen: Advisor/Consultant|Merck & Co.: Advisor/Consultant|Merck & Co.: Grant/Research Support|ViiV Healthcare: Advisor/Consultant.

Analysis of Critical Factors for the Entrepreneurship in Industries of the Future Based on DEMATEL-ISM Approach

In the face of the fourth industrial revolution (Industry 4.0 era), in order to cope with the various crises that may come, countries around the world are accelerating the research and development of cutting-edge technologies and promoting and deploying the Industries of the Future in order to seize the high ground in the new round of strategic competition in science and technology. Therefore, entrepreneurship in Industries of the Future has become an urgent problem for governments and enterprises to solve. Entrepreneurship in Industries of the Future is a systematic project with uncertainties, which is dynamically influenced by many factors and has different levels of division among them. Inspired by the form of Porter’s diamond model, this paper constructs a diamond model of the driving mechanism of entrepreneurship in Industries of the Future. Using the DEMATEL-ISM analysis method, each critical factor and influence mechanism of entrepreneurship in Industries of the Future is explored, and a multi-level structural model is established. The study found eight critical factors affecting entrepreneurship in Industries of the Future, among which technology, creation, need, and aspiration are the critical factors, and relevant enterprises and governments should prioritize these influencing factors and deal with them.

Examining the within- and between-person structure of a short form of the positive and negative affect schedule: A multilevel and dynamic approach.

Increasing research uses intensive longitudinal designs to examine antecedents and consequences associated with dynamic affective processes. These studies often rely on the Positive and Negative Affect Schedule (PANAS) to measure affect. Studies assessing the structure of the PANAS are largely cross-sectional in nature and cannot always disentangle within-person variability from between-person differences in affect. A paucity of studies examines structural similarities and differences in affect at the between- and within-person levels, and few have done so with short-form versions of the PANAS. This study investigates the multilevel factor structure of the 10-item PANAS-short-form in a sample of young adults (n = 272) measured daily consecutively over 1 month. Additionally, dynamic relations between positive and negative affect, depressive symptoms, stress, and physical symptoms were examined. Results support a three factors within and two factors between multilevel structural model. Distinct dynamic relations were observed among positive affect, negative affect, stress, and physical symptoms at the within level. Positive and negative affect were correlated with depressive symptoms, stress, and physical symptoms at the between level. Findings indicate the need to disentangle structural components of positive and negative affect when conducting intensive longitudinal studies to examine correlates linked to dynamic affective processes. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Measuring and exploring mental health determinants: a closer look at co-residents’ effect using a multilevel structural equations model

ObjectivePrevious research has demonstrated that individual risk of mental illness is associated with individual, co-resident, and household risk factors. However, modelling the overall effect of these risk factors presents several methodological challenges. In this study we apply a multilevel structural equation model (MSEM) to address some of these challenges and the impact of the different determinants when measuring mental health risk.Study design and settingTwo thousand, one hundred forty-three individuals aged 16 and over from 888 households were analysed based on the Household Survey for England-2014 dataset. We applied MSEM to simultaneously measure and identify psychiatric morbidity determinants while accounting for the dependency among individuals within the same household and the measurement errors.ResultsYounger age, female gender, non-working status, headship of the household, having no close relationship with other people, having history of mental illness and obesity were all significant (p < 0.01) individual risk factors for psychiatric morbidity. A previous history of mental illness in the co-residents, living in a deprived household, and a lack of closeness in relationships among residents were also significant predictors. Model fit indices showed a very good model specification (CFI = 0.987, TLI = 0.980, RMSEA = 0.023, GFI = 0.992).ConclusionMeasuring and addressing mental health determinants should consider not only an individual’s characteristics but also the co-residents and the households in which they live.

The Importance of Different Forms of Social Capital for Happiness in Europe: A Multilevel Structural Equation Model (GSEM)

This paper investigates the effects of different dimensions of social capital ​on happiness of Europeans. Unlike other studies, a categorical principal component analysis (CATPCA) is applied to obtain the dimensions of social capital. The data used come from the ninth wave of the European Social Survey (ESS), year 2018. Happiness is modelled using a multilevel structural equations model (GSEM) by country to study the role of social capital in Europeans' happiness, when controlling for the effect of factors such as gender, unemployment, age, low income, higher education, and living with a partner. Social capital is measured as a multidimensional concept composed of institutional trust, social trust, social ties and voluntary association, civility and sense of belonging, and religiosity. Among the results, we found that the five dimensions that build social capital have a positive impact on happiness. In addition to the positive effects of social capital, the control variables have the expected impact. In a context marked by growing individualism and social isolation, the results of this work can guide policy makers in using the dimensions of social capital to increase the subjective well-being of the population.

The Establishment of Risk Evaluation Index System for Small- and Medium-Sized Agency Bookkeeping Companies.

In recent years, China's economy has developed rapidly; many small companies have risen rapidly; and the tax system has become more and more standardized. Because many small businesses cannot afford to hire full-time accountants, they opt to outsource accounting services, giving small- and medium-sized bookkeeping firms a large market space. However, these opportunities also bring huge operational risks to small- and medium-sized bookkeeping companies. The purpose of this research is to help such enterprises carry out risk management and reduce operational risks. This study uses an analytic hierarchy process and a fuzzy comprehensive assessment approach to successfully combine quantitative and qualitative analysis and create a multilevel analysis structure model of the risk management evaluation index system of small- and medium-sized agency accounting firms. The structural model is verified by a case, the specific risk score of each factor is calculated through the scores of 20 experts, and the importance of risk is judged according to the size of the score, indicating that the structural model is feasible.

ANALYSIS ON INFLUENCING FACTOR OF COST CONTROL OF EPC PROJECT BASED ON THE DEMATEL-ISM

The paper selects the influencing factors of EPC project’s cost control，analyzes and constructs the model of EPC project’s cost control from the point of view of system engineering，and utilizes the integrating DEMATEL—ISM method to study the relationships between the influencing factors and their impacts on cost control. And it gets the multilevel structure model of the influencing factors of EPC project’s cost control. The results show that project construction management level, procurement system, procurement process and standards project content acceptance and project settlement basis are the direct impacting factors of EPC project’s cost control. The study provides a reference of EPC project’s enterprises to improve project management level，effectively control project cost and achieve project management objectives.

How Does Public Health Investment Affect Subjective Well-Being? Empirical Evidence from China.

Maximizing or improving residents’ subjective well-being is one of the basic purposes of public expenditure. As an important component of public expenditure, the impact of public health investment on residents’ subjective well-being receives considerable attention. Regarding the empirical evidence, this paper measures residents’ subjective well-being from the perspectives of overall cognitive happiness, life satisfaction, positive emotions and negative emotions, on the basis of a multi-level structural model of subjective well-being. Factor analysis is used to estimate the subjective well-being of residents at the province level in China, based on the China Family Panel Studies of 2018. In addition, structural equation modeling is employed to explore the impact of public health investment and its regional disparity on the subjective well-being of residents. The empirical results show that public health investment has a significant positive effect on residents’ subjective well-being. Moreover, there is an inverted U-shaped relationship between the regional disparity of public health investment and residents’ subjective well-being. Further study illustrates that the effects of public health investment and its regional disparity on residents’ subjective well-being are heterogeneous by group. Public health investment has a greater impact on the well-being of low- and middle-income, eastern and urban residents than high-income, midwest and rural residents.

Using the ISM Method to Analyze the Relationships between Various Contractor Prequalification Criteria

Construction contractors significantly contribute to the progress and success of projects. Contractor prequalification grants tendering rights only to competent contractors. The bidding process is one of the most critical phases in the construction industry. The project leader must assess the general, technical, and financial information of the contractors to prepare an accurate proposal and select the best contractor. In this study, contractor prequalification is considered, along with the complex relationships between various criteria. ISM is a computational method that involves a qualitative and interpretive approach to solving complex problems based on structural mapping of the connections between attributes and their subsequent transformation into a multilevel structural model. Using ISM, we establish a seven-level hierarchy for various contractor prequalification criteria, which are then grouped into four clusters based on their driving power and dependence power. The result of this study shows that ISM can be used to rank complex contractor prequalification criteria and help managers select a qualified contractor in the construction project bidding process during the strategic planning phase.

Investigating the Effect of the State, Stability, and Change in Deep Approaches to Learning From Kindergarten to Third Grade: A Multilevel Structural Equation Modeling Indicator-Specific Growth Model Approach.

Adopting deep approaches to learning can have a profound impact on learning outcomes. The extent of change in the learning approach could be attributed to the effect of contextual factors (e.g., instruction). After a substantive review, it was found that research interested in investigating the longitudinal effect of deep approaches to learning on learning outcomes were rarely directly concerned with the longitudinal state and trend of the approach itself. Moreover, the limitations of past analytical methods (e.g., using a single indicator to represent deep approaches to learning at each point in time), has not been appropriately acknowledged. This study examined deep approaches to learning in students from kindergarten to third grade using a multilevel structural equation modeling indicator-specific growth model (MSEM-ISGM). This was used to highlight the methodological issues (e.g., consider four indicators separately at each wave) to investigate the effect of context and the states, stability, and changes in deep approaches to learning over this developmental period. The current study comprised of a large-scale sample of 21,490 kindergarteners in kindergarten. Results showed: (1) there was a contextual effect on the longitudinal changes of deep approaches to learning; (2) deep approaches to learning was high but showed considerable individual differences; (3) most indicators relating to deep approaches to learning declined (however, one increased), whereas the trend were relatively stable over time. Corresponding suggestions were proposed at the end of this article.

Factors influencing green transformation efficiency in China's mineral resource-based cities: Method analysis based on IPAT-E and PLS-SEM

China's mineral resource-based cities (MRBCs) face developmental difficulties, including environmental degradation, resource depletion, and economic growth. Therefore, there is an urgent need to explore factors affecting the green transformation efficiency of MRBC, which are expected to provide theoretical support and practical guidance for the formulation of scientific and effective transformation strategies. Based on the IPAT-E model and DEMATEL-ISM method, present study identifies and extracts four influencing factors: population, affluence, technology, and energy, and a multilevel systematic structural model of influencing factors was established. Meanwhile, the partial least squares method was employed to establish a structural equation model using data obtained from 110 MRBCs in China between 2009 and 2018. Factors influencing green transformation efficiency in different groups of MRBCs and the heterogeneity of these cities were analyzed. The results showed that affluence and energy had positive and negative direct and significant effects on transformation efficiency at the national level, respectively. At the same time, technology and population played significant positive roles through different intermediaries. Among them, the negative effect of energy was maximum, and the positive effect of technology was significant. From a regional perspective, the impact of affluence on the east, middle, west, and northeast was significant. The east had the greatest positive effect, whereas the west direction was negative. Furthermore, energy had a significant adverse effect on the central, western, and northeastern regions; however, its influence on the eastern region was not significant. The total indirect effects of technology on the east, middle, and northeast were significantly positive, but the impact on the west was not significant. Similarly, the indirect effect of the population was significant, although negative in the West. Based on city types, the influence of affluence on coal, oil, non-ferrous, and ferrous cities was significantly positive, among which the oil cities experienced the most significant influence. In contrast, the role of energy is significantly negative, as coal cities being the largest. The indirect effects of technology and population were also significantly positive. The former had the least impact on non-ferrous metal cities, while the latter had the greatest impact on oil cities. Therefore, the present study presents a multi-factor and systematic research framework to evaluate the factors influencing the green transformation efficiency of MRBCs, specifically evaluating the impact of various factors on China's MRBC green transformation efficiency for the first time; and proposes diverse strategies for different groups of MRBCs.