Multilevel Structural Modeling Research Articles

Багаторівневі структурні моделі сценаріїв розвитку суб’єктів міжнародного торговельного ринку в аграрному секторі в умовах ризиків

Багаторівневі структурні моделі сценаріїв розвитку суб’єктів міжнародного торговельного ринку в аграрному секторі в умовах ризиків

School Climate, Student Engagement, and Academic Achievement: A Latent Variable, Multilevel Multi-Informant Examination

This study tested the authoritative school climate theory that schools characterized by high structure and student support have greater levels of student engagement and that these factors are associated with higher academic achievement, as indicated by school graduation rates and school performance on state-mandated testing. The model was tested through a multilevel multi-informant structural model on a statewide sample of 60,441 students and 11,442 teachers in 298 high schools. Consistent with the authoritative school climate model, both structure and student support were associated with higher student engagement in schools. Moreover, student engagement was directly associated with academic achievement and operated as an intervening factor. Results provide new evidence that an authoritative school climate is associated with high school academic achievement.

Self-control demands and alcohol-related problems: Within- and between-person associations.

This study tested a multilevel structural model of associations between two aspects of self-control (effortful control and reactivity), self-control demands, alcohol consumption, and alcohol problems and related risk behaviors using daily diary data from 196 young adults (4,177 person-days). Self-control demands were hypothesized to be positively associated with alcohol consumption and alcohol problems and related risk behaviors both within- and between-persons. At the between-person level, self-control demands were hypothesized to mediate the association between trait self-control and alcohol problems and related risk behaviors. At the within-person level, self-control demands had a direct positive effect on alcohol problems and related risk behaviors, over and above alcohol consumption. However, contrary to expectation, self-control demands were inversely associated with alcohol consumption. In contrast, self-control demands were positively associated with alcohol consumption at the between-person level and partially mediated the positive effects of reactivity on consumption and alcohol problems and related risk behaviors. That is, reactivity was associated with higher perceived self-control demands, which in turn predicted higher rates of consumption and alcohol problems and related risk behaviors. Effortful control was not significantly associated with alcohol consumption or self-control demands. The pattern of self-control demand effects at the within-person level suggest that young adults are less likely to drink when struggling to manage their day-to-day behavior, yet if they do drink they are more susceptible to negative consequences. Trait effects suggest that individual differences in self-control may be associated with alcohol use patterns in part attributable to development of, and response to, structured daily routines. (PsycINFO Database Record

Virtual Levels and Role Models: N-Level Structural Equations Model of Reciprocal Ratings Data

ABSTRACTA general latent variable modeling framework called n-Level Structural Equations Modeling (NL-SEM) for dependent data-structures is introduced. NL-SEM is applicable to a wide range of complex multilevel data-structures (e.g., cross-classified, switching membership, etc.). Reciprocal dyadic ratings obtained in round-robin design involve complex set of dependencies that cannot be modeled within Multilevel Modeling (MLM) or Structural Equations Modeling (SEM) frameworks. The Social Relations Model (SRM) for round robin data is used as an example to illustrate key aspects of the NL-SEM framework. NL-SEM introduces novel constructs such as ‘virtual levels’ that allows a natural specification of latent variable SRMs. An empirical application of an explanatory SRM for personality using xxM, a software package implementing NL-SEM is presented. Results show that person perceptions are an integral aspect of personality. Methodological implications of NL-SEM for the analyses of an emerging class of contextual- and relational-SEMs are discussed.

Risk Early Warning Analysis on Vulnerability of Metro Stampede Accident

Based on the statistical analysis of the typical crowded stampede in the past ten years and based on the theory of vulnerability, determine the vulnerable parts of the crowded stampede in the subway station crowd, combined with interpretative structural model, systematically analyze the fragile parts of the crowded stampede at the subway station and find out the relationship between the vulnerable points and establish a multi-level hierarchical subway stampede Structural model. The generality of the characteristics of the Beijing subway crowd was calculated by setting up observation points for escalators and stairways at five high-speed subway stations, use Matlab and Spss to calculate the regression equation, and determine the related relationship between traffic flow, speed and crowd flow and crowded stampede, construct the metro crowding stampede accident risk matrix and put forward different levels of risk warning control measures.

Multilevel Structure of Wheat Starch and Its Relationship to Noodle Eating Qualities.

Although the processing and eating qualities of noodles are largely related to the quality and quantity of wheat protein (gluten), the importance of starch, a major ingredient of wheat flour, is often overlooked. Recent developments on the multilevel structural model of starch have brought new insights into the role of starch for better processing and noodle eating qualities. With critical analysis and discussion, this review outlines the comprehensive relationships between the multilevel (molecular, crystalline, and granular) starch structure, noodle eating qualities, and related physicochemical properties. Further, the major and minor structural features of wheat starch and their contributions toward noodle quality are summarized and presented as a schematic diagram, which shows the effects of starch structure on cooked noodles. These features provide new insights for the scientific community, as well as industry, into the role of starch, along with gluten, on the quality of noodles.

Modeling the Failure Behavior of CFRP Laminates Subjected to Combined Thermal and Mechanical Loadings

This paper proposes a theoretical approach to predict the failure behavior of laminated carbon fiber reinforced polymer (CFRP) under combined thermal and mechanical loadings. Two types of CFRP Laminates, i.e., CCF300/BA9916 and T700/BA9916, are investigated, and TGA tests in both nitrogen and oxidation environments at different heating rates are carried out to obtain the thermal decomposition kinetic parameters of polymer matrix and carbon fiber. Based on the thermal decomposition behavior and a multi-level structure model, the thermal physical properties, mechanical properties and thermal deformations of the laminated composites at high temperatures are obtained. Then substituting thermally degraded properties into constitutive equations of composite materials as macroscopic defects, the damage mode and failure strength of the laminated composite under thermo-mechanical loadings is obtained. Predicted elastic properties and failure strength are compared with experimental results as well as previous models. Effects of heating rates and heating environments through rigorous physical model are considered in the present work. It is found that the heating rate significantly affects the thermal and mechanical properties, the higher the heating rate, the less degraded are the thermo-mechanical properties and failure strength at a given temperature. Young’s modulus and failure strength of T700/BA9916 are higher than those of CCF300/BA9916 at high temperatures, due to the higher volume fraction of carbon fibers, which are less weakened in thermal environment.

CAUSAL FACTORS AND INCREASING THE EFFECTIVENESS GUIDELINES OF LEARNER QUALITIES IN THE OPPORTUNITY EXPANSION SCHOOLS UNDER THE OFFICE OF BASIC EDUCATION COMMISSION

This paper reports in the aims of research study were to investigate the effectiveness level on learner qualities, to determine the causal factors and increasing the effectiveness guidelines of learner qualities, to develop and validate causal model of multi-level factors that influence the effectiveness, and to promote the increasing the effectiveness guidelines of learner qualities in the Opportunity Expansion Schools under the Office of Basic Education Commission were the main purposes. Administrations of the sample consisted of 1,122 teachers who taught and students who sat at the 9 th grade level in 33 schools with the Multistage Random sampling technique. Using both the high quality of the research instruments was validated and reliable with the questionnaire evidence of 0.912, to measure achievement motivation confidence of 0.906 and attitude test with a confidence of 0.908, respectively. Statistically significant analyzed with the descriptive statistics and confirmatory factor analysis (CFA), the multilevel confirmatory factor analysis (MCFA) and structural equation modeling analysis and the study of ways to promote the effectiveness guidelines of learner qualities in the opportunity expansion schools with seminar was based on the expert connoisseurship both quantitative and qualitative data were analyzed. The results of the research findings as the effectiveness guideline level indicated as a whole at the medium level. The causal factors of learning motivation and attitude towards students’ learning outcomes were related at the high level. The causal factors were also found between increasing the effectiveness guidelines of learner qualities and their motivation and attitude towards to their learning outcomes with the learning processes were consistency with the empirical data ( = 120.544, df = 111, P = 0.252, CFI = 0.999, TLI = 0.999, RMSEA = 0.009, SRMR W = 0.029, SRMR B = 0.132, and = 1.086). The effect sizes and influences considered directly as the highest evidence of 0.919, 0.792, and 0.292 with their affecting learning processes, attitudes, achievement motivations at the relation level of 0.01, respectively. The guidelines for learning processes consisted of four main components that followed as: introduction, the thinking processing knowledge, practical schooling guideline, and practical classroom guideline. The assessing experts were evaluated to qualify causal factors and increasing the effectiveness guidelines of learner qualities to their appropriateness and feasibility are provided at the highest level, interestingly. Article visualizations:

The application of the multi-alternative approach in active neural network models

The article refers to the construction of intelligent systems based artificial neuron networks are used. We discuss the basic properties of the non-compliance of artificial neuron networks and their biological prototypes. It is shown here that the main reason for these discrepancies is the structural immutability of the neuron network models in the learning process, that is, their passivity. Based on the modern understanding of the biological nervous system as a structured ensemble of nerve cells, it is proposed to abandon the attempts to simulate its work at the level of the elementary neurons functioning processes and proceed to the reproduction of the information structure of data storage and processing on the basis of the general enough evolutionary principles of multialternativity, i.e. the multi-level structural model, diversity and modularity. The implementation method of these principles is offered, using the faceted memory organization in the neuron network with the rearranging active structure. An example of the implementation of the active facet-type neuron network in the intellectual decision-making system in the conditions of critical events development in the electrical distribution system.

An ancient rule for constructing dodecagonal quasiperiodic patterns

The discovery of complex dodecagonal patterns in historical Islamic architecture is generating a renewed interest into understanding the mathematical principles of traditional Islamic geometry. By employing a compass and a straightedge, ancient craftsmen utilized consistent design principles that allowed for diverse geometric expressions to be realized throughout the ancient world. Derived from these principles, a global multi-level structural model is proposed that provides a general guiding principle for constructing a wide variety of infinite dodecagon-based quasiperiodic patterns.

Pan-Sharpening by Multilevel Interband Structure Modeling

Pan-sharpening is designed to estimate multi-/hyperspectral (MS/HS) images that would have been observed with a sensor at higher resolution. It is a very important issue for many remote sensing and mapping applications. This letter proposes an improved pan-sharpening algorithm based on the ARSIS concept under the assumption that missing information of a low-resolution MS/HS image is linked to the high frequencies of MS/HS and panchromatic (PAN) images. The main object of this letter is to exhibit a multilevel interband structure model that better considers the inherent relationship between the hierarchical structures of MS/HS and PAN images. Several groups of data sets are used to demonstrate the performance of the proposed method. The results show that the proposed method outperforms the existing ARSIS-based and some other fusion techniques and can be extended to HS image sharpening as well.

The Importance of Isomorphism for Conclusions about Homology: A Bayesian Multilevel Structural Equation Modeling Approach with Ordinal Indicators.

We describe a Monte Carlo study examining the impact of assuming item isomorphism (i.e., equivalent construct meaning across levels of analysis) on conclusions about homology (i.e., equivalent structural relations across levels of analysis) under varying degrees of non-isomorphism in the context of ordinal indicator multilevel structural equation models (MSEMs). We focus on the condition where one or more loadings are higher on the between level than on the within level to show that while much past research on homology has ignored the issue of psychometric isomorphism, psychometric isomorphism is in fact critical to valid conclusions about homology. More specifically, when a measurement model with non-isomorphic items occupies an exogenous position in a multilevel structural model and the non-isomorphism of these items is not modeled, the within level exogenous latent variance is under-estimated leading to over-estimation of the within level structural coefficient, while the between level exogenous latent variance is overestimated leading to underestimation of the between structural coefficient. When a measurement model with non-isomorphic items occupies an endogenous position in a multilevel structural model and the non-isomorphism of these items is not modeled, the endogenous within level latent variance is under-estimated leading to under-estimation of the within level structural coefficient while the endogenous between level latent variance is over-estimated leading to over-estimation of the between level structural coefficient. The innovative aspect of this article is demonstrating that even minor violations of psychometric isomorphism render claims of homology untenable. We also show that posterior predictive p-values for ordinal indicator Bayesian MSEMs are insensitive to violations of isomorphism even when they lead to severely biased within and between level structural parameters. We highlight conditions where poor estimation of even correctly specified models rules out empirical examination of isomorphism and homology without taking precautions, for instance, larger Level-2 sample sizes, or using informative priors.

Measurement and structural relations of an authoritative school climate model: A multi-level latent variable investigation

AbstractThis study tested a conceptual model of school climate in which two key elements of an authoritative school, structure and support variables, are associated with student engagement in school and lower levels of peer aggression. Multilevel multivariate structural modeling was conducted in a statewide sample of 48,027 students in 323 public high schools who completed the Authoritative School Climate Survey. As hypothesized, two measures of structure (Disciplinary Structure and Academic Expectations) and two measures of support (Respect for Students and Willingness to Seek Help) were associated with higher student engagement (Affective Engagement and Cognitive Engagement) and lower peer aggression (Prevalence of Teasing and Bullying) on both student and school levels of analysis, controlling for the effects of school demographics (school size, percentage of minority students, and percentage of low income students). These results support the extension of authoritative school climate model to high school and guide further research on the conditions for a positive school climate.

The determinants of work autonomy and employee involvement: A multilevel analysis

Although the effects of work autonomy (WA) and employee involvement (EI) have been largely studied, their determinants, especially at the macro/institutional level, have attracted much less attention. To better understand (a) the extent to which WA and EI are distinct constructs and (b) the factors that explain their respective levels, this article uses the 2010 European Working Conditions Survey to build sound indexes of WA and EI, provide a picture of the level of both constructs in 33 European countries and analyse their predictors through a multilevel structural model. The results show that WA and EI differ in what concerns their macro-level but not micro-level predictors. Whereas union density and generalized trust strongly influence EI, only generalized trust impacts WA. Documenting that generalized trust as a macro-social trait is powerfully associated with organizational choices is a key contribution of the article.

Explicit polarization: a quantum mechanical framework for developing next generation force fields.

ConspectusMolecular mechanical force fields have been successfully used to model condensed-phase and biological systems for a half century. By means of careful parametrization, such classical force fields can be used to provide useful interpretations of experimental findings and predictions of certain properties. Yet, there is a need to further improve computational accuracy for the quantitative prediction of biomolecular interactions and to model properties that depend on the wave functions and not just the energy terms. A new strategy called explicit polarization (X-Pol) has been developed to construct the potential energy surface and wave functions for macromolecular and liquid-phase simulations on the basis of quantum mechanics rather than only using quantum mechanical results to fit analytic force fields. In this spirit, this approach is called a quantum mechanical force field (QMFF).X-Pol is a general fragment method for electronic structure calculations based on the partition of a condensed-phase or macromolecular system into subsystems (“fragments”) to achieve computational efficiency. Here, intrafragment energy and the mutual electronic polarization of interfragment interactions are treated explicitly using quantum mechanics. X-Pol can be used as a general, multilevel electronic structure model for macromolecular systems, and it can also serve as a new-generation force field. As a quantum chemical model, a variational many-body (VMB) expansion approach is used to systematically improve interfragment interactions, including exchange repulsion, charge delocalization, dispersion, and other correlation energies. As a quantum mechanical force field, these energy terms are approximated by empirical functions in the spirit of conventional molecular mechanics. This Account first reviews the formulation of X-Pol, in the full variationally correct version, in the faster embedded version, and with systematic many-body improvements. We discuss illustrative examples involving water clusters (which show the power of two-body corrections), ethylmethylimidazolium acetate ionic liquids (which reveal that the amount of charge transfer between anion and cation is much smaller than what has been assumed in some classical simulations), and a solvated protein in aqueous solution (which shows that the average charge distribution of carbonyl groups along the polypeptide chain depends strongly on their position in the sequence, whereas they are fixed in most classical force fields). The development of QMFFs also offers an opportunity to extend the accuracy of biochemical simulations to areas where classical force fields are often insufficient, especially in the areas of spectroscopy, reactivity, and enzyme catalysis.

Prenatal and perinatal risk factors for developmental coordination disorder in children

To explore the prenatal and perinatal risk factors for developmental coordination disorder (DCD) in children so as to provide a basis for etiological studies and early diagnosis on DCD. Stratified clustered sampling was used to select 160 classes from randomly selected 15 public nursery schools which were distributed throughout the five main districts in Suzhou city. A total of 4 001 children were included in the study. Multilevel logistic regression and structural equation model (SEM) were used to analyze the risk factors of DCD. Results from the multilevel logistic regression model showed that when factors as:class internal clustering, children's gender, age and Kaup value etc., were under control, factors as acute fetal distress, premature and newborn pathological jaundice would be included in the model (OR values were 7.030, 3.374, 1.993, with all their Ps<0.001), and showing these variables were related to DCD. of SEM showed that the related coefficient between 'Minimal Brain Dysfunction' and 'Motor coordination skill' was -0.18 with statistical significance (P < 0.05). It also indicated that the minimal brain dysfunction would negatively impact on the children's motor skill. There were risk factors of DCD noticed during the prenatal and peri-natal periods. Practitioners working at the maternity and child health care areas should improve the skills in assessing and monitoring the prenatal and peri-natal risk factors related to DCD, and to better carry out early screening, diagnosis, treatment and prevention of DCD.

Additive Multilevel Item Structure Models with Random Residuals: Item Modeling for Explanation and Item Generation

An additive multilevel item structure (AMIS) model with random residuals is proposed. The model includes multilevel latent regressions of item discrimination and item difficulty parameters on covariates at both item and item category levels with random residuals at both levels. The AMIS model is useful for explanation purposes and also for prediction purposes as in an item generation context. The parameters can be estimated with an alternating imputation posterior algorithm that makes use of adaptive quadrature, and the performance of this algorithm is evaluated in a simulation study.

Multi-level structural modeling of an offshore wind turbine

Offshore wind turbines are complex structural and mechanical systems located in a highly demanding environment. This paper proposes a multi-level system approach for studying the structural behavior of the support structure of an offshore wind turbine. In accordance with this approach, a proper numerical modeling requires the adoption of a suitable technique in order to organize the qualitative and quantitative assessment in various sub-problems, which can be solved by means of sub-models at different levels of detail, both for the structural behavior and for the simulation of loads. Consequently, in a first place, the effects on the structural response induced by the uncertainty of the parameters used to describe the environmental actions and the finite element model of the structure are inquired. After that, a meso- level FEM model of the blade is adopted in order to obtain the detailed load stress on the blade/hub connection.

ASIAN BUSINESS CYCLE SYNCHRONIZATION

AbstractThis paper develops a multilevel structural factor model to study international output comovement and its underlying driving forces. Our method combines a structural vector autoregression with a multilevel factor model, which helps us understand the economic meaning of the estimated factors. Using quarterly data of real GDP growth covering 9 emerging Asian economies and G‐7 countries, we estimate a global supply factor, a global demand factor, and group supply and demand factors for each group of the economies. We find that although the role of the global factors has intensified over the past 15 years for most of the economies, output fluctuations in Asia have remained less synchronized with the global factor than those in the industrial countries. The Asian regional factors have become increasingly important in tightening the interdependence within the region over time. Therefore, although emerging Asian economies cannot ‘decouple’ completely from the advanced economies, they have, nonetheless, sustained a strong independent cycle among themselves. We also find that synchronized supply shocks contributed more to the observed synchronization in output fluctuations among the Asian economies than demand shocks. This points to the role of productivity enhancement and transmission of other supply shocks through, for example, vertical trade integration, rather than dependence on external demand, as the primary source of business cycle synchronization in emerging Asia.

The global long-range order of quasi-periodic patterns in Islamic architecture

Three decades after their discovery, the unique long-range structure of quasicrystals still poses a perplexing puzzle. The fact that some ancient Islamic patterns share similar quasi-periodic symmetries has prompted several scientists to investigate their underlying geometry and construction methods. However, available structural models depend heavily on local rules and hence they were unable to explain the global long-range order of Islamic quasi-periodic patterns. This paper shows that ancient designers, using simple consecutive geometry, have resolved the complicated long-range principles of quasi-periodic formations. Derived from these principles, a global multi-level structural model is presented that is able to describe the global long-range translational and orientational order of quasi-periodic formations. The proposed model suggests that the position of building units, locally and globally, is defined by one framework, and not tiled based on local rules (matching, overlapping or subdividing). In this way, quasi-periodic formations can grow rapidly ad infinitum without the need for any defects or mismatches. The proposed model, which presents a novel approach to the study of quasi-periodic symmetries, will hopefully provide a deeper understanding of the structure of quasicrystals at an atomic scale, allowing scientists to achieve improved control over their composition and structure.