WorldWideScience

Sample records for multilevel multimember model

  1. Multilevel modeling using R

    CERN Document Server

    Finch, W Holmes; Kelley, Ken

    2014-01-01

    A powerful tool for analyzing nested designs in a variety of fields, multilevel/hierarchical modeling allows researchers to account for data collected at multiple levels. Multilevel Modeling Using R provides you with a helpful guide to conducting multilevel data modeling using the R software environment.After reviewing standard linear models, the authors present the basics of multilevel models and explain how to fit these models using R. They then show how to employ multilevel modeling with longitudinal data and demonstrate the valuable graphical options in R. The book also describes models fo

  2. Multilevel models for longitudinal data

    OpenAIRE

    Fiona Steele

    2008-01-01

    Repeated measures and repeated events data have a hierarchical structure which can be analysed by using multilevel models. A growth curve model is an example of a multilevel random-coefficients model, whereas a discrete time event history model for recurrent events can be fitted as a multilevel logistic regression model. The paper describes extensions to the basic growth curve model to handle auto-correlated residuals, multiple-indicator latent variables and correlated growth processes, and e...

  3. Multilevel models applications using SAS

    CERN Document Server

    Wang, Jichuan; Fisher, James F

    2011-01-01

    This book covers a broad range of topics about multilevel modeling. The goal is to help readers to understand the basic concepts, theoretical frameworks, and application methods of multilevel modeling. It is at a level also accessible to non-mathematicians, focusing on the methods and applications of various multilevel models and using the widely used statistical software SAS®. Examples are drawn from analysis of real-world research data.

  4. Modeling Multi-Level Systems

    CERN Document Server

    Iordache, Octavian

    2011-01-01

    This book is devoted to modeling of multi-level complex systems, a challenging domain for engineers, researchers and entrepreneurs, confronted with the transition from learning and adaptability to evolvability and autonomy for technologies, devices and problem solving methods. Chapter 1 introduces the multi-scale and multi-level systems and highlights their presence in different domains of science and technology. Methodologies as, random systems, non-Archimedean analysis, category theory and specific techniques as model categorification and integrative closure, are presented in chapter 2. Chapters 3 and 4 describe polystochastic models, PSM, and their developments. Categorical formulation of integrative closure offers the general PSM framework which serves as a flexible guideline for a large variety of multi-level modeling problems. Focusing on chemical engineering, pharmaceutical and environmental case studies, the chapters 5 to 8 analyze mixing, turbulent dispersion and entropy production for multi-scale sy...

  5. Multilevel joint competing risk models

    Science.gov (United States)

    Karunarathna, G. H. S.; Sooriyarachchi, M. R.

    2017-09-01

    Joint modeling approaches are often encountered for different outcomes of competing risk time to event and count in many biomedical and epidemiology studies in the presence of cluster effect. Hospital length of stay (LOS) has been the widely used outcome measure in hospital utilization due to the benchmark measurement for measuring multiple terminations such as discharge, transferred, dead and patients who have not completed the event of interest at the follow up period (censored) during hospitalizations. Competing risk models provide a method of addressing such multiple destinations since classical time to event models yield biased results when there are multiple events. In this study, the concept of joint modeling has been applied to the dengue epidemiology in Sri Lanka, 2006-2008 to assess the relationship between different outcomes of LOS and platelet count of dengue patients with the district cluster effect. Two key approaches have been applied to build up the joint scenario. In the first approach, modeling each competing risk separately using the binary logistic model, treating all other events as censored under the multilevel discrete time to event model, while the platelet counts are assumed to follow a lognormal regression model. The second approach is based on the endogeneity effect in the multilevel competing risks and count model. Model parameters were estimated using maximum likelihood based on the Laplace approximation. Moreover, the study reveals that joint modeling approach yield more precise results compared to fitting two separate univariate models, in terms of AIC (Akaike Information Criterion).

  6. Multi-Level Model

    Directory of Open Access Journals (Sweden)

    Constanta Nicoleta BODEA

    2008-01-01

    Full Text Available Is an original paper, which contains a hierarchical model with three levels, for determining the linearized non-homogeneous and homogeneous credibility premiums at company level, at sector level and at contract level, founded on the relevant covariance relations between the risk premium, the observations and the weighted averages. We give a rather explicit description of the input data for the multi- level hierarchical model used, only to show that in practical situations, there will always be enough data to apply credibility theory to a real insurance portfolio.

  7. Multilevel Models: Conceptual Framework and Applicability

    Directory of Open Access Journals (Sweden)

    Roxana-Otilia-Sonia Hrițcu

    2015-10-01

    Full Text Available Individuals and the social or organizational groups they belong to can be viewed as a hierarchical system situated on different levels. Individuals are situated on the first level of the hierarchy and they are nested together on the higher levels. Individuals interact with the social groups they belong to and are influenced by these groups. Traditional methods that study the relationships between data, like simple regression, do not take into account the hierarchical structure of the data and the effects of a group membership and, hence, results may be invalidated. Unlike standard regression modelling, the multilevel approach takes into account the individuals as well as the groups to which they belong. To take advantage of the multilevel analysis it is important that we recognize the multilevel characteristics of the data. In this article we introduce the outlines of multilevel data and we describe the models that work with such data. We introduce the basic multilevel model, the two-level model: students can be nested into classes, individuals into countries and the general two-level model can be extended very easily to several levels. Multilevel analysis has begun to be extensively used in many research areas. We present the most frequent study areas where multilevel models are used, such as sociological studies, education, psychological research, health studies, demography, epidemiology, biology, environmental studies and entrepreneurship. We support the idea that since hierarchies exist everywhere, multilevel data should be recognized and analyzed properly by using multilevel modelling.

  8. Multilevel modelling: Beyond the basic applications.

    Science.gov (United States)

    Wright, Daniel B; London, Kamala

    2009-05-01

    Over the last 30 years statistical algorithms have been developed to analyse datasets that have a hierarchical/multilevel structure. Particularly within developmental and educational psychology these techniques have become common where the sample has an obvious hierarchical structure, like pupils nested within a classroom. We describe two areas beyond the basic applications of multilevel modelling that are important to psychology: modelling the covariance structure in longitudinal designs and using generalized linear multilevel modelling as an alternative to methods from signal detection theory (SDT). Detailed code for all analyses is described using packages for the freeware R.

  9. Multilevel models in international business research

    NARCIS (Netherlands)

    Peterson, M.F.; Arregle, J-L.; Martin, Xavier

    2012-01-01

    Multiple-level (or mixed linear) modeling (MLM) can simultaneously test hypotheses at several levels of analysis (usually two or three), or control for confounding effects at one level while testing hypotheses at others. Advances in multi-level modeling allow increased precision in quantitative

  10. Generalized latent variable modeling multilevel, longitudinal, and structural equation models

    CERN Document Server

    Skrondal, Anders; Rabe-Hesketh, Sophia

    2004-01-01

    This book unifies and extends latent variable models, including multilevel or generalized linear mixed models, longitudinal or panel models, item response or factor models, latent class or finite mixture models, and structural equation models.

  11. Generalization of Random Intercept Multilevel Models

    Directory of Open Access Journals (Sweden)

    Rehan Ahmad Khan

    2013-10-01

    Full Text Available The concept of random intercept models in a multilevel model developed by Goldstein (1986 has been extended for k-levels. The random variation in intercepts at individual level is marginally split into components by incorporating higher levels of hierarchy in the single level model. So, one can control the random variation in intercepts by incorporating the higher levels in the model.

  12. Analyzing chromatographic data using multilevel modeling.

    Science.gov (United States)

    Wiczling, Paweł

    2018-06-01

    It is relatively easy to collect chromatographic measurements for a large number of analytes, especially with gradient chromatographic methods coupled with mass spectrometry detection. Such data often have a hierarchical or clustered structure. For example, analytes with similar hydrophobicity and dissociation constant tend to be more alike in their retention than a randomly chosen set of analytes. Multilevel models recognize the existence of such data structures by assigning a model for each parameter, with its parameters also estimated from data. In this work, a multilevel model is proposed to describe retention time data obtained from a series of wide linear organic modifier gradients of different gradient duration and different mobile phase pH for a large set of acids and bases. The multilevel model consists of (1) the same deterministic equation describing the relationship between retention time and analyte-specific and instrument-specific parameters, (2) covariance relationships relating various physicochemical properties of the analyte to chromatographically specific parameters through quantitative structure-retention relationship based equations, and (3) stochastic components of intra-analyte and interanalyte variability. The model was implemented in Stan, which provides full Bayesian inference for continuous-variable models through Markov chain Monte Carlo methods. Graphical abstract Relationships between log k and MeOH content for acidic, basic, and neutral compounds with different log P. CI credible interval, PSA polar surface area.

  13. An introduction to multilevel flow modeling

    DEFF Research Database (Denmark)

    Lind, Morten

    2011-01-01

    Multilevel Flow Modeling (MFM) is a methodology for functional modeling of industrial processes on several interconnected levels of means-end and part-whole abstractions. The basic idea of MFM is to represent an industrial plant as a system which provides the means required to serve purposes in i...... in detail by a water mill example. The overall reasoning capabilities of MFM and its basis in cause-effect relations are also explained. The appendix contains an overview of MFM concepts and their definitions....

  14. Plasma simulation studies using multilevel physics models

    International Nuclear Information System (INIS)

    Park, W.; Belova, E.V.; Fu, G.Y.; Tang, X.Z.; Strauss, H.R.; Sugiyama, L.E.

    1999-01-01

    The question of how to proceed toward ever more realistic plasma simulation studies using ever increasing computing power is addressed. The answer presented here is the M3D (Multilevel 3D) project, which has developed a code package with a hierarchy of physics levels that resolve increasingly complete subsets of phase-spaces and are thus increasingly more realistic. The rationale for the multilevel physics models is given. Each physics level is described and examples of its application are given. The existing physics levels are fluid models (3D configuration space), namely magnetohydrodynamic (MHD) and two-fluids; and hybrid models, namely gyrokinetic-energetic-particle/MHD (5D energetic particle phase-space), gyrokinetic-particle-ion/fluid-electron (5D ion phase-space), and full-kinetic-particle-ion/fluid-electron level (6D ion phase-space). Resolving electron phase-space (5D or 6D) remains a future project. Phase-space-fluid models are not used in favor of δf particle models. A practical and accurate nonlinear fluid closure for noncollisional plasmas seems not likely in the near future. copyright 1999 American Institute of Physics

  15. Plasma simulation studies using multilevel physics models

    International Nuclear Information System (INIS)

    Park, W.; Belova, E.V.; Fu, G.Y.

    2000-01-01

    The question of how to proceed toward ever more realistic plasma simulation studies using ever increasing computing power is addressed. The answer presented here is the M3D (Multilevel 3D) project, which has developed a code package with a hierarchy of physics levels that resolve increasingly complete subsets of phase-spaces and are thus increasingly more realistic. The rationale for the multilevel physics models is given. Each physics level is described and examples of its application are given. The existing physics levels are fluid models (3D configuration space), namely magnetohydrodynamic (MHD) and two-fluids; and hybrid models, namely gyrokinetic-energetic-particle/MHD (5D energetic particle phase-space), gyrokinetic-particle-ion/fluid-electron (5D ion phase-space), and full-kinetic-particle-ion/fluid-electron level (6D ion phase-space). Resolving electron phase-space (5D or 6D) remains a future project. Phase-space-fluid models are not used in favor of delta f particle models. A practical and accurate nonlinear fluid closure for noncollisional plasmas seems not likely in the near future

  16. Testing Group Mean Differences of Latent Variables in Multilevel Data Using Multiple-Group Multilevel CFA and Multilevel MIMIC Modeling.

    Science.gov (United States)

    Kim, Eun Sook; Cao, Chunhua

    2015-01-01

    Considering that group comparisons are common in social science, we examined two latent group mean testing methods when groups of interest were either at the between or within level of multilevel data: multiple-group multilevel confirmatory factor analysis (MG ML CFA) and multilevel multiple-indicators multiple-causes modeling (ML MIMIC). The performance of these methods were investigated through three Monte Carlo studies. In Studies 1 and 2, either factor variances or residual variances were manipulated to be heterogeneous between groups. In Study 3, which focused on within-level multiple-group analysis, six different model specifications were considered depending on how to model the intra-class group correlation (i.e., correlation between random effect factors for groups within cluster). The results of simulations generally supported the adequacy of MG ML CFA and ML MIMIC for multiple-group analysis with multilevel data. The two methods did not show any notable difference in the latent group mean testing across three studies. Finally, a demonstration with real data and guidelines in selecting an appropriate approach to multilevel multiple-group analysis are provided.

  17. Consequence Reasoning in Multilevel Flow Modelling

    DEFF Research Database (Denmark)

    Zhang, Xinxin; Lind, Morten; Ravn, Ole

    2013-01-01

    Consequence reasoning is a major element for operation support system to assess the plant situations. The purpose of this paper is to elaborate how Multilevel Flow Models can be used to reason about consequences of disturbances in complex engineering systems. MFM is a modelling methodology...... for representing process knowledge for complex systems. It represents the system by using means-end and part-whole decompositions, and describes not only the purposes and functions of the system but also the causal relations between them. Thus MFM is a tool for causal reasoning. The paper introduces MFM modelling...... syntax and gives detailed reasoning formulas for consequence reasoning. The reasoning formulas offers basis for developing rule-based system to perform consequence reasoning based on MFM, which can be used for alarm design, risk monitoring, and supervision and operation support system design....

  18. Multilevel Modeling of the Performance Variance

    Directory of Open Access Journals (Sweden)

    Alexandre Teixeira Dias

    2012-12-01

    Full Text Available Focusing on the identification of the role played by Industry on the relations between Corporate Strategic Factors and Performance, the hierarchical multilevel modeling method was adopted when measuring and analyzing the relations between the variables that comprise each level of analysis. The adequacy of the multilevel perspective to the study of the proposed relations was identified and the relative importance analysis point out to the lower relevance of industry as a moderator of the effects of corporate strategic factors on performance, when the latter was measured by means of return on assets, and that industry don‟t moderates the relations between corporate strategic factors and Tobin‟s Q. The main conclusions of the research are that the organizations choices in terms of corporate strategy presents a considerable influence and plays a key role on the determination of performance level, but that industry should be considered when analyzing the performance variation despite its role as a moderator or not of the relations between corporate strategic factors and performance.

  19. An introduction to multilevel flow modeling

    International Nuclear Information System (INIS)

    Lind, Morten

    2011-01-01

    Multilevel Flow Modeling (MFM) is a methodology for functional modeling of industrial processes on several interconnected levels of means-end and part-whole abstractions. The basic idea of MFM is to represent an industrial plant as a system which provides the means required to serve purposes in its environment. MFM has a primary focus on plant goals and functions and provide a methodological way of using those concepts to represent complex industrial plant. The paper gives a brief introduction to the historical development, introduces the concepts of MFM and presents the application of the concepts in detail by a water mill example. The overall reasoning capabilities of MFM and its basis in cause-effect relations are also explained. The appendix contains an overview of MFM concepts and their definitions. (author)

  20. Multilevel Higher-Order Item Response Theory Models

    Science.gov (United States)

    Huang, Hung-Yu; Wang, Wen-Chung

    2014-01-01

    In the social sciences, latent traits often have a hierarchical structure, and data can be sampled from multiple levels. Both hierarchical latent traits and multilevel data can occur simultaneously. In this study, we developed a general class of item response theory models to accommodate both hierarchical latent traits and multilevel data. The…

  1. The Sage handbook of multilevel modeling

    CERN Document Server

    Scott, Marc A; Marx, Brian D

    2013-01-01

    Leading contributors combine practical pieces with overviews of the state of the art in the field, making this handbook essential reading for any student or researcher looking to apply multilevel techniques in their own research

  2. Integrity Based Access Control Model for Multilevel XML Document

    Institute of Scientific and Technical Information of China (English)

    HONG Fan; FENG Xue-bin; HUANO Zhi; ZHENG Ming-hui

    2008-01-01

    XML's increasing popularity highlights the security demand for XML documents. A mandatory access control model for XML document is presented on the basis of investigation of the function dependency of XML documents and discussion of the integrity properties of multilevel XML document. Then, the algorithms for decomposition/recovery multilevel XML document into/from single level document are given, and the manipulation rules for typical operations of XQuery and XUpdate: QUERY, INSERT,UPDATE, and REMOVE, are elaborated. The multilevel XML document access model can meet the requirement of sensitive information processing application.

  3. Measuring Collective Efficacy: A Multilevel Measurement Model for Nested Data

    Science.gov (United States)

    Matsueda, Ross L.; Drakulich, Kevin M.

    2016-01-01

    This article specifies a multilevel measurement model for survey response when data are nested. The model includes a test-retest model of reliability, a confirmatory factor model of inter-item reliability with item-specific bias effects, an individual-level model of the biasing effects due to respondent characteristics, and a neighborhood-level…

  4. Mathematical model comparing of the multi-level economics systems

    Science.gov (United States)

    Brykalov, S. M.; Kryanev, A. V.

    2017-12-01

    The mathematical model (scheme) of a multi-level comparison of the economic system, characterized by the system of indices, is worked out. In the mathematical model of the multi-level comparison of the economic systems, the indicators of peer review and forecasting of the economic system under consideration can be used. The model can take into account the uncertainty in the estimated values of the parameters or expert estimations. The model uses the multi-criteria approach based on the Pareto solutions.

  5. Multilevel Modeling: Overview and Applications to Research in Counseling Psychology

    Science.gov (United States)

    Kahn, Jeffrey H.

    2011-01-01

    Multilevel modeling (MLM) is rapidly becoming the standard method of analyzing nested data, for example, data from students within multiple schools, data on multiple clients seen by a smaller number of therapists, and even longitudinal data. Although MLM analyses are likely to increase in frequency in counseling psychology research, many readers…

  6. Determinants of Academic Entrepreneurship Behavior: A Multilevel Model

    Science.gov (United States)

    Llano, Joseph Anthony

    2010-01-01

    It is well established that universities encourage the acquisition and dissemination of new knowledge among university community members and beyond. However, what is less well understood is how universities encourage entrepreneurial (opportunity discovery, evaluation, and exploiting) behavior. This research investigated a multilevel model of the…

  7. Attachment, Autonomy, and Emotional Reliance: A Multilevel Model

    Science.gov (United States)

    Lynch, Martin F.

    2013-01-01

    This article reports a test of a multilevel model investigating how attachment security and autonomy contribute to emotional reliance, or the willingness to seek interpersonal support. Participants ("N" = 247) completed online measures of attachment, autonomy, emotional reliance, and vitality with respect to several everyday…

  8. Studying historical occupational careers with multilevel growth models

    NARCIS (Netherlands)

    Schulz, W.; Maas, I.

    2010-01-01

    In this article we propose to study occupational careers with historical data by using multilevel growth models. Historical career data are often characterized by a lack of information on the timing of occupational changes and by different numbers of observations of occupations per individual.

  9. Application of Multilevel Models to Morphometric Data. Part 2. Correlations

    Directory of Open Access Journals (Sweden)

    O. Tsybrovskyy

    2003-01-01

    Full Text Available Multilevel organization of morphometric data (cells are “nested” within patients requires special methods for studying correlations between karyometric features. The most distinct feature of these methods is that separate correlation (covariance matrices are produced for every level in the hierarchy. In karyometric research, the cell‐level (i.e., within‐tumor correlations seem to be of major interest. Beside their biological importance, these correlation coefficients (CC are compulsory when dimensionality reduction is required. Using MLwiN, a dedicated program for multilevel modeling, we show how to use multivariate multilevel models (MMM to obtain and interpret CC in each of the levels. A comparison with two usual, “single‐level” statistics shows that MMM represent the only way to obtain correct cell‐level correlation coefficients. The summary statistics method (take average values across each patient produces patient‐level CC only, and the “pooling” method (merge all cells together and ignore patients as units of analysis yields incorrect CC at all. We conclude that multilevel modeling is an indispensable tool for studying correlations between morphometric variables.

  10. Comparisons of Multilevel Modeling and Structural Equation Modeling Approaches to Actor-Partner Interdependence Model.

    Science.gov (United States)

    Hong, Sehee; Kim, Soyoung

    2018-01-01

    There are basically two modeling approaches applicable to analyzing an actor-partner interdependence model: the multilevel modeling (hierarchical linear model) and the structural equation modeling. This article explains how to use these two models in analyzing an actor-partner interdependence model and how these two approaches work differently. As an empirical example, marital conflict data were used to analyze an actor-partner interdependence model. The multilevel modeling and the structural equation modeling produced virtually identical estimates for a basic model. However, the structural equation modeling approach allowed more realistic assumptions on measurement errors and factor loadings, rendering better model fit indices.

  11. Multilevel flow modelling of process plant for diagnosis and control

    International Nuclear Information System (INIS)

    Lind, M.

    1982-08-01

    The paper describes the multilevel flow modelling methodology which can be used to construct functional models of energy and material processing systems. The models describe mass and energy flow topology on different levels of abstraction and represent the hierarchical functional structure of complex systems. A model of a nuclear power plant (PWR) is presented in the paper for illustration. Due to the consistency of the method, multilevel flow models provide specifications of plant goals and functions and may be used as a basis for design of computer-based support systems for the plant operator. Plant control requirements can be derived from the models and due to independence of the actual controller implementation the method may be used as basic for design of control strategies and for the allocation of control tasks to the computer and the plant operator. (author)

  12. Multilevel Flow Modelling of Process Plant for Diagnosis and Control

    DEFF Research Database (Denmark)

    Lind, Morten

    1982-01-01

    The paper describes the multilevel flow modelling methodology which can be used to construct functional models of energy and material processing systems. The models describe mass and energy flow topology on different levels of abstraction and represent the hierarchical functional structure...... of complex systems. A model of a nuclear power plant (PWR) is presented in the paper for illustration. Due to the consistency of the method, multilevel flow models provide specifications of plant goals and functions and may be used as a basis for design of computer-based support systems for the plant...... operator. Plant control requirements can be derived from the models and due to independence of the actual controller implementation the method may be used as a basis for design of control strategies and for the allocation of control tasks to the computer and the plant operator....

  13. [How to fit and interpret multilevel models using SPSS].

    Science.gov (United States)

    Pardo, Antonio; Ruiz, Miguel A; San Martín, Rafael

    2007-05-01

    Hierarchic or multilevel models are used to analyse data when cases belong to known groups and sample units are selected both from the individual level and from the group level. In this work, the multilevel models most commonly discussed in the statistic literature are described, explaining how to fit these models using the SPSS program (any version as of the 11 th ) and how to interpret the outcomes of the analysis. Five particular models are described, fitted, and interpreted: (1) one-way analysis of variance with random effects, (2) regression analysis with means-as-outcomes, (3) one-way analysis of covariance with random effects, (4) regression analysis with random coefficients, and (5) regression analysis with means- and slopes-as-outcomes. All models are explained, trying to make them understandable to researchers in health and behaviour sciences.

  14. Multilevel Flow Modeling for Nuclear Power Plant Diagnosis

    DEFF Research Database (Denmark)

    Gola, G; Lind, Morten; Thunem, Harald P-J

    2012-01-01

    , especially if extended to the whole plant. Monitoring plant performances by means of data reconciliation techniques has proved successful to detect anomalies during operation, provide early warnings and eventually schedule maintenance. At the same time, the large amount of information provided by large...... detected anomalies. The combination of a data reconciliation system and the Multilevel Flow Modeling approach is illustrated with regard to the secondary loop of the Loviisa-2 Pressurized Water Reactor located in Finland....

  15. Multi-level decision making models, methods and applications

    CERN Document Server

    Zhang, Guangquan; Gao, Ya

    2015-01-01

    This monograph presents new developments in multi-level decision-making theory, technique and method in both modeling and solution issues. It especially presents how a decision support system can support managers in reaching a solution to a multi-level decision problem in practice. This monograph combines decision theories, methods, algorithms and applications effectively. It discusses in detail the models and solution algorithms of each issue of bi-level and tri-level decision-making, such as multi-leaders, multi-followers, multi-objectives, rule-set-based, and fuzzy parameters. Potential readers include organizational managers and practicing professionals, who can use the methods and software provided to solve their real decision problems; PhD students and researchers in the areas of bi-level and multi-level decision-making and decision support systems; students at an advanced undergraduate, master’s level in information systems, business administration, or the application of computer science.  

  16. Knowledge Representation Using Multilevel Flow Model in Expert System

    International Nuclear Information System (INIS)

    Wang, Wenlin; Yang, Ming

    2015-01-01

    As for the knowledge representation, of course, there are a great many methods available for knowledge representation. These include frames, causal models, and many others. This paper presents a novel method called Multilevel Flow Model (MFM), which is used for knowledge representation in G2 expert system. Knowledge representation plays a vital role in constructing knowledge bases. Moreover, it also has impact on building of generic fault model as well as knowledge bases. The MFM is particularly useful to describe system knowledge concisely as domain map in expert system when domain experts are not available

  17. Knowledge Representation Using Multilevel Flow Model in Expert System

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Wenlin; Yang, Ming [Harbin Engineering University, Harbin (China)

    2015-05-15

    As for the knowledge representation, of course, there are a great many methods available for knowledge representation. These include frames, causal models, and many others. This paper presents a novel method called Multilevel Flow Model (MFM), which is used for knowledge representation in G2 expert system. Knowledge representation plays a vital role in constructing knowledge bases. Moreover, it also has impact on building of generic fault model as well as knowledge bases. The MFM is particularly useful to describe system knowledge concisely as domain map in expert system when domain experts are not available.

  18. Studying historical occupational careers with multilevel growth models

    Directory of Open Access Journals (Sweden)

    Wiebke Schulz

    2010-10-01

    Full Text Available In this article we propose to study occupational careers with historical data by using multilevel growth models. Historical career data are often characterized by a lack of information on the timing of occupational changes and by different numbers of observations of occupations per individual. Growth models can handle these specificities, whereas standard methods, such as event history analyses can't. We illustrate the use of growth models by studying career success of men and women, using data from the Historical Sample of the Netherlands. The results show that the method is applicable to male careers, but causes trouble when analyzing female careers.

  19. Multilevel model of safety climate for furniture industries.

    Science.gov (United States)

    Rodrigues, Matilde A; Arezes, Pedro M; Leão, Celina P

    2015-01-01

    Furniture companies can analyze their safety status using quantitative measures. However, the data needed are not always available and the number of accidents is under-reported. Safety climate scales may be an alternative. However, there are no validated Portuguese scales that account for the specific attributes of the furniture sector. The current study aims to develop and validate an instrument that uses a multilevel structure to measure the safety climate of the Portuguese furniture industry. The Safety Climate in Wood Industries (SCWI) model was developed and applied to the safety climate analysis using three different scales: organizational, group and individual. A multilevel exploratory factor analysis was performed to analyze the factorial structure. The studied companies' safety conditions were also analyzed. Different factorial structures were found between and within levels. In general, the results show the presence of a group-level safety climate. The scores of safety climates are directly and positively related to companies' safety conditions; the organizational scale is the one that best reflects the actual safety conditions. The SCWI instrument allows for the identification of different safety climates in groups that comprise the same furniture company and it seems to reflect those groups' safety conditions. The study also demonstrates the need for a multilevel analysis of the studied instrument.

  20. Multilevel flow modeling of Monju Nuclear Power Plant

    DEFF Research Database (Denmark)

    Lind, Morten; Yoshikawa, Hidekazu; Jørgensen, Sten Bay

    2011-01-01

    Multilevel Flow Modeling is a method for modeling complex processes on multiple levels of means-end and part-whole abstraction. The modeling method has been applied on a wide range of processes including power plants, chemical engineering plants and power systems. The modeling method is supported...... with reasoning tools for fault diagnosis and control and is proposed to be used as a central knowledge base giving integrated support in diagnosis and maintenance tasks. Recent developments of MFM include the introduction of concepts for representation of control functions and the relations between plant...... functions and structure. The paper will describe how MFM can be used to represent the goals and functions of the Japanese Monju Nuclear Power Plant. A detailed explanation will be given of the model describing the relations between levels of goal, function and structural. Furthermore, it will be explained...

  1. Lipid Processing Technology: Building a Multilevel Modeling Network

    DEFF Research Database (Denmark)

    Diaz Tovar, Carlos Axel; Mustaffa, Azizul Azri; Hukkerikar, Amol

    2011-01-01

    of a computer aided multilevel modeling network consisting a collection of new and adopted models, methods and tools for the systematic design and analysis of processes employing lipid technology. This is achieved by decomposing the problem into four levels of modeling: 1. pure component properties; 2. mixtures...... and phase behavior; 3. unit operations; and 4. process synthesis and design. The methods and tools in each level include: For the first level, a lipid‐database of collected experimental data from the open literature, confidential data from industry and generated data from validated predictive property...... of these unit operations with respect to performance parameters such as minimum total cost, product yield improvement, operability etc., and process intensification for the retrofit of existing biofuel plants. In the fourth level the information and models developed are used as building blocks...

  2. Detailed Modeling and Evaluation of a Scalable Multilevel Checkpointing System

    Energy Technology Data Exchange (ETDEWEB)

    Mohror, Kathryn [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Moody, Adam [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Bronevetsky, Greg [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); de Supinski, Bronis R. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2014-09-01

    High-performance computing (HPC) systems are growing more powerful by utilizing more components. As the system mean time before failure correspondingly drops, applications must checkpoint frequently to make progress. But, at scale, the cost of checkpointing becomes prohibitive. A solution to this problem is multilevel checkpointing, which employs multiple types of checkpoints in a single run. Moreover, lightweight checkpoints can handle the most common failure modes, while more expensive checkpoints can handle severe failures. We designed a multilevel checkpointing library, the Scalable Checkpoint/Restart (SCR) library, that writes lightweight checkpoints to node-local storage in addition to the parallel file system. We present probabilistic Markov models of SCR's performance. We show that on future large-scale systems, SCR can lead to a gain in machine efficiency of up to 35 percent, and reduce the load on the parallel file system by a factor of two. In addition, we predict that checkpoint scavenging, or only writing checkpoints to the parallel file system on application termination, can reduce the load on the parallel file system by 20 × on today's systems and still maintain high application efficiency.

  3. Three essays on multi-level optimization models and applications

    Science.gov (United States)

    Rahdar, Mohammad

    The general form of a multi-level mathematical programming problem is a set of nested optimization problems, in which each level controls a series of decision variables independently. However, the value of decision variables may also impact the objective function of other levels. A two-level model is called a bilevel model and can be considered as a Stackelberg game with a leader and a follower. The leader anticipates the response of the follower and optimizes its objective function, and then the follower reacts to the leader's action. The multi-level decision-making model has many real-world applications such as government decisions, energy policies, market economy, network design, etc. However, there is a lack of capable algorithms to solve medium and large scale these types of problems. The dissertation is devoted to both theoretical research and applications of multi-level mathematical programming models, which consists of three parts, each in a paper format. The first part studies the renewable energy portfolio under two major renewable energy policies. The potential competition for biomass for the growth of the renewable energy portfolio in the United States and other interactions between two policies over the next twenty years are investigated. This problem mainly has two levels of decision makers: the government/policy makers and biofuel producers/electricity generators/farmers. We focus on the lower-level problem to predict the amount of capacity expansions, fuel production, and power generation. In the second part, we address uncertainty over demand and lead time in a multi-stage mathematical programming problem. We propose a two-stage tri-level optimization model in the concept of rolling horizon approach to reducing the dimensionality of the multi-stage problem. In the third part of the dissertation, we introduce a new branch and bound algorithm to solve bilevel linear programming problems. The total time is reduced by solving a smaller relaxation

  4. The problematic estimation of "imitation effects" in multilevel models

    Directory of Open Access Journals (Sweden)

    2003-09-01

    Full Text Available It seems plausible that a person's demographic behaviour may be influenced by that among other people in the community, for example because of an inclination to imitate. When estimating multilevel models from clustered individual data, some investigators might perhaps feel tempted to try to capture this effect by simply including on the right-hand side the average of the dependent variable, constructed by aggregation within the clusters. However, such modelling must be avoided. According to simulation experiments based on real fertility data from India, the estimated effect of this obviously endogenous variable can be very different from the true effect. Also the other community effect estimates can be strongly biased. An "imitation effect" can only be estimated under very special assumptions that in practice will be hard to defend.

  5. Modelling and Validating a Deoiling Hydrocyclone for Fault Diagnosis using Multilevel Flow Modeling

    DEFF Research Database (Denmark)

    Nielsen, Emil Krabbe; Bram, Mads Valentin; Frutiger, Jerome

    a procedure to measure model performance, according to diagnosticrequirements, to ensure reliability during operation. A simple procedure is proposed for validatingand evaluating Multilevel Flow Modeling models. For this purpose expert statements, a dynamicprocess simulation in K-spice, and pilot plant...

  6. A water treatment case study for quantifying model performance with multilevel flow modeling

    Directory of Open Access Journals (Sweden)

    Emil K. Nielsen

    2018-05-01

    Full Text Available Decision support systems are a key focus of research on developing control rooms to aid operators in making reliable decisions and reducing incidents caused by human errors. For this purpose, models of complex systems can be developed to diagnose causes or consequences for specific alarms. Models applied in safety systems of complex and safety-critical systems require rigorous and reliable model building and testing. Multilevel flow modeling is a qualitative and discrete method for diagnosing faults and has previously only been validated by subjective and qualitative means. To ensure reliability during operation, this work aims to synthesize a procedure to measure model performance according to diagnostic requirements. A simple procedure is proposed for validating and evaluating the concept of multilevel flow modeling. For this purpose, expert statements, dynamic process simulations, and pilot plant experiments are used for validation of simple multilevel flow modeling models of a hydrocyclone unit for oil removal from produced water. Keywords: Fault Diagnosis, Model Validation, Multilevel Flow Modeling, Produced Water Treatment

  7. Multilevel method for modeling large-scale networks.

    Energy Technology Data Exchange (ETDEWEB)

    Safro, I. M. (Mathematics and Computer Science)

    2012-02-24

    researchers. We propose to develop multilevel methods to model complex networks. The key point of the proposed strategy is that it will help to preserve part of the unknown structural attributes by guaranteeing the similar behavior of the real and artificial model on different scales.

  8. Multilevel structural equation models for assessing moderation within and across levels of analysis.

    Science.gov (United States)

    Preacher, Kristopher J; Zhang, Zhen; Zyphur, Michael J

    2016-06-01

    Social scientists are increasingly interested in multilevel hypotheses, data, and statistical models as well as moderation or interactions among predictors. The result is a focus on hypotheses and tests of multilevel moderation within and across levels of analysis. Unfortunately, existing approaches to multilevel moderation have a variety of shortcomings, including conflated effects across levels of analysis and bias due to using observed cluster averages instead of latent variables (i.e., "random intercepts") to represent higher-level constructs. To overcome these problems and elucidate the nature of multilevel moderation effects, we introduce a multilevel structural equation modeling (MSEM) logic that clarifies the nature of the problems with existing practices and remedies them with latent variable interactions. This remedy uses random coefficients and/or latent moderated structural equations (LMS) for unbiased tests of multilevel moderation. We describe our approach and provide an example using the publicly available High School and Beyond data with Mplus syntax in Appendix. Our MSEM method eliminates problems of conflated multilevel effects and reduces bias in parameter estimates while offering a coherent framework for conceptualizing and testing multilevel moderation effects. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  9. Multi-level and hybrid modelling approaches for systems biology.

    Science.gov (United States)

    Bardini, R; Politano, G; Benso, A; Di Carlo, S

    2017-01-01

    During the last decades, high-throughput techniques allowed for the extraction of a huge amount of data from biological systems, unveiling more of their underling complexity. Biological systems encompass a wide range of space and time scales, functioning according to flexible hierarchies of mechanisms making an intertwined and dynamic interplay of regulations. This becomes particularly evident in processes such as ontogenesis, where regulative assets change according to process context and timing, making structural phenotype and architectural complexities emerge from a single cell, through local interactions. The information collected from biological systems are naturally organized according to the functional levels composing the system itself. In systems biology, biological information often comes from overlapping but different scientific domains, each one having its own way of representing phenomena under study. That is, the different parts of the system to be modelled may be described with different formalisms. For a model to have improved accuracy and capability for making a good knowledge base, it is good to comprise different system levels, suitably handling the relative formalisms. Models which are both multi-level and hybrid satisfy both these requirements, making a very useful tool in computational systems biology. This paper reviews some of the main contributions in this field.

  10. Estimating the Multilevel Rasch Model: With the lme4 Package

    Directory of Open Access Journals (Sweden)

    Harold Doran

    2007-02-01

    Full Text Available Traditional Rasch estimation of the item and student parameters via marginal maximum likelihood, joint maximum likelihood or conditional maximum likelihood, assume individuals in clustered settings are uncorrelated and items within a test that share a grouping structure are also uncorrelated. These assumptions are often violated, particularly in educational testing situations, in which students are grouped into classrooms and many test items share a common grouping structure, such as a content strand or a reading passage. Consequently, one possible approach is to explicitly recognize the clustered nature of the data and directly incorporate random effects to account for the various dependencies. This article demonstrates how the multilevel Rasch model can be estimated using the functions in R for mixed-effects models with crossed or partially crossed random effects. We demonstrate how to model the following hierarchical data structures: a individuals clustered in similar settings (e.g., classrooms, schools, b items nested within a particular group (such as a content strand or a reading passage, and c how to estimate a teacher × content strand interaction.

  11. Multi-level molecular modelling for plasma medicine

    International Nuclear Information System (INIS)

    Bogaerts, Annemie; Khosravian, Narjes; Van der Paal, Jonas; Verlackt, Christof C W; Yusupov, Maksudbek; Kamaraj, Balu; Neyts, Erik C

    2016-01-01

    Modelling at the molecular or atomic scale can be very useful for obtaining a better insight in plasma medicine. This paper gives an overview of different atomic/molecular scale modelling approaches that can be used to study the direct interaction of plasma species with biomolecules or the consequences of these interactions for the biomolecules on a somewhat longer time-scale. These approaches include density functional theory (DFT), density functional based tight binding (DFTB), classical reactive and non-reactive molecular dynamics (MD) and united-atom or coarse-grained MD, as well as hybrid quantum mechanics/molecular mechanics (QM/MM) methods. Specific examples will be given for three important types of biomolecules, present in human cells, i.e. proteins, DNA and phospholipids found in the cell membrane. The results show that each of these modelling approaches has its specific strengths and limitations, and is particularly useful for certain applications. A multi-level approach is therefore most suitable for obtaining a global picture of the plasma–biomolecule interactions. (paper)

  12. Multilevel selection in a resource-based model

    Science.gov (United States)

    Ferreira, Fernando Fagundes; Campos, Paulo R. A.

    2013-07-01

    In the present work we investigate the emergence of cooperation in a multilevel selection model that assumes limiting resources. Following the work by R. J. Requejo and J. Camacho [Phys. Rev. Lett.0031-900710.1103/PhysRevLett.108.038701 108, 038701 (2012)], the interaction among individuals is initially ruled by a prisoner's dilemma (PD) game. The payoff matrix may change, influenced by the resource availability, and hence may also evolve to a non-PD game. Furthermore, one assumes that the population is divided into groups, whose local dynamics is driven by the payoff matrix, whereas an intergroup competition results from the nonuniformity of the growth rate of groups. We study the probability that a single cooperator can invade and establish in a population initially dominated by defectors. Cooperation is strongly favored when group sizes are small. We observe the existence of a critical group size beyond which cooperation becomes counterselected. Although the critical size depends on the parameters of the model, it is seen that a saturation value for the critical group size is achieved. The results conform to the thought that the evolutionary history of life repeatedly involved transitions from smaller selective units to larger selective units.

  13. Distinguishing Continuous and Discrete Approaches to Multilevel Mixture IRT Models: A Model Comparison Perspective

    Science.gov (United States)

    Zhu, Xiaoshu

    2013-01-01

    The current study introduced a general modeling framework, multilevel mixture IRT (MMIRT) which detects and describes characteristics of population heterogeneity, while accommodating the hierarchical data structure. In addition to introducing both continuous and discrete approaches to MMIRT, the main focus of the current study was to distinguish…

  14. Modeling Performance in C4ISR Sustained Operations: A Multi-Level Approach (Briefing Charts)

    National Research Council Canada - National Science Library

    Barnes, Christopher; Miller, James C; Elliott, Linda; Coovert, Michael

    2003-01-01

    This briefing discusses methodology and preliminary findings focused on the application of multi-level modeling techniques to distinguish effects of sleep loss and task demands on individual and team...

  15. Multilevel Models for the Analysis of Angle-Specific Torque Curves with Application to Master Athletes

    Directory of Open Access Journals (Sweden)

    Carvalho Humberto M.

    2015-12-01

    Full Text Available The aim of this paper was to outline a multilevel modeling approach to fit individual angle-specific torque curves describing concentric knee extension and flexion isokinetic muscular actions in Master athletes. The potential of the analytical approach to examine between individual differences across the angle-specific torque curves was illustrated including between-individuals variation due to gender differences at a higher level. Torques in concentric muscular actions of knee extension and knee extension at 60°·s-1 were considered within a range of motion between 5°and 85° (only torques “truly” isokinetic. Multilevel time series models with autoregressive covariance structures with standard multilevel models were superior fits compared with standard multilevel models for repeated measures to fit anglespecific torque curves. Third and fourth order polynomial models were the best fits to describe angle-specific torque curves of isokinetic knee flexion and extension concentric actions, respectively. The fixed exponents allow interpretations for initial acceleration, the angle at peak torque and the decrement of torque after peak torque. Also, the multilevel models were flexible to illustrate the influence of gender differences on the shape of torque throughout the range of motion and in the shape of the curves. The presented multilevel regression models may afford a general framework to examine angle-specific moment curves by isokinetic dynamometry, and add to the understanding mechanisms of strength development, particularly the force-length relationship, both related to performance and injury prevention.

  16. THE MODEL OF LIFELONG EDUCATION IN A TECHNICAL UNIVERSITY AS A MULTILEVEL EDUCATIONAL COMPLEX

    Directory of Open Access Journals (Sweden)

    Svetlana V. Sergeyeva

    2016-06-01

    Full Text Available Introduction: the current leading trend of the educational development is characterised by its continuity. Institutions of higher education as multi-level educational complexes nurture favourable conditions for realisation of the strategy of lifelong education. Today a technical university offering training of future engineers is facing a topic issue of creating a multilevel educational complex. Materials and Methods: this paper is put together on the basis of modern Russian and foreign scientific literature about lifelong education. The authors used theoretical methods of scientific research: systemstructural analysis, synthesis, modeling, analysis and generalisations of concepts. Results: the paper presents a model of lifelong education developed by authors for a technical university as a multilevel educational complex. It is realised through a set of principles: multi-level and continuity, integration, conformity and quality, mobility, anticipation, openness, social partnership and feedback. In accordance with the purpose, objectives and principles, the content part of the model is formed. The syllabi following the described model are run in accordance with the training levels undertaken by a technical university as a multilevel educational complex. All syllabi are based on the gradual nature of their implementation. In this regard, the authors highlight three phases: diagnostic, constructive and transformative, assessing. Discussion and Conclusions: the expected result of the created model of lifelong education development in a technical university as a multilevel educational complex is presented by a graduate trained for effective professional activity, competitive, prepared and sought-after at the regional labour market.

  17. Statistical behaviour of adaptive multilevel splitting algorithms in simple models

    International Nuclear Information System (INIS)

    Rolland, Joran; Simonnet, Eric

    2015-01-01

    Adaptive multilevel splitting algorithms have been introduced rather recently for estimating tail distributions in a fast and efficient way. In particular, they can be used for computing the so-called reactive trajectories corresponding to direct transitions from one metastable state to another. The algorithm is based on successive selection–mutation steps performed on the system in a controlled way. It has two intrinsic parameters, the number of particles/trajectories and the reaction coordinate used for discriminating good or bad trajectories. We investigate first the convergence in law of the algorithm as a function of the timestep for several simple stochastic models. Second, we consider the average duration of reactive trajectories for which no theoretical predictions exist. The most important aspect of this work concerns some systems with two degrees of freedom. They are studied in detail as a function of the reaction coordinate in the asymptotic regime where the number of trajectories goes to infinity. We show that during phase transitions, the statistics of the algorithm deviate significatively from known theoretical results when using non-optimal reaction coordinates. In this case, the variance of the algorithm is peaking at the transition and the convergence of the algorithm can be much slower than the usual expected central limit behaviour. The duration of trajectories is affected as well. Moreover, reactive trajectories do not correspond to the most probable ones. Such behaviour disappears when using the optimal reaction coordinate called committor as predicted by the theory. We finally investigate a three-state Markov chain which reproduces this phenomenon and show logarithmic convergence of the trajectory durations

  18. Space vector-based modeling and control of a modular multilevel converter in HVDC applications

    DEFF Research Database (Denmark)

    Bonavoglia, M.; Casadei, G.; Zarri, L.

    2013-01-01

    Modular multilevel converter (MMC) is an emerging multilevel topology for high-voltage applications that has been developed in recent years. In this paper, the modeling and the control of MMCs are restated in terms of space vectors, which may allow a deeper understanding of the converter behavior....... As a result, a control scheme for three-phase MMCs based on the previous theoretical analysis is presented. Numerical simulations are used to test its feasibility.......Modular multilevel converter (MMC) is an emerging multilevel topology for high-voltage applications that has been developed in recent years. In this paper, the modeling and the control of MMCs are restated in terms of space vectors, which may allow a deeper understanding of the converter behavior...

  19. A collision dynamics model of a multi-level train

    Science.gov (United States)

    2006-11-05

    In train collisions, multi-level rail passenger vehicles can deform in modes that are different from the behavior of single level cars. The deformation in single level cars usually occurs at the front end during a collision. In one particular inciden...

  20. Using Multilevel Modeling in Language Assessment Research: A Conceptual Introduction

    Science.gov (United States)

    Barkaoui, Khaled

    2013-01-01

    This article critiques traditional single-level statistical approaches (e.g., multiple regression analysis) to examining relationships between language test scores and variables in the assessment setting. It highlights the conceptual, methodological, and statistical problems associated with these techniques in dealing with multilevel or nested…

  1. A Structural Modeling Approach to a Multilevel Random Coefficients Model.

    Science.gov (United States)

    Rovine, Michael J.; Molenaar, Peter C. M.

    2000-01-01

    Presents a method for estimating the random coefficients model using covariance structure modeling and allowing one to estimate both fixed and random effects. The method is applied to real and simulated data, including marriage data from J. Belsky and M. Rovine (1990). (SLD)

  2. Constructing and validating readability models: the method of integrating multilevel linguistic features with machine learning.

    Science.gov (United States)

    Sung, Yao-Ting; Chen, Ju-Ling; Cha, Ji-Her; Tseng, Hou-Chiang; Chang, Tao-Hsing; Chang, Kuo-En

    2015-06-01

    Multilevel linguistic features have been proposed for discourse analysis, but there have been few applications of multilevel linguistic features to readability models and also few validations of such models. Most traditional readability formulae are based on generalized linear models (GLMs; e.g., discriminant analysis and multiple regression), but these models have to comply with certain statistical assumptions about data properties and include all of the data in formulae construction without pruning the outliers in advance. The use of such readability formulae tends to produce a low text classification accuracy, while using a support vector machine (SVM) in machine learning can enhance the classification outcome. The present study constructed readability models by integrating multilevel linguistic features with SVM, which is more appropriate for text classification. Taking the Chinese language as an example, this study developed 31 linguistic features as the predicting variables at the word, semantic, syntax, and cohesion levels, with grade levels of texts as the criterion variable. The study compared four types of readability models by integrating unilevel and multilevel linguistic features with GLMs and an SVM. The results indicate that adopting a multilevel approach in readability analysis provides a better representation of the complexities of both texts and the reading comprehension process.

  3. Application of Multilevel Models to Morphometric Data. Part 1. Linear Models and Hypothesis Testing

    Directory of Open Access Journals (Sweden)

    O. Tsybrovskyy

    2003-01-01

    Full Text Available Morphometric data usually have a hierarchical structure (i.e., cells are nested within patients, which should be taken into consideration in the analysis. In the recent years, special methods of handling hierarchical data, called multilevel models (MM, as well as corresponding software have received considerable development. However, there has been no application of these methods to morphometric data yet. In this paper we report our first experience of analyzing karyometric data by means of MLwiN – a dedicated program for multilevel modeling. Our data were obtained from 34 follicular adenomas and 44 follicular carcinomas of the thyroid. We show examples of fitting and interpreting MM of different complexity, and draw a number of interesting conclusions about the differences in nuclear morphology between follicular thyroid adenomas and carcinomas. We also demonstrate substantial advantages of multilevel models over conventional, single‐level statistics, which have been adopted previously to analyze karyometric data. In addition, some theoretical issues related to MM as well as major statistical software for MM are briefly reviewed.

  4. A Water Treatment Case Study for Quantifying Model Performance with Multilevel Flow Modelling

    DEFF Research Database (Denmark)

    Nielsen, Emil Krabbe; Bram, Mads Valentin; Frutiger, Jerome

    2018-01-01

    Decision support systems are a key focus of research on developing control rooms to aid operators in making reliable decisions, and reducing incidents caused by human errors. For this purpose, models of complex systems can be developed to diagnose causes or consequences for specific alarms. Models...... during operation, this work aims to synthesize a procedure to measure model performance according to diagnostic requirements. A simple procedure is proposed for validating and evaluating the concept of Multilevel Flow Modelling. For this purpose, expert statements, dynamic process simulations, and pilot...

  5. 93-106, 2015 93 Multilevel random effect and marginal models

    African Journals Online (AJOL)

    Multilevel random effect and marginal models for longitudinal data ... and random effect models that take the correlation among measurements of the same subject ... comparing the level of redness, pain and irritability ... clinical trial evaluating the safety profile of a new .... likelihood-based methods to compare models and.

  6. Applications of Multilevel Structural Equation Modeling to Cross-Cultural Research

    Science.gov (United States)

    Cheung, Mike W.-L.; Au, Kevin

    2005-01-01

    Multilevel structural equation modeling (MSEM) has been proposed as an extension to structural equation modeling for analyzing data with nested structure. We have begun to see a few applications in cross-cultural research in which MSEM fits well as the statistical model. However, given that cross-cultural studies can only afford collecting data…

  7. Distinguishing Differential Testlet Functioning from Differential Bundle Functioning Using the Multilevel Measurement Model

    Science.gov (United States)

    Beretvas, S. Natasha; Walker, Cindy M.

    2012-01-01

    This study extends the multilevel measurement model to handle testlet-based dependencies. A flexible two-level testlet response model (the MMMT-2 model) for dichotomous items is introduced that permits assessment of differential testlet functioning (DTLF). A distinction is made between this study's conceptualization of DTLF and that of…

  8. Estimating trajectories of energy intake through childhood and adolescence using linear-spline multilevel models.

    Science.gov (United States)

    Anderson, Emma L; Tilling, Kate; Fraser, Abigail; Macdonald-Wallis, Corrie; Emmett, Pauline; Cribb, Victoria; Northstone, Kate; Lawlor, Debbie A; Howe, Laura D

    2013-07-01

    Methods for the assessment of changes in dietary intake across the life course are underdeveloped. We demonstrate the use of linear-spline multilevel models to summarize energy-intake trajectories through childhood and adolescence and their application as exposures, outcomes, or mediators. The Avon Longitudinal Study of Parents and Children assessed children's dietary intake several times between ages 3 and 13 years, using both food frequency questionnaires (FFQs) and 3-day food diaries. We estimated energy-intake trajectories for 12,032 children using linear-spline multilevel models. We then assessed the associations of these trajectories with maternal body mass index (BMI), and later offspring BMI, and also their role in mediating the relation between maternal and offspring BMIs. Models estimated average and individual energy intake at 3 years, and linear changes in energy intake from age 3 to 7 years and from age 7 to 13 years. By including the exposure (in this example, maternal BMI) in the multilevel model, we were able to estimate the average energy-intake trajectories across levels of the exposure. When energy-intake trajectories are the exposure for a later outcome (in this case offspring BMI) or a mediator (between maternal and offspring BMI), results were similar, whether using a two-step process (exporting individual-level intercepts and slopes from multilevel models and using these in linear regression/path analysis), or a single-step process (multivariate multilevel models). Trajectories were similar when FFQs and food diaries were assessed either separately, or when combined into one model. Linear-spline multilevel models provide useful summaries of trajectories of dietary intake that can be used as an exposure, outcome, or mediator.

  9. COORDINATION IN MULTILEVEL NETWORK-CENTRIC CONTROL SYSTEMS OF REGIONAL SECURITY: APPROACH AND FORMAL MODEL

    Directory of Open Access Journals (Sweden)

    A. V. Masloboev

    2015-01-01

    Full Text Available The paper deals with development of methods and tools for mathematical and computer modeling of the multilevel network-centric control systems of regional security. This research is carried out under development strategy implementation of the Arctic zone of the Russian Federation and national safeguarding for the period before 2020 in the Murmansk region territory. Creation of unified interdepartmental multilevel computer-aided system is proposed intended for decision-making information support and socio-economic security monitoring of the Arctic regions of Russia. The distinctive features of the investigated system class are openness, self-organization, decentralization of management functions and decision-making, weak hierarchy in the decision-making circuit and goal generation capability inside itself. Research techniques include functional-target approach, mathematical apparatus of multilevel hierarchical system theory and principles of network-centric control of distributed systems with pro-active components and variable structure. The work considers network-centric management local decisions coordination problem-solving within the multilevel distributed systems intended for information support of regional security. The coordination problem-solving approach and problem formalization in the multilevel network-centric control systems of regional security have been proposed based on developed multilevel recurrent hierarchical model of regional socio-economic system complex security. The model provides coordination of regional security indexes, optimized by the different elements of multilevel control systems, subject to decentralized decision-making. The model specificity consists in application of functional-target technology and mathematical apparatus of multilevel hierarchical system theory for coordination procedures implementation of the network-centric management local decisions. The work-out and research results can find further

  10. A Goal Programming Model for the Siting of Multilevel EMS Systems.

    Science.gov (United States)

    1980-03-01

    Management," unpublished Ph.D. thesis, University of Texas, Austin, Texas, 1971. -23- (11) Daskin , M. and E. Stern, " A Multiobjective Set Covering...GOAL PROGRAM4MING MODEL FOR THE SITING OF MULTILEVEL EMS SYSTE-ETC(U) UNM1AR 80 A CHARNES, J E STORBECK N000iA-75-C-569 WICLASSIFIED CCS-366 N...366 A GOAL PROGRAMMING MODEL FOR THE SITING OF MULTILEVEL EMS SYSTEMS by A . Charnes J. Storbeck March 1980 This project was partially supported by

  11. Impact of lifetime model selections on the reliability prediction of IGBT modules in modular multilevel converters

    DEFF Research Database (Denmark)

    Zhang, Yi; Wang, Huai; Wang, Zhongxu

    2017-01-01

    , this paper benchmarks the most commonly-employed lifetime models of power semiconductor devices for offshore Modular Multilevel Converters (MMC) based wind farms. The benchmarking reveals that the lifetime model selection has a significant impact on the lifetime estimation. The use of analytical lifetime...

  12. Finite Mixture Multilevel Multidimensional Ordinal IRT Models for Large Scale Cross-Cultural Research

    Science.gov (United States)

    de Jong, Martijn G.; Steenkamp, Jan-Benedict E. M.

    2010-01-01

    We present a class of finite mixture multilevel multidimensional ordinal IRT models for large scale cross-cultural research. Our model is proposed for confirmatory research settings. Our prior for item parameters is a mixture distribution to accommodate situations where different groups of countries have different measurement operations, while…

  13. Teaching Quality Management Model for the Training of Innovation Ability and the Multilevel Decomposition Indicators

    Science.gov (United States)

    Lu, Xingjiang; Yao, Chen; Zheng, Jianmin

    2013-01-01

    This paper focuses on the training of undergraduate students' innovation ability. On top of the theoretical framework of the Quality Function Deployment (QFD), we propose a teaching quality management model. Based on this model, we establish a multilevel decomposition indicator system, which integrates innovation ability characterized by four…

  14. Computational Tools for Probing Interactions in Multiple Linear Regression, Multilevel Modeling, and Latent Curve Analysis

    Science.gov (United States)

    Preacher, Kristopher J.; Curran, Patrick J.; Bauer, Daniel J.

    2006-01-01

    Simple slopes, regions of significance, and confidence bands are commonly used to evaluate interactions in multiple linear regression (MLR) models, and the use of these techniques has recently been extended to multilevel or hierarchical linear modeling (HLM) and latent curve analysis (LCA). However, conducting these tests and plotting the…

  15. A Dynamic Multi-Level Factor Model with Long-Range Dependence

    DEFF Research Database (Denmark)

    Ergemen, Yunus Emre; Rodríguez-Caballero, Carlos Vladimir

    A dynamic multi-level factor model with stationary or nonstationary global and regional factors is proposed. In the model, persistence in global and regional common factors as well as innovations allows for the study of fractional cointegrating relationships. Estimation of global and regional...

  16. Developing the multi-level functioning interface framework for DER models

    DEFF Research Database (Denmark)

    Han, Xue; Bindner, Henrik W.; You, Shi

    2013-01-01

    The paper summarises several modelling applications of distributed energy resources (DERs) for various purposes, and describes the related operational issues regarding the complexity of the future distribution grid. Furthermore, a multi-level functioning interface framework is proposed for DER mo....... The information mapping for photovoltaic panel (PV) modelling is also provided as an example....

  17. Explaining Technology Integration in K-12 Classrooms: A Multilevel Path Analysis Model

    Science.gov (United States)

    Liu, Feng; Ritzhaupt, Albert D.; Dawson, Kara; Barron, Ann E.

    2017-01-01

    The purpose of this research was to design and test a model of classroom technology integration in the context of K-12 schools. The proposed multilevel path analysis model includes teacher, contextual, and school related variables on a teacher's use of technology and confidence and comfort using technology as mediators of classroom technology…

  18. Assessing Impact, DIF, and DFF in Accommodated Item Scores: A Comparison of Multilevel Measurement Model Parameterizations

    Science.gov (United States)

    Beretvas, S. Natasha; Cawthon, Stephanie W.; Lockhart, L. Leland; Kaye, Alyssa D.

    2012-01-01

    This pedagogical article is intended to explain the similarities and differences between the parameterizations of two multilevel measurement model (MMM) frameworks. The conventional two-level MMM that includes item indicators and models item scores (Level 1) clustered within examinees (Level 2) and the two-level cross-classified MMM (in which item…

  19. A Bayesian Multi-Level Factor Analytic Model of Consumer Price Sensitivities across Categories

    Science.gov (United States)

    Duvvuri, Sri Devi; Gruca, Thomas S.

    2010-01-01

    Identifying price sensitive consumers is an important problem in marketing. We develop a Bayesian multi-level factor analytic model of the covariation among household-level price sensitivities across product categories that are substitutes. Based on a multivariate probit model of category incidence, this framework also allows the researcher to…

  20. Investigating Associations between School Climate and Bullying in Secondary Schools: Multilevel Contextual Effects Modeling

    Science.gov (United States)

    Konishi, Chiaki; Miyazaki, Yasuo; Hymel, Shelley; Waterhouse, Terry

    2017-01-01

    This study examined how student reports of bullying were related to different dimensions of school climate, at both the school and the student levels, using a contextual effects model in a two-level multilevel modeling framework. Participants included 48,874 secondary students (grades 8 to 12; 24,244 girls) from 76 schools in Western Canada.…

  1. Multilevel Modeling and Policy Development: Guidelines and Applications to Medical Travel

    Science.gov (United States)

    Garcia-Garzon, Eduardo; Zhukovsky, Peter; Haller, Elisa; Plakolm, Sara; Fink, David; Petrova, Dafina; Mahalingam, Vaishali; Menezes, Igor G.; Ruggeri, Kai

    2016-01-01

    Medical travel has expanded rapidly in recent years, resulting in new markets and increased access to medical care. Whereas several studies investigated the motives of individuals seeking healthcare abroad, the conventional analytical approach is limited by substantial caveats. Classical techniques as found in the literature cannot provide sufficient insight due to the nested nature of data generated. The application of adequate analytical techniques, specifically multilevel modeling, is scarce to non-existent in the context of medical travel. This study introduces the guidelines for application of multilevel techniques in public health research by presenting an application of multilevel modeling in analyzing the decision-making patterns of potential medical travelers. Benefits and potential limitations are discussed. PMID:27252672

  2. Multilevel Modeling and Policy Development: Guidelines and Applications to Medical Travel.

    Science.gov (United States)

    Garcia-Garzon, Eduardo; Zhukovsky, Peter; Haller, Elisa; Plakolm, Sara; Fink, David; Petrova, Dafina; Mahalingam, Vaishali; Menezes, Igor G; Ruggeri, Kai

    2016-01-01

    Medical travel has expanded rapidly in recent years, resulting in new markets and increased access to medical care. Whereas several studies investigated the motives of individuals seeking healthcare abroad, the conventional analytical approach is limited by substantial caveats. Classical techniques as found in the literature cannot provide sufficient insight due to the nested nature of data generated. The application of adequate analytical techniques, specifically multilevel modeling, is scarce to non-existent in the context of medical travel. This study introduces the guidelines for application of multilevel techniques in public health research by presenting an application of multilevel modeling in analyzing the decision-making patterns of potential medical travelers. Benefits and potential limitations are discussed.

  3. The relationship between multilevel models and non-parametric multilevel mixture models: Discrete approximation of intraclass correlation, random coefficient distributions, and residual heteroscedasticity.

    Science.gov (United States)

    Rights, Jason D; Sterba, Sonya K

    2016-11-01

    Multilevel data structures are common in the social sciences. Often, such nested data are analysed with multilevel models (MLMs) in which heterogeneity between clusters is modelled by continuously distributed random intercepts and/or slopes. Alternatively, the non-parametric multilevel regression mixture model (NPMM) can accommodate the same nested data structures through discrete latent class variation. The purpose of this article is to delineate analytic relationships between NPMM and MLM parameters that are useful for understanding the indirect interpretation of the NPMM as a non-parametric approximation of the MLM, with relaxed distributional assumptions. We define how seven standard and non-standard MLM specifications can be indirectly approximated by particular NPMM specifications. We provide formulas showing how the NPMM can serve as an approximation of the MLM in terms of intraclass correlation, random coefficient means and (co)variances, heteroscedasticity of residuals at level 1, and heteroscedasticity of residuals at level 2. Further, we discuss how these relationships can be useful in practice. The specific relationships are illustrated with simulated graphical demonstrations, and direct and indirect interpretations of NPMM classes are contrasted. We provide an R function to aid in implementing and visualizing an indirect interpretation of NPMM classes. An empirical example is presented and future directions are discussed. © 2016 The British Psychological Society.

  4. Using multilevel modeling to assess case-mix adjusters in consumer experience surveys in health care.

    Science.gov (United States)

    Damman, Olga C; Stubbe, Janine H; Hendriks, Michelle; Arah, Onyebuchi A; Spreeuwenberg, Peter; Delnoij, Diana M J; Groenewegen, Peter P

    2009-04-01

    Ratings on the quality of healthcare from the consumer's perspective need to be adjusted for consumer characteristics to ensure fair and accurate comparisons between healthcare providers or health plans. Although multilevel analysis is already considered an appropriate method for analyzing healthcare performance data, it has rarely been used to assess case-mix adjustment of such data. The purpose of this article is to investigate whether multilevel regression analysis is a useful tool to detect case-mix adjusters in consumer assessment of healthcare. We used data on 11,539 consumers from 27 Dutch health plans, which were collected using the Dutch Consumer Quality Index health plan instrument. We conducted multilevel regression analyses of consumers' responses nested within health plans to assess the effects of consumer characteristics on consumer experience. We compared our findings to the results of another methodology: the impact factor approach, which combines the predictive effect of each case-mix variable with its heterogeneity across health plans. Both multilevel regression and impact factor analyses showed that age and education were the most important case-mix adjusters for consumer experience and ratings of health plans. With the exception of age, case-mix adjustment had little impact on the ranking of health plans. On both theoretical and practical grounds, multilevel modeling is useful for adequate case-mix adjustment and analysis of performance ratings.

  5. Converter DC/AC Multilevel of Three Cells: Modeling and Simulation

    Directory of Open Access Journals (Sweden)

    Julián Peláez-Restrepo

    2013-11-01

    Full Text Available This paper presents a three-cell converter DC / AC. Multilevel topologies are attracting attention in the industry, obtained as a ripple on the state variables much smaller, and reduces stress on the switching devices. The topology used in this work is known in the technical literature as floating capacitor multilevel inverter, which imposes the challenge of balancing the voltage across each cell switching using floating capacitors, besides obtaining a sinusoidal signal regulated. The paper presents the averaged model of the inverter, and results obtained through simulation.

  6. Micro-macro multilevel latent class models with multiple discrete individual-level variables

    NARCIS (Netherlands)

    Bennink, M.; Croon, M.A.; Kroon, B.; Vermunt, J.K.

    2016-01-01

    An existing micro-macro method for a single individual-level variable is extended to the multivariate situation by presenting two multilevel latent class models in which multiple discrete individual-level variables are used to explain a group-level outcome. As in the univariate case, the

  7. Gender Differences When Parenting Children with Autism Spectrum Disorders: A Multilevel Modeling Approach

    Science.gov (United States)

    Jones, Leah; Totsika, Vasiliki; Hastings, Richard P.; Petalas, Michael A.

    2013-01-01

    Parenting a child with autism may differentially affect mothers and fathers. Existing studies of mother-father differences often ignore the interdependence of data within families. We investigated gender differences within-families using multilevel linear modeling. Mothers and fathers of children with autism (161 couples) reported on their own…

  8. A longitudinal study of interethnic contacts in Germany: estimates from a multilevel growth curve model

    NARCIS (Netherlands)

    Martinovic, B.; van Tubergen, F.; Maas, I.

    2015-01-01

    Interethnic ties are considered important for the cohesion in society. Previous research has studied the determinants of interethnic ties with cross-sectional data or lagged panel designs. This study improves on prior research by applying multilevel growth curve modelling techniques with lagged

  9. A longitudinal study of interethnic contacts in Germany : Estimates from a multilevel growth curve model

    NARCIS (Netherlands)

    Martinovic, Borja|info:eu-repo/dai/nl/304822752; van Tubergen, Frank|info:eu-repo/dai/nl/271429534; Maas, Ineke|info:eu-repo/dai/nl/075229390

    2015-01-01

    Interethnic ties are considered important for the cohesion in society. Previous research has studied the determinants of interethnic ties with cross-sectional data or lagged panel designs. This study improves on prior research by applying multilevel growth curve modelling techniques with lagged

  10. Modeling the Factors Associated with Children's Mental Health Difficulties in Primary School: A Multilevel Study

    Science.gov (United States)

    Humphrey, Neil; Wigelsworth, Michael

    2012-01-01

    The current study explores some of the factors associated with children's mental health difficulties in primary school. Multilevel modeling with data from 628 children from 36 schools was used to determine how much variation in mental health difficulties exists between and within schools, and to identify characteristics at the school and…

  11. A Multilevel Model of Team Cultural Diversity and Creativity: The Role of Climate for Inclusion

    Science.gov (United States)

    Li, Ci-Rong; Lin, Chen-Ju; Tien, Yun-Hsiang; Chen, Chien-Ming

    2017-01-01

    We developed a multi-level model to test how team cultural diversity may relate to team- and individual-level creativity, integrating team diversity research and information-exchange perspective. We proposed that the team climate for inclusion would moderate both the relationship between cultural diversity and team information sharing and between…

  12. A multivariate multilevel Gaussian model with a mixed effects structure in the mean and covariance part.

    Science.gov (United States)

    Li, Baoyue; Bruyneel, Luk; Lesaffre, Emmanuel

    2014-05-20

    A traditional Gaussian hierarchical model assumes a nested multilevel structure for the mean and a constant variance at each level. We propose a Bayesian multivariate multilevel factor model that assumes a multilevel structure for both the mean and the covariance matrix. That is, in addition to a multilevel structure for the mean we also assume that the covariance matrix depends on covariates and random effects. This allows to explore whether the covariance structure depends on the values of the higher levels and as such models heterogeneity in the variances and correlation structure of the multivariate outcome across the higher level values. The approach is applied to the three-dimensional vector of burnout measurements collected on nurses in a large European study to answer the research question whether the covariance matrix of the outcomes depends on recorded system-level features in the organization of nursing care, but also on not-recorded factors that vary with countries, hospitals, and nursing units. Simulations illustrate the performance of our modeling approach. Copyright © 2013 John Wiley & Sons, Ltd.

  13. A novel modular multilevel converter modelling technique based on semi-analytical models for HVDC application

    Directory of Open Access Journals (Sweden)

    Ahmed Zama

    2016-12-01

    Full Text Available Thanks to scalability, performance and efficiency, the Modular Multilevel Converter (MMC, since its invention, becomes an attractive topology in industrial applications such as high voltage direct current (HVDC transmission system. However, modelling challenges related to the high number of switching elements in the MMC are highlighted when such systems are integrated into large simulated networks for stability or protection algorithms testing. In this work, a novel dynamic models for MMC is proposed. The proposed models are intended to simplify modeling challenges related to the high number of switching elements in the MMC. The models can be easily used to simulate the converter for stability analysis or protection algorithms for HVDC grids.

  14. Race, Employment Disadvantages, and Heavy Drinking: A Multilevel Model.

    Science.gov (United States)

    Lo, Celia C; Cheng, Tyrone C

    2015-01-01

    We intended to determine (1) whether stress from employment disadvantages led to increased frequency of heavy drinking and (2) whether race had a role in the relationship between such disadvantages and heavy drinking. Study data came from the National Longitudinal Survey of Youth, a prospective study that has followed a representative sample of youth since 1979. Our study employed data from 11 particular years, during which the survey included items measuring respondents' heavy drinking. Our final sample numbered 10,171 respondents, which generated 75,394 person-waves for data analysis. Both of our hypotheses were supported by results from multilevel mixed-effects linear regression capturing the time-varying nature of three employment disadvantages and of the heavy-drinking outcome. Results show that more-frequent heavy drinking was associated with employment disadvantages, and that disadvantages' effects on drinking were stronger for Blacks and Hispanics than for Whites. That worsening employment disadvantages have worse effects on minority groups' heavy drinking (compared to Whites) probably contributes to the racial health disparities in our nation. Policies and programs addressing such disparities are especially important during economic downturns.

  15. Model Promosi Kesehatan di Tempat Kerja Multilevel: Bagaimana Implementasinya dalam Mengubah Perilaku Pekerja? (Suatu Kajian Kepustakaan

    Directory of Open Access Journals (Sweden)

    Zahtamal .

    2015-05-01

    Full Text Available Konsekuensi dari penyakit-penyakit yang sering dialami oleh pekerja merupakan kerugian besar bagi perusahaan dan pekerja. Dalam rangka mengatasi persoalan penyakit pada pekerja, perlu upaya promosi kesehatan di tempat kerja, khususnya untuk mengubah perilaku. Penerapan perubahan perilaku di tempat kerja bersifat lebih kompleks. Perubahan perilaku tidak saja didorong oleh faktor-faktor individu, tetapi juga oleh peran faktor eksternal, sehingga pihak yang dijadikan sasaran workplace health promotion (WHP adalah secara multilevel. Artikel ini menjelaskan rumusan model WHP multilevel yang dapat diterapkan untuk mengubah perilaku pekerja yang tidak sehat, sehingga diharapkan dapat menurunkan kesakitan dan kematian penyakit pada pekerja. Prinsip pemilihan model perubahan perilaku, perlu  diperhatikan dalam merumuskan WHP secara multilevel. Hal ini dijadikan sebagai acuan memodifikasi perilaku yang akan dituju. Selanjutnya, prinsip memilih strategi dan metode perubahan perilaku, disesuaikan dengan level sasaran yang diintervensi. Secara keseluruhan, prinsip-prinsip ini dirumuskan dalam sebuah acuan program WHP secara komprehensif dan dilaksanakan dengan efektif dan efisien di tempat kerja. Artikel ini dapat menjadi acuan bagi pihak yang akan mengimplementasikan WHP dengan pendekatan perubahan perilaku secara multilevel

  16. Modeling the dynamics of evaluation: a multilevel neural network implementation of the iterative reprocessing model.

    Science.gov (United States)

    Ehret, Phillip J; Monroe, Brian M; Read, Stephen J

    2015-05-01

    We present a neural network implementation of central components of the iterative reprocessing (IR) model. The IR model argues that the evaluation of social stimuli (attitudes, stereotypes) is the result of the IR of stimuli in a hierarchy of neural systems: The evaluation of social stimuli develops and changes over processing. The network has a multilevel, bidirectional feedback evaluation system that integrates initial perceptual processing and later developing semantic processing. The network processes stimuli (e.g., an individual's appearance) over repeated iterations, with increasingly higher levels of semantic processing over time. As a result, the network's evaluations of stimuli evolve. We discuss the implications of the network for a number of different issues involved in attitudes and social evaluation. The success of the network supports the IR model framework and provides new insights into attitude theory. © 2014 by the Society for Personality and Social Psychology, Inc.

  17. A Formal Model of Trust Chain based on Multi-level Security Policy

    OpenAIRE

    Kong Xiangying

    2013-01-01

    Trust chain is the core technology of trusted computing. A formal model of trust chain based on finite state automata theory is proposed. We use communicating sequential processes to describe the system state transition in trust chain and by combining with multi-level security strategy give the definition of trust system and trust decision theorem of trust chain transfer which is proved meantime. Finally, a prototype system is given to show the efficiency of the model.

  18. The Norwegian Healthier Goats program--modeling lactation curves using a multilevel cubic spline regression model.

    Science.gov (United States)

    Nagel-Alne, G E; Krontveit, R; Bohlin, J; Valle, P S; Skjerve, E; Sølverød, L S

    2014-07-01

    In 2001, the Norwegian Goat Health Service initiated the Healthier Goats program (HG), with the aim of eradicating caprine arthritis encephalitis, caseous lymphadenitis, and Johne's disease (caprine paratuberculosis) in Norwegian goat herds. The aim of the present study was to explore how control and eradication of the above-mentioned diseases by enrolling in HG affected milk yield by comparison with herds not enrolled in HG. Lactation curves were modeled using a multilevel cubic spline regression model where farm, goat, and lactation were included as random effect parameters. The data material contained 135,446 registrations of daily milk yield from 28,829 lactations in 43 herds. The multilevel cubic spline regression model was applied to 4 categories of data: enrolled early, control early, enrolled late, and control late. For enrolled herds, the early and late notations refer to the situation before and after enrolling in HG; for nonenrolled herds (controls), they refer to development over time, independent of HG. Total milk yield increased in the enrolled herds after eradication: the total milk yields in the fourth lactation were 634.2 and 873.3 kg in enrolled early and enrolled late herds, respectively, and 613.2 and 701.4 kg in the control early and control late herds, respectively. Day of peak yield differed between enrolled and control herds. The day of peak yield came on d 6 of lactation for the control early category for parities 2, 3, and 4, indicating an inability of the goats to further increase their milk yield from the initial level. For enrolled herds, on the other hand, peak yield came between d 49 and 56, indicating a gradual increase in milk yield after kidding. Our results indicate that enrollment in the HG disease eradication program improved the milk yield of dairy goats considerably, and that the multilevel cubic spline regression was a suitable model for exploring effects of disease control and eradication on milk yield. Copyright © 2014

  19. Multilevel Modelling with Spatial Interaction Effects with Application to an Emerging Land Market in Beijing, China.

    Directory of Open Access Journals (Sweden)

    Guanpeng Dong

    Full Text Available This paper develops a methodology for extending multilevel modelling to incorporate spatial interaction effects. The motivation is that classic multilevel models are not specifically spatial. Lower level units may be nested into higher level ones based on a geographical hierarchy (or a membership structure--for example, census zones into regions but the actual locations of the units and the distances between them are not directly considered: what matters is the groupings but not how close together any two units are within those groupings. As a consequence, spatial interaction effects are neither modelled nor measured, confounding group effects (understood as some sort of contextual effect that acts 'top down' upon members of a group with proximity effects (some sort of joint dependency that emerges between neighbours. To deal with this, we incorporate spatial simultaneous autoregressive processes into both the outcome variable and the higher level residuals. To assess the performance of the proposed method and the classic multilevel model, a series of Monte Carlo simulations are conducted. The results show that the proposed method performs well in retrieving the true model parameters whereas the classic multilevel model provides biased and inefficient parameter estimation in the presence of spatial interactions. An important implication of the study is to be cautious of an apparent neighbourhood effect in terms of both its magnitude and statistical significance if spatial interaction effects at a lower level are suspected. Applying the new approach to a two-level land price data set for Beijing, China, we find significant spatial interactions at both the land parcel and district levels.

  20. Dual deep modeling: multi-level modeling with dual potencies and its formalization in F-Logic.

    Science.gov (United States)

    Neumayr, Bernd; Schuetz, Christoph G; Jeusfeld, Manfred A; Schrefl, Michael

    2018-01-01

    An enterprise database contains a global, integrated, and consistent representation of a company's data. Multi-level modeling facilitates the definition and maintenance of such an integrated conceptual data model in a dynamic environment of changing data requirements of diverse applications. Multi-level models transcend the traditional separation of class and object with clabjects as the central modeling primitive, which allows for a more flexible and natural representation of many real-world use cases. In deep instantiation, the number of instantiation levels of a clabject or property is indicated by a single potency. Dual deep modeling (DDM) differentiates between source potency and target potency of a property or association and supports the flexible instantiation and refinement of the property by statements connecting clabjects at different modeling levels. DDM comes with multiple generalization of clabjects, subsetting/specialization of properties, and multi-level cardinality constraints. Examples are presented using a UML-style notation for DDM together with UML class and object diagrams for the representation of two-level user views derived from the multi-level model. Syntax and semantics of DDM are formalized and implemented in F-Logic, supporting the modeler with integrity checks and rich query facilities.

  1. Multilevel binomial logistic prediction model for malignant pulmonary nodules based on texture features of CT image

    International Nuclear Information System (INIS)

    Wang Huan; Guo Xiuhua; Jia Zhongwei; Li Hongkai; Liang Zhigang; Li Kuncheng; He Qian

    2010-01-01

    Purpose: To introduce multilevel binomial logistic prediction model-based computer-aided diagnostic (CAD) method of small solitary pulmonary nodules (SPNs) diagnosis by combining patient and image characteristics by textural features of CT image. Materials and methods: Describe fourteen gray level co-occurrence matrix textural features obtained from 2171 benign and malignant small solitary pulmonary nodules, which belongs to 185 patients. Multilevel binomial logistic model is applied to gain these initial insights. Results: Five texture features, including Inertia, Entropy, Correlation, Difference-mean, Sum-Entropy, and age of patients own aggregating character on patient-level, which are statistically different (P < 0.05) between benign and malignant small solitary pulmonary nodules. Conclusion: Some gray level co-occurrence matrix textural features are efficiently descriptive features of CT image of small solitary pulmonary nodules, which can profit diagnosis of earlier period lung cancer if combined patient-level characteristics to some extent.

  2. The Design Model of Multilevel Estimation Means for Students’ Competence Assessment at Technical Higher School

    Directory of Open Access Journals (Sweden)

    O. F. Shikhova

    2012-01-01

    Full Text Available The paper considers the research findings aimed at the developing the new quality testing technique for students assessment at Technical Higher School. The model of multilevel estimation means is provided for diagnosing the level of general cultural and professional competences of students doing a bachelor degree in technological fields. The model implies the integrative character of specialists training - the combination of both the psycho-pedagogic (invariable and engineering (variable components, as well as the qualimetric approach substantiating the system of students competence estimation and providing the most adequate assessment means. The principles of designing the multilevel estimation means are defined along with the methodology approaches to their implementation. For the reasonable selection of estimation means, the system of quality criteria is proposed by the authors, being based on the group expert assessment. The research findings can be used for designing the competence-oriented estimation means. 

  3. Multilevel Flow Modeling Based Decision Support System and Its Task Organization

    DEFF Research Database (Denmark)

    Zhang, Xinxin; Lind, Morten; Ravn, Ole

    2013-01-01

    For complex engineering systems, there is an increasing demand for safety and reliability. Decision support system (DSS) is designed to offer su-pervision and analysis about operational situations. A proper model representa-tion is required for DSS to understand the process knowledge. Multilevel ...... techniques of MFM reasoning and less mature yet relevant MFM concepts are considered. It also offers an architecture design of task organization for MFM software tools by using the concept of agent and technology of multiagent software system....

  4. Site-Specific Multilevel Modeling of Potato Response to Nitrogen Fertilization

    OpenAIRE

    Serge-Étienne Parent; Michaël A. Leblanc; Annie-Claude Parent; Zonlehoua Coulibali; Léon E. Parent

    2017-01-01

    Technologies of precision agriculture, digital soil maps, and meteorological stations provide a minimum data set to guide precision farming operations. However, determining optimal nutrient requirements for potato (Solanum tuberosum L.) crops at subfield scale remains a challenge given specific climatic, edaphic, and managerial conditions. Multilevel modeling can generalize yield response to fertilizer additions using data easily accessible to growers. Our objective was to elaborate a multile...

  5. Using iMCFA to Perform the CFA, Multilevel CFA, and Maximum Model for Analyzing Complex Survey Data.

    Science.gov (United States)

    Wu, Jiun-Yu; Lee, Yuan-Hsuan; Lin, John J H

    2018-01-01

    To construct CFA, MCFA, and maximum MCFA with LISREL v.8 and below, we provide iMCFA (integrated Multilevel Confirmatory Analysis) to examine the potential multilevel factorial structure in the complex survey data. Modeling multilevel structure for complex survey data is complicated because building a multilevel model is not an infallible statistical strategy unless the hypothesized model is close to the real data structure. Methodologists have suggested using different modeling techniques to investigate potential multilevel structure of survey data. Using iMCFA, researchers can visually set the between- and within-level factorial structure to fit MCFA, CFA and/or MAX MCFA models for complex survey data. iMCFA can then yield between- and within-level variance-covariance matrices, calculate intraclass correlations, perform the analyses and generate the outputs for respective models. The summary of the analytical outputs from LISREL is gathered and tabulated for further model comparison and interpretation. iMCFA also provides LISREL syntax of different models for researchers' future use. An empirical and a simulated multilevel dataset with complex and simple structures in the within or between level was used to illustrate the usability and the effectiveness of the iMCFA procedure on analyzing complex survey data. The analytic results of iMCFA using Muthen's limited information estimator were compared with those of Mplus using Full Information Maximum Likelihood regarding the effectiveness of different estimation methods.

  6. Random Intercept and Random Slope 2-Level Multilevel Models

    Directory of Open Access Journals (Sweden)

    Rehan Ahmad Khan

    2012-11-01

    Full Text Available Random intercept model and random intercept & random slope model carrying two-levels of hierarchy in the population are presented and compared with the traditional regression approach. The impact of students’ satisfaction on their grade point average (GPA was explored with and without controlling teachers influence. The variation at level-1 can be controlled by introducing the higher levels of hierarchy in the model. The fanny movement of the fitted lines proves variation of student grades around teachers.

  7. Evaluating Technical Efficiency of Nursing Care Using Data Envelopment Analysis and Multilevel Modeling.

    Science.gov (United States)

    Min, Ari; Park, Chang Gi; Scott, Linda D

    2016-05-23

    Data envelopment analysis (DEA) is an advantageous non-parametric technique for evaluating relative efficiency of performance. This article describes use of DEA to estimate technical efficiency of nursing care and demonstrates the benefits of using multilevel modeling to identify characteristics of efficient facilities in the second stage of analysis. Data were drawn from LTCFocUS.org, a secondary database including nursing home data from the Online Survey Certification and Reporting System and Minimum Data Set. In this example, 2,267 non-hospital-based nursing homes were evaluated. Use of DEA with nurse staffing levels as inputs and quality of care as outputs allowed estimation of the relative technical efficiency of nursing care in these facilities. In the second stage, multilevel modeling was applied to identify organizational factors contributing to technical efficiency. Use of multilevel modeling avoided biased estimation of findings for nested data and provided comprehensive information on differences in technical efficiency among counties and states. © The Author(s) 2016.

  8. Modelling primary branch growth based on a multilevel nonlinear ...

    African Journals Online (AJOL)

    In addition to random effects, various time series correlation structures were evaluated to account for residual autocorrelation, and the AR(1) and ARMA(1,1) structures were selected for the branch diameter and length growth models, respectively. Model validation results using an independent data set confirmed that ...

  9. Multilevel Molecular Modeling Approach for a Rational Design of Ionic Current Sensors for Nanofluidics.

    Science.gov (United States)

    Kirch, Alexsandro; de Almeida, James M; Miranda, Caetano R

    2018-05-10

    The complexity displayed by nanofluidic-based systems involves electronic and dynamic aspects occurring across different size and time scales. To properly model such kind of system, we introduced a top-down multilevel approach, combining molecular dynamics simulations (MD) with first-principles electronic transport calculations. The potential of this technique was demonstrated by investigating how the water and ionic flow through a (6,6) carbon nanotube (CNT) influences its electronic transport properties. We showed that the confinement on the CNT favors the partially hydrated Na, Cl, and Li ions to exchange charge with the nanotube. This leads to a change in the electronic transmittance, allowing for the distinguishing of cations from anions. Such an ionic trace may handle an indirect measurement of the ionic current that is recorded as a sensing output. With this case study, we are able to show the potential of this top-down multilevel approach, to be applied on the design of novel nanofluidic devices.

  10. Modeling And Simulation Of Highly Advanced Multilevel Inverter For Speed Control Of Induction Motor

    Directory of Open Access Journals (Sweden)

    Ravi Raj

    2017-02-01

    Full Text Available In this Paper the problem of removing Power dissipation from single phase Induction Motor with DC sources is considered by the speed control of Induction Motor with highly advanced 9-Level multi-level Inverter which having approximate zero Harmonics. As the demand of power is increasing day by day. So that we must introduced very advanced Electrical Instruments which having high efficiency and less dissipation of power. The requirement of very advanced Inverter is necessary. Here we are designing a Multi-level Inverter up to the 9-level using IGBT Insulated-gate bipolar transistor by Mat lab which having negligible total harmonic distortion THD thats why it will control the speed of single phase Induction motor which is presently widely used in our daily needs. Also several informative Simulation results verify the authority and truthiness of the proposed Model.

  11. To center or not to center? Investigating inertia with a multilevel autoregressive model

    Directory of Open Access Journals (Sweden)

    Ellen L. Hamaker

    2015-01-01

    Full Text Available Whether level 1 predictors should be centered per cluster has received considerable attention in the multilevel literature. While most agree that there is no one preferred approach, it has also been argued that cluster mean centering is desirable when the within-cluster slope and the between-cluster slope are expected to deviate, and the main interest is in the within-cluster slope. However, we show in a series of simulations that if one has a multilevel autoregressive model in which the level 1 predictor is the lagged outcome variable (i.e., the outcome variable at the previous occasion, cluster mean centering will in general lead to a downward bias in the parameter estimate of the within-cluster slope (i.e., the autoregressive relationship. This is particularly relevant if the main question is whether there is on average an autoregressive effect. Nonetheless, we show that if the main interest is in estimating the effect of a level 2 predictor on the autoregressive parameter (i.e., a cross-level interaction, cluster mean centering should be preferred over other forms of centering. Hence, researchers should be clear on what is considered the main goal of their study, and base their choice of centering method on this when using a multilevel autoregressive model.

  12. Proposal for operator's mental model using the concept of multilevel flow modeling

    International Nuclear Information System (INIS)

    Yoshimura, Seiichi; Takano, Kenichi; Sasou, Kunihide

    1995-01-01

    It is necessary to analyze an operator's thinking process and a operator team's intension forming process for preventing human errors in a highly advanced huge system like a nuclear power plant. Central Research Institute of Electric Power Industry is promoting a research project to establish human error prevention countermeasures by modeling the thinking and intension forming process. The important is the future prediction and the cause identification when abnormal situations occur in a nuclear power plant. The concept of Multilevel Flow Modeling (MFM) seems to be effective as an operator's mental model which performs the future prediction and the cause identification. MFM is a concept which qualitatively describes the plant functions by energy and mass flows and also describes the plant status by breaking down the targets in a hierarchical manner which a plant should achieve. In this paper, an operator's mental model using the concept of MFM was proposed and a nuclear power plant diagnosis support system using MFM was developed. The system evaluation test by personnel who have operational experience in nuclear power plants revealed that MFM was superior in the future prediction and the cause identification to a traditional nuclear power plant status display system which used mimics and trends. MFM proved to be useful as an operator's mental model by the test. (author)

  13. Multilevel random effect and marginal models for longitudinal data ...

    African Journals Online (AJOL)

    The models were applied to data obtained from a phase-III clinical trial on a new meningococcal vaccine. The goal is to investigate whether children injected by the candidate vaccine have a lower or higher risk for the occurrence of specific adverse events than children injected with licensed vaccine, and if so, to quantify the ...

  14. Building a multilevel modeling network for lipid processing systems

    DEFF Research Database (Denmark)

    Mustaffa, Azizul Azri; Díaz Tovar, Carlos Axel; Hukkerikar, Amol

    2011-01-01

    ). The applicability of this methodology is highlighted in each level of modeling through the analysis of a lipid process that has significant relevance in the edible oil and biodiesel industries since it determines the quality of the final oil product, the physical refining process of oils and fats....

  15. Safety of Mixed Model Access Control in a Multilevel System

    Science.gov (United States)

    2014-06-01

    42  H.  FIREWALL AND IPS LANGUAGES...Research Laboratory AIS automated information system ANOA advance notice of arrival APT advanced persistent threat BFM boundary flow modeling...of Investigation FW firewall GENSER general service xvi GUI graphical user interface HAG high-assurance guard HGS high-grade service H-H-H High

  16. A Multi-Level Model of Moral Functioning Revisited

    Science.gov (United States)

    Reed, Don Collins

    2009-01-01

    The model of moral functioning scaffolded in the 2008 "JME" Special Issue is here revisited in response to three papers criticising that volume. As guest editor of that Special Issue I have formulated the main body of this response, concerning the dynamic systems approach to moral development, the problem of moral relativism and the role of…

  17. Adaptive filters and internal models: multilevel description of cerebellar function.

    Science.gov (United States)

    Porrill, John; Dean, Paul; Anderson, Sean R

    2013-11-01

    Cerebellar function is increasingly discussed in terms of engineering schemes for motor control and signal processing that involve internal models. To address the relation between the cerebellum and internal models, we adopt the chip metaphor that has been used to represent the combination of a homogeneous cerebellar cortical microcircuit with individual microzones having unique external connections. This metaphor indicates that identifying the function of a particular cerebellar chip requires knowledge of both the general microcircuit algorithm and the chip's individual connections. Here we use a popular candidate algorithm as embodied in the adaptive filter, which learns to decorrelate its inputs from a reference ('teaching', 'error') signal. This algorithm is computationally powerful enough to be used in a very wide variety of engineering applications. However, the crucial issue is whether the external connectivity required by such applications can be implemented biologically. We argue that some applications appear to be in principle biologically implausible: these include the Smith predictor and Kalman filter (for state estimation), and the feedback-error-learning scheme for adaptive inverse control. However, even for plausible schemes, such as forward models for noise cancellation and novelty-detection, and the recurrent architecture for adaptive inverse control, there is unlikely to be a simple mapping between microzone function and internal model structure. This initial analysis suggests that cerebellar involvement in particular behaviours is therefore unlikely to have a neat classification into categories such as 'forward model'. It is more likely that cerebellar microzones learn a task-specific adaptive-filter operation which combines a number of signal-processing roles. Copyright © 2012 Elsevier Ltd. All rights reserved.

  18. A longitudinal multilevel CFA-MTMM model for interchangeable and structurally different methods

    Science.gov (United States)

    Koch, Tobias; Schultze, Martin; Eid, Michael; Geiser, Christian

    2014-01-01

    One of the key interests in the social sciences is the investigation of change and stability of a given attribute. Although numerous models have been proposed in the past for analyzing longitudinal data including multilevel and/or latent variable modeling approaches, only few modeling approaches have been developed for studying the construct validity in longitudinal multitrait-multimethod (MTMM) measurement designs. The aim of the present study was to extend the spectrum of current longitudinal modeling approaches for MTMM analysis. Specifically, a new longitudinal multilevel CFA-MTMM model for measurement designs with structurally different and interchangeable methods (called Latent-State-Combination-Of-Methods model, LS-COM) is presented. Interchangeable methods are methods that are randomly sampled from a set of equivalent methods (e.g., multiple student ratings for teaching quality), whereas structurally different methods are methods that cannot be easily replaced by one another (e.g., teacher, self-ratings, principle ratings). Results of a simulation study indicate that the parameters and standard errors in the LS-COM model are well recovered even in conditions with only five observations per estimated model parameter. The advantages and limitations of the LS-COM model relative to other longitudinal MTMM modeling approaches are discussed. PMID:24860515

  19. Model Predictive Control of Grid Connected Modular Multilevel Converter for Integration of Photovoltaic Power Systems

    DEFF Research Database (Denmark)

    Hajizadeh, Amin; Shahirinia, Amir

    2017-01-01

    Investigation of an advanced control structure for integration of Photovoltaic Power Systems through Grid Connected-Modular Multilevel Converter (GC-MMC) is proposed in this paper. To achieve this goal, a non-linear model of MMC regarding considering of negative and positive sequence components has...... been presented. Then, due to existence of unbalance voltage faults in distribution grid, non-linarites and uncertainties in model, model predictive controller which is developed for GC-MMC. They are implemented based upon positive and negative components of voltage and current to mitigate the power...

  20. Multi-Level Marketing as a business model

    Directory of Open Access Journals (Sweden)

    Bogdan Gregor

    2013-03-01

    Full Text Available Multi Level Marketing is a very popular business model in the Western countries. It is a kind of hybrid of the method of distribution of goods and the method of building a sales network. It is one of the safest (carries a very low risk ways of conducting a business activity. The knowledge about functioning of this business model, both among theoreticians (scanty literature on the subject and practitioners, is still insufficient in Poland. Thus, the presented paper has been prepared as — in the Authors' opinion — it, at least infinitesimally, bridges the gap in the recognition of Multi Level Marketing issues. The aim of the study was, first of all, to describe Multi Level Marketing, to indicate practical benefits of this business model as well as to present basic systems of calculating a commission, which are used in marketing plans of companies. The discussion was based on the study of literature and the knowledge gained in the course of free-form interviews with the leaders of the sector.

  1. Vehicle logo recognition using multi-level fusion model

    Science.gov (United States)

    Ming, Wei; Xiao, Jianli

    2018-04-01

    Vehicle logo recognition plays an important role in manufacturer identification and vehicle recognition. This paper proposes a new vehicle logo recognition algorithm. It has a hierarchical framework, which consists of two fusion levels. At the first level, a feature fusion model is employed to map the original features to a higher dimension feature space. In this space, the vehicle logos become more recognizable. At the second level, a weighted voting strategy is proposed to promote the accuracy and the robustness of the recognition results. To evaluate the performance of the proposed algorithm, extensive experiments are performed, which demonstrate that the proposed algorithm can achieve high recognition accuracy and work robustly.

  2. MODEL MULTILEVEL PERTUMBUHAN ANAK USIA 0-24 BULAN DAN VARIABEL YANG MEMPENGARUHINYA

    Directory of Open Access Journals (Sweden)

    Irianton Aritonang

    2013-01-01

    Full Text Available Tujuan umum penelitian ini untuk mengkaji bagaimana berbagai variabel mempengaruhi pertumbuhan anak usia 0-24 bulan di kabupaten Sleman. Penelitian noneksperimen desain korelasional ini dilakukan pada 272 anak usia 0-24 bulan yang diambil secara acak stratifikasi dari dua kecamatan (Sleman dan Moyudan yang ditentukan secara purposif. Analisis multilevel pertumbuhan anak dilakukan dengan program Stata-10 dan analisis jalur dilakukan dengan program Amos-8. Hasil penelitian menunjukkan bahwa ada hubungan variabel berat badan lahir, jenis kelamin dan strata usia anak dan status gizi ibu dengan pertumbuhan anak pada level-1 dan ada hubungan variabel hasil penimbangan pada level-2, sedangkan pada level 3 ada hubungan yang tidak signifikan hasil penimbangan dan pencapaian program. Hasil analisis jalur yang mempengaruhi pertumbuhan anak 0-24 bulan, yakni variabel endogenous terdiri dari status gizi ibu, pengetahuan ibu tentang gizi seimbang, pertumbuhan anak indeks BB/U, hasil penimbangan tingkat dusun dan hasil program tingkat desa. Sedangkan variabel exogenous terdiri dari sikap ibu terhadap posyandu, berat badan lahir, jenis kelamin dan stratifikasi usia anak. Kata kunci: Model multilevel, Pertumbuhan anak 0-24 bulan ______________________________________________________________ A MULTILEVEL MODEL FOR THE GROWTH OF CHILDREN AGED 0-24 MONTHS AND THE VARIABLES AFFECTING IT Abstract The main objective of this study is to investigate how various variables contribute to the growth of children between 0-24  months old in Sleman Regency. This study was a non-experimental correlational design which was conducted on 272 children aged 0-24 months, selected using the purposive stratified random sampling technique from 21 hamlets in two districts (Sleman and Moyudan. The multilevel analysis of children’s growth of was carried out using the Stata-10 program and the path analysis using the Amos-8 program. The results show  that there is a significant

  3. Beholder and Beheld: A Multilevel Model of Perceived Sexual Appeal.

    Science.gov (United States)

    Mackaronis, Julia E; Strassberg, Donald S; Cundiff, Jeanne M; Cann, Deanna J

    2015-11-01

    When individuals (observers) assess how appealing they find sexual stimuli (targets), which factors matter and to whom? The present study examined how observer and target characteristics interact and impact perceived sexual appeal. Participants were 302 men (206 heterosexual, 96 gay) and 289 women (196 heterosexual, 93 lesbian) between the ages of 18 and 67 years, who viewed 34 photographs of targets of their preferred gender and rated each target for sexual appeal, masculinity-femininity, and estimated age. Participants also rated their own masculinity-femininity. A baseline model indicated that roughly 30 % of the variance in sexual appeal ratings was at the observer level (between observers) and 70 % of the variance was at the target level (within observers). In the final model, five characteristics of the participant observers (gender, sexual orientation, age, race/ethnicity, and self-described masculinity-femininity) and six characteristics of the target photographs (gender, whether the photographs were taken from heterosexual versus gay/lesbian media, race/ethnicity, perceived masculinity-femininity, and estimated age) were independently and interactively related to observer ratings of target sexual appeal. Observers displayed preferences for similar targets in terms of race/ethnicity and masculinity-femininity, while also displaying a general preference for target youth. Variation in the strength of these preferences occurred according to observers' own gender, race/ethnicity, masculinity-femininity, and sexual orientation.

  4. Simplified Thermal Modeling for IGBT Modules with Periodic Power Loss Profiles in Modular Multilevel Converters

    DEFF Research Database (Denmark)

    Zhang, Yi; Wang, Huai; Wang, Zhongxu

    2018-01-01

    One of the future challenges in Modular Multilevel Converters (MMCs) is how to size key components with compromised costs and design margins while fulfilling specific reliability targets. It demands better thermal modeling compared to the state-of-the-art in terms of both accuracy and simplicity....... Different from two-level power converters, MMCs have inherent dc-bias in arm currents and the power device conduction time is affected by operational parameters. A time-wise thermal modeling for the power devices in MMCs is, therefore, an iteration process and time-consuming. This paper thus proposes...

  5. An application of multilevel flow modelling method for nuclear plant state identification

    International Nuclear Information System (INIS)

    Businaro, T.; Di Lorenzo, A.; Meo, G.B.; Rabbani, M.I.; Rubino, E.

    1986-01-01

    With the advent of advanced digital techniques it has been rendered possible, necessity of which has long since been recognised, to develop a computer based man-machine interface and hance an expert system based on knowledge based decision making for operator support in the control rooms of nuclear plants. The Multilevel Flow Modelling method developed at RISO Laboratories, Denmark, has been applied in the present experiment to model Italian PEC reactor and to verify applicability of this method in plant state identification. In MFM method functional structure of a process plant is described in terms of a set of interrelated mass and energy flow structures on different levels of physical aggregation

  6. A multilevel nonlinear mixed-effects approach to model growth in pigs

    DEFF Research Database (Denmark)

    Strathe, Anders Bjerring; Danfær, Allan Christian; Sørensen, H.

    2010-01-01

    Growth functions have been used to predict market weight of pigs and maximize return over feed costs. This study was undertaken to compare 4 growth functions and methods of analyzing data, particularly one that considers nonlinear repeated measures. Data were collected from an experiment with 40...... pigs maintained from birth to maturity and their BW measured weekly or every 2 wk up to 1,007 d. Gompertz, logistic, Bridges, and Lopez functions were fitted to the data and compared using information criteria. For each function, a multilevel nonlinear mixed effects model was employed because....... Furthermore, studies should consider adding continuous autoregressive process when analyzing nonlinear mixed models with repeated measures....

  7. A 2 x 2 Taxonomy of Multilevel Latent Contextual Models: Accuracy-Bias Trade-Offs in Full and Partial Error Correction Models

    Science.gov (United States)

    Ludtke, Oliver; Marsh, Herbert W.; Robitzsch, Alexander; Trautwein, Ulrich

    2011-01-01

    In multilevel modeling, group-level variables (L2) for assessing contextual effects are frequently generated by aggregating variables from a lower level (L1). A major problem of contextual analyses in the social sciences is that there is no error-free measurement of constructs. In the present article, 2 types of error occurring in multilevel data…

  8. Phase-change memory: A continuous multilevel compact model of subthreshold conduction and threshold switching

    Science.gov (United States)

    Pigot, Corentin; Gilibert, Fabien; Reyboz, Marina; Bocquet, Marc; Zuliani, Paola; Portal, Jean-Michel

    2018-04-01

    Phase-change memory (PCM) compact modeling of the threshold switching based on a thermal runaway in Poole–Frenkel conduction is proposed. Although this approach is often used in physical models, this is the first time it is implemented in a compact model. The model accuracy is validated by a good correlation between simulations and experimental data collected on a PCM cell embedded in a 90 nm technology. A wide range of intermediate states is measured and accurately modeled with a single set of parameters, allowing multilevel programing. A good convergence is exhibited even in snapback simulation owing to this fully continuous approach. Moreover, threshold properties extraction indicates a thermally enhanced switching, which validates the basic hypothesis of the model. Finally, it is shown that this model is compliant with a new drift-resilient cell-state metric. Once enriched with a phase transition module, this compact model is ready to be implemented in circuit simulators.

  9. cudaBayesreg: Parallel Implementation of a Bayesian Multilevel Model for fMRI Data Analysis

    Directory of Open Access Journals (Sweden)

    Adelino R. Ferreira da Silva

    2011-10-01

    Full Text Available Graphic processing units (GPUs are rapidly gaining maturity as powerful general parallel computing devices. A key feature in the development of modern GPUs has been the advancement of the programming model and programming tools. Compute Unified Device Architecture (CUDA is a software platform for massively parallel high-performance computing on Nvidia many-core GPUs. In functional magnetic resonance imaging (fMRI, the volume of the data to be processed, and the type of statistical analysis to perform call for high-performance computing strategies. In this work, we present the main features of the R-CUDA package cudaBayesreg which implements in CUDA the core of a Bayesian multilevel model for the analysis of brain fMRI data. The statistical model implements a Gibbs sampler for multilevel/hierarchical linear models with a normal prior. The main contribution for the increased performance comes from the use of separate threads for fitting the linear regression model at each voxel in parallel. The R-CUDA implementation of the Bayesian model proposed here has been able to reduce significantly the run-time processing of Markov chain Monte Carlo (MCMC simulations used in Bayesian fMRI data analyses. Presently, cudaBayesreg is only configured for Linux systems with Nvidia CUDA support.

  10. Modeling, Development and Control of Multilevel Converters for Power System Application =

    Science.gov (United States)

    Vahedi, Hani

    The main goal of this project is to develop a multilevel converter topology to be useful in power system applications. Although many topologies are introduced rapidly using a bunch of switches and isolated dc sources, having a single-dc-source multilevel inverter is still a matter of controversy. In fact, each isolated dc source means a bulky transformer and a rectifier that have their own losses and costs forcing the industries to avoid entering in this topic conveniently. On the other hand, multilevel inverters topologies with single-dc-source require associated controllers to regulate the dc capacitors voltages in order to have multilevel voltage waveform at the output. Thus, a complex controller would not interest investors properly. Consequently, developing a single-dc-source multilevel inverter topology along with a light and reliable voltage control is still a challenging topic to replace the 2-level inverters in the market effectively. The first effort in this project was devoted to the PUC7 inverter to design a simple and yet efficient controller. A new modelling is performed on the PUC7 inverter and it has been simplified to first order system. Afterwards, a nonlinear cascaded controller is designed and applied to regulate the capacitor voltage at 1/3 of the DC source amplitude and to generate 7 identical voltage levels at the output supplying different type of loads such as RL or rectifier harmonic ones. In next work, the PUC5 topology is proposed as a remedy to the PUC7 that requires a complicated controller to operate properly. The capacitor voltage is regulated at half of dc source amplitude to generate 5 voltage levels at the output. Although the 7-level voltage waveform is replaced by a 5-level one in PUC5 topology, it is shown that the PUC5 needs a very simple and reliable voltage balancing technique due to having some redundant switching states. Moreover, a sensor-less voltage balancing technique is designed and implemented on the PUC5 inverter

  11. Multilevel flow models studio: human-centralized development for operation support system

    International Nuclear Information System (INIS)

    Zhou Yangping; Hidekazu Yoshikawa; Liu Jingquan; Yang Ming; Ouyang Jun

    2005-01-01

    Computerized Operation Support Systems (COSS), integrating Artificial Intelligence, Multimedia and Network Technology, are now being proposed for reducing operator's cognitive load for process operation. This study proposed a Human-Centralized Development (HCD) that COSS can be developed and maintained independently, conveniently and flexibly by operator and expert of industry system with little expertise on software development. A graphical interface system for HCD, Multilevel Flow Models Studio (MFMS), is proposed for development assistance of COSS. An Extensible Markup Language based file structure is designed to represent the Multilevel Flow Models (MFM) model for the target system. With a friendly graphical interface, MFMS mainly consists of two components: 1) an editor to intelligently assist user establish and maintain the MFM model; 2) an executor to implement the application for monitoring, diagnosis and operational instruction in terms of the established MFM model. A prototype MFMS system has been developed and applied to construct a trial operation support system for a Nuclear Power Plant simulated by RELAP5/MOD2. (authors)

  12. A Novel Method to Verify Multilevel Computational Models of Biological Systems Using Multiscale Spatio-Temporal Meta Model Checking.

    Science.gov (United States)

    Pârvu, Ovidiu; Gilbert, David

    2016-01-01

    Insights gained from multilevel computational models of biological systems can be translated into real-life applications only if the model correctness has been verified first. One of the most frequently employed in silico techniques for computational model verification is model checking. Traditional model checking approaches only consider the evolution of numeric values, such as concentrations, over time and are appropriate for computational models of small scale systems (e.g. intracellular networks). However for gaining a systems level understanding of how biological organisms function it is essential to consider more complex large scale biological systems (e.g. organs). Verifying computational models of such systems requires capturing both how numeric values and properties of (emergent) spatial structures (e.g. area of multicellular population) change over time and across multiple levels of organization, which are not considered by existing model checking approaches. To address this limitation we have developed a novel approximate probabilistic multiscale spatio-temporal meta model checking methodology for verifying multilevel computational models relative to specifications describing the desired/expected system behaviour. The methodology is generic and supports computational models encoded using various high-level modelling formalisms because it is defined relative to time series data and not the models used to generate it. In addition, the methodology can be automatically adapted to case study specific types of spatial structures and properties using the spatio-temporal meta model checking concept. To automate the computational model verification process we have implemented the model checking approach in the software tool Mule (http://mule.modelchecking.org). Its applicability is illustrated against four systems biology computational models previously published in the literature encoding the rat cardiovascular system dynamics, the uterine contractions of labour

  13. MULTI-LEVEL SAMPLING APPROACH FOR CONTINOUS LOSS DETECTION USING ITERATIVE WINDOW AND STATISTICAL MODEL

    OpenAIRE

    Mohd Fo'ad Rohani; Mohd Aizaini Maarof; Ali Selamat; Houssain Kettani

    2010-01-01

    This paper proposes a Multi-Level Sampling (MLS) approach for continuous Loss of Self-Similarity (LoSS) detection using iterative window. The method defines LoSS based on Second Order Self-Similarity (SOSS) statistical model. The Optimization Method (OM) is used to estimate self-similarity parameter since it is fast and more accurate in comparison with other estimation methods known in the literature. Probability of LoSS detection is introduced to measure continuous LoSS detection performance...

  14. The Life History Calendar Method and Multilevel Modeling: Application to Research on Intimate Partner Violence.

    Science.gov (United States)

    Yoshihama, Mieko; Bybee, Deborah

    2011-03-01

    Intimate partner violence (IPV) is prevalent and often recurrent in women's lives. To better understand the changing risk of IPV over the life course, which could guide more effective policies and program responses, methodological innovations are needed. Life History Calendar methods enhance respondents' recall of the timing of specific types of IPV experienced over the life course. Multilevel modeling provides a way to analyze individual and collective trajectories and examine covariates of IPV risk. We apply these complementary methods to examine IPV trajectories for a sample of women of Filipina descent living in the United States, examining life course timing and cohort effects. © The Author(s) 2011.

  15. Representing Operational Knowledge of PWR Plant by Using Multilevel Flow Modelling

    DEFF Research Database (Denmark)

    Zhang, Xinxin; Lind, Morten; Jørgensen, Sten Bay

    2014-01-01

    situation and support operational decisions. This paper will provide a general MFM model of the primary side in a standard Westinghouse Pressurized Water Reactor ( PWR ) system including sub - systems of Reactor Coolant System, Rod Control System, Chemical and Volume Control System, emergency heat removal......The aim of this paper is to explore the capability of representing operational knowledge by using Multilevel Flow Modelling ( MFM ) methodology. The paper demonstrate s how the operational knowledge can be inserted into the MFM models and be used to evaluate the plant state, identify the current...... systems. And the sub - systems’ functions will be decomposed into sub - models according to different operational situations. An operational model will be developed based on the operating procedure by using MFM symbols and this model can be used to implement coordination rules for organize the utilizati...

  16. Study of visualized simulation and analysis of nuclear fuel cycle system based on multilevel flow model

    International Nuclear Information System (INIS)

    Liu Jingquan; Yoshikawa, H.; Zhou Yangping

    2005-01-01

    Complex energy and environment system, especially nuclear fuel cycle system recently raised social concerns about the issues of economic competitiveness, environmental effect and nuclear proliferation. Only under the condition that those conflicting issues are gotten a consensus between stakeholders with different knowledge background, can nuclear power industry be continuingly developed. In this paper, a new analysis platform has been developed to help stakeholders to recognize and analyze various socio-technical issues in the nuclear fuel cycle sys- tem based on the functional modeling method named Multilevel Flow Models (MFM) according to the cognition theory of human being, Its character is that MFM models define a set of mass, energy and information flow structures on multiple levels of abstraction to describe the functional structure of a process system and its graphical symbol representation and the means-end and part-whole hierarchical flow structure to make the represented process easy to be understood. Based upon this methodology, a micro-process and a macro-process of nuclear fuel cycle system were selected to be simulated and some analysis processes such as economics analysis, environmental analysis and energy balance analysis related to those flows were also integrated to help stakeholders to understand the process of decision-making with the introduction of some new functions for the improved Multilevel Flow Models Studio, and finally the simple simulation such as spent fuel management process simulation and money flow of nuclear fuel cycle and its levelised cost analysis will be represented as feasible examples. (authors)

  17. Study of visualized simulation and analysis of nuclear fuel cycle system based on multilevel flow model

    Institute of Scientific and Technical Information of China (English)

    LIU Jing-Quan; YOSHIKAWA Hidekazu; ZHOU Yang-Ping

    2005-01-01

    Complex energy and environment system, especially nuclear fuel cycle system recently raised social concerns about the issues of economic competitiveness, environmental effect and nuclear proliferation. Only under the condition that those conflicting issues are gotten a consensus between stakeholders with different knowledge background, can nuclear power industry be continuingly developed. In this paper, a new analysis platform has been developed to help stakeholders to recognize and analyze various socio-technical issues in the nuclear fuel cycle system based on the functional modeling method named Multilevel Flow Models (MFM) according to the cognition theory of human being. Its character is that MFM models define a set of mass, energy and information flow structures on multiple levels of abstraction to describe the functional structure of a process system and its graphical symbol representation and the means-end and part-whole hierarchical flow structure to make the represented process easy to be understood. Based upon this methodology, a micro-process and a macro-process of nuclear fuel cycle system were selected to be simulated and some analysis processes such as economics analysis, environmental analysis and energy balance analysis related to those flows were also integrated to help stakeholders to understand the process of decision-making with the introduction of some new functions for the improved Multilevel Flow Models Studio, and finally the simple simulation such as spent fuel management process simulation and money flow of nuclear fuel cycle and its levelised cost analysis will be represented as feasible examples.

  18. Dispositional and Environmental Predictors of the Development of Internalizing Problems in Childhood: Testing a Multilevel Model.

    Science.gov (United States)

    Hastings, Paul D; Helm, Jonathan; Mills, Rosemary S L; Serbin, Lisa A; Stack, Dale M; Schwartzman, Alex E

    2015-07-01

    This investigation evaluated a multilevel model of dispositional and environmental factors contributing to the development of internalizing problems from preschool-age to school-age. In a sample of 375 families (185 daughters, 190 sons) drawn from three independent samples, preschoolers' behavioral inhibition, cortisol and gender were examined as moderators of the links between mothers' negative parenting behavior, negative emotional characteristics, and socioeconomic status when children were 3.95 years, and their internalizing problems when they were 8.34 years. Children's dispositional characteristics moderated all associations between these environmental factors and mother-reported internalizing problems in patterns that were consistent with either diathesis-stress or differential-susceptibility models of individual-environment interaction, and with gender models of developmental psychopathology. Greater inhibition and lower socioeconomic status were directly predictive of more teacher reported internalizing problems. These findings highlight the importance of using multilevel models within a bioecological framework to understand the complex pathways through which internalizing difficulties develop.

  19. Site-Specific Multilevel Modeling of Potato Response to Nitrogen Fertilization

    Directory of Open Access Journals (Sweden)

    Serge-Étienne Parent

    2017-12-01

    Full Text Available Technologies of precision agriculture, digital soil maps, and meteorological stations provide a minimum data set to guide precision farming operations. However, determining optimal nutrient requirements for potato (Solanum tuberosum L. crops at subfield scale remains a challenge given specific climatic, edaphic, and managerial conditions. Multilevel modeling can generalize yield response to fertilizer additions using data easily accessible to growers. Our objective was to elaborate a multilevel N fertilizer response model for potato crops using the Mitscherlich equation and a core data set of 93 N fertilizer trials conducted in Québec, Canada. Daily climatic data were collected at 10 × 10 km resolution. Soils were characterized by organic matter content, pH, and texture in the arable layer, and by texture and tools of pedometrics across a gleization-podzolization continuum in subsoil layers. There were five categories of preceding crops and five cultivar maturity orders. The three Mitscherlich parameters (Asymptote, Rate, and Environment were most often site-specific. Sensitivity analysis showed that optimum N dosage increased with non-leguminous high-residue preceding crops, coarser soils, podzolization, drier climatic condition, and late cultivar maturity. The inferential model could guide site-specific N fertilization using an accessible minimum data set to support fertilization decisions. As decision-support system, the model could also provide a range of optimum N doses across a large spectrum of site-specific conditions including climate change.

  20. A multilevel model of organizational health culture and the effectiveness of health promotion.

    Science.gov (United States)

    Lin, Yea-Wen; Lin, Yueh-Ysen

    2014-01-01

    Organizational health culture is a health-oriented core characteristic of the organization that is shared by all members. It is effective in regulating health-related behavior for employees and could therefore influence the effectiveness of health promotion efforts among organizations and employees. This study applied a multilevel analysis to verify the effects of organizational health culture on the organizational and individual effectiveness of health promotion. At the organizational level, we investigated the effect of organizational health culture on the organizational effectiveness of health promotion. At the individual level, we adopted a cross-level analysis to determine if organizational health culture affects employee effectiveness through the mediating effect of employee health behavior. The study setting consisted of the workplaces of various enterprises. We selected 54 enterprises in Taiwan and surveyed 20 full-time employees from each organization, for a total sample of 1011 employees. We developed the Organizational Health Culture Scale to measure employee perceptions and aggregated the individual data to formulate organization-level data. Organizational effectiveness of health promotion included four dimensions: planning effectiveness, production, outcome, and quality, which were measured by scale or objective indicators. The Health Promotion Lifestyle Scale was adopted for the measurement of health behavior. Employee effectiveness was measured subjectively in three dimensions: self-evaluated performance, altruism, and happiness. Following the calculation of descriptive statistics, hierarchical linear modeling (HLM) was used to test the multilevel hypotheses. Organizational health culture had a significant effect on the planning effectiveness (β = .356, p production (β = .359, p promotion. In addition, results of cross-level moderating effect analysis by HLM demonstrated that the effects of organizational health culture on three dimensions of

  1. [A multilevel model analysis of correlation between population characteristics and work ability of employees].

    Science.gov (United States)

    Zhang, Lei; Huang, Chunping; Lan, Yajia; Wang, Mianzhen

    2015-12-01

    To analyze the correlation between population characteristics and work ability of employees with a multilevel model, to investigate the important influencing factors for work ability, and to provide a basis for improvement in work ability. Work ability index (WAI)was applied to measure the work ability of 1686 subjects from different companies (n=6). MLwi N2.0 software was applied for two-level variance component model fitting. The WAI of employees showed differences between various companies (χ2=3.378 6, P=0.0660); working years was negatively correlated with WAI (χ2=38.229 2, P=0.0001), and the WAI of the employees with 20 or more working years was 1.63 lower than that of the employees with less than 20 working years; the work ability of manual workers was lower than that of mental-manual workers (χ2=8.2726, P=0.0040), and the work ability showed no significant difference between mental workers and mental-manual workers (χ2=2.086 0, P=0.148 7). From the perspective of probability, the multilevel model analysis reveals the differences in work ability of employees between different companies, and suggests that company, work type, and working years are the important influencing factors for work ability of employees. These factors should be improved and adjusted to protect or enhance the work ability of employees.

  2. Agent-based model with multi-level herding for complex financial systems

    Science.gov (United States)

    Chen, Jun-Jie; Tan, Lei; Zheng, Bo

    2015-02-01

    In complex financial systems, the sector structure and volatility clustering are respectively important features of the spatial and temporal correlations. However, the microscopic generation mechanism of the sector structure is not yet understood. Especially, how to produce these two features in one model remains challenging. We introduce a novel interaction mechanism, i.e., the multi-level herding, in constructing an agent-based model to investigate the sector structure combined with volatility clustering. According to the previous market performance, agents trade in groups, and their herding behavior comprises the herding at stock, sector and market levels. Further, we propose methods to determine the key model parameters from historical market data, rather than from statistical fitting of the results. From the simulation, we obtain the sector structure and volatility clustering, as well as the eigenvalue distribution of the cross-correlation matrix, for the New York and Hong Kong stock exchanges. These properties are in agreement with the empirical ones. Our results quantitatively reveal that the multi-level herding is the microscopic generation mechanism of the sector structure, and provide new insight into the spatio-temporal interactions in financial systems at the microscopic level.

  3. Bayesian Mixed Hidden Markov Models: A Multi-Level Approach to Modeling Categorical Outcomes with Differential Misclassification

    Science.gov (United States)

    Zhang, Yue; Berhane, Kiros

    2014-01-01

    Questionnaire-based health status outcomes are often prone to misclassification. When studying the effect of risk factors on such outcomes, ignoring any potential misclassification may lead to biased effect estimates. Analytical challenges posed by these misclassified outcomes are further complicated when simultaneously exploring factors for both the misclassification and health processes in a multi-level setting. To address these challenges, we propose a fully Bayesian Mixed Hidden Markov Model (BMHMM) for handling differential misclassification in categorical outcomes in a multi-level setting. The BMHMM generalizes the traditional Hidden Markov Model (HMM) by introducing random effects into three sets of HMM parameters for joint estimation of the prevalence, transition and misclassification probabilities. This formulation not only allows joint estimation of all three sets of parameters, but also accounts for cluster level heterogeneity based on a multi-level model structure. Using this novel approach, both the true health status prevalence and the transition probabilities between the health states during follow-up are modeled as functions of covariates. The observed, possibly misclassified, health states are related to the true, but unobserved, health states and covariates. Results from simulation studies are presented to validate the estimation procedure, to show the computational efficiency due to the Bayesian approach and also to illustrate the gains from the proposed method compared to existing methods that ignore outcome misclassification and cluster level heterogeneity. We apply the proposed method to examine the risk factors for both asthma transition and misclassification in the Southern California Children's Health Study (CHS). PMID:24254432

  4. Multilevel Modeling of Distributed Denial of Service Attacks in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Katarzyna Mazur

    2016-01-01

    Full Text Available The growing popularity of wireless sensor networks increases the risk of security attacks. One of the most common and dangerous types of attack that takes place these days in any electronic society is a distributed denial of service attack. Due to the resource constraint nature of mobile sensors, DDoS attacks have become a major threat to its stability. In this paper, we established a model of a structural health monitoring network, being disturbed by one of the most common types of DDoS attacks, the flooding attack. Through a set of simulations, we explore the scope of flood-based DDoS attack problem, assessing the performance and the lifetime of the network under the attack condition. To conduct our research, we utilized the Quality of Protection Modeling Language. With the proposed approach, it was possible to examine numerous network configurations, parameters, attack options, and scenarios. The results of the carefully performed multilevel analysis allowed us to identify a new kind of DDoS attack, the delayed distributed denial of service, by the authors, referred to as DDDoS attack. Multilevel approach to DDoS attack analysis confirmed that, examining endangered environments, it is significant to take into account many characteristics at once, just to not overlook any important aspect.

  5. Multilevel modeling and panel data analysis in educational research (Case study: National examination data senior high school in West Java)

    Science.gov (United States)

    Zulvia, Pepi; Kurnia, Anang; Soleh, Agus M.

    2017-03-01

    Individual and environment are a hierarchical structure consist of units grouped at different levels. Hierarchical data structures are analyzed based on several levels, with the lowest level nested in the highest level. This modeling is commonly call multilevel modeling. Multilevel modeling is widely used in education research, for example, the average score of National Examination (UN). While in Indonesia UN for high school student is divided into natural science and social science. The purpose of this research is to develop multilevel and panel data modeling using linear mixed model on educational data. The first step is data exploration and identification relationships between independent and dependent variable by checking correlation coefficient and variance inflation factor (VIF). Furthermore, we use a simple model approach with highest level of the hierarchy (level-2) is regency/city while school is the lowest of hierarchy (level-1). The best model was determined by comparing goodness-of-fit and checking assumption from residual plots and predictions for each model. Our finding that for natural science and social science, the regression with random effects of regency/city and fixed effects of the time i.e multilevel model has better performance than the linear mixed model in explaining the variability of the dependent variable, which is the average scores of UN.

  6. A Multi-Level Model of Information Seeking in the Clinical Domain

    Science.gov (United States)

    Hung, Peter W.; Johnson, Stephen B.; Kaufman, David R.; Mendonça, Eneida A.

    2008-01-01

    Objective: Clinicians often have difficulty translating information needs into effective search strategies to find appropriate answers. Information retrieval systems employing an intelligent search agent that generates adaptive search strategies based on human search expertise could be helpful in meeting clinician information needs. A prerequisite for creating such systems is an information seeking model that facilitates the representation of human search expertise. The purpose of developing such a model is to provide guidance to information seeking system development and to shape an empirical research program. Design: The information seeking process was modeled as a complex problem-solving activity. After considering how similarly complex activities had been modeled in other domains, we determined that modeling context-initiated information seeking across multiple problem spaces allows the abstraction of search knowledge into functionally consistent layers. The knowledge layers were identified in the information science literature and validated through our observations of searches performed by health science librarians. Results: A hierarchical multi-level model of context-initiated information seeking is proposed. Each level represents (1) a problem space that is traversed during the online search process, and (2) a distinct layer of knowledge that is required to execute a successful search. Grand strategy determines what information resources will be searched, for what purpose, and in what order. The strategy level represents an overall approach for searching a single resource. Tactics are individual moves made to further a strategy. Operations are mappings of abstract intentions to information resource-specific concrete input. Assessment is the basis of interaction within the strategic hierarchy, influencing the direction of the search. Conclusion: The described multi-level model provides a framework for future research and the foundation for development of an

  7. Data Model Approach And Markov Chain Based Analysis Of Multi-Level Queue Scheduling

    Directory of Open Access Journals (Sweden)

    Diwakar Shukla

    2010-01-01

    Full Text Available There are many CPU scheduling algorithms inliterature like FIFO, Round Robin, Shortest-Job-First and so on.The Multilevel-Queue-Scheduling is superior to these due to itsbetter management of a variety of processes. In this paper, aMarkov chain model is used for a general setup of Multilevelqueue-scheduling and the scheduler is assumed to performrandom movement on queue over the quantum of time.Performance of scheduling is examined through a rowdependent data model. It is found that with increasing value of αand d, the chance of system going over the waiting state reduces.At some of the interesting combinations of α and d, it diminishesto zero, thereby, provides us some clue regarding better choice ofqueues over others for high priority jobs. It is found that ifqueue priorities are added in the scheduling intelligently thenbetter performance could be obtained. Data model helpschoosing appropriate preferences.

  8. A multi-level model of emerging technology: An empirical study of the evolution of biotechnology from 1976 to 2003

    Science.gov (United States)

    van Witteloostuijn, Arjen

    2018-01-01

    In this paper, we develop an ecological, multi-level model that can be used to study the evolution of emerging technology. More specifically, by defining technology as a system composed of a set of interacting components, we can build upon the argument of multi-level density dependence from organizational ecology to develop a distribution-independent model of technological evolution. This allows us to distinguish between different stages of component development, which provides more insight into the emergence of stable component configurations, or dominant designs. We validate our hypotheses in the biotechnology industry by using patent data from the USPTO from 1976 to 2003. PMID:29795575

  9. Simulation model of harmonics reduction technique using shunt active filter by cascade multilevel inverter method

    Science.gov (United States)

    Andreh, Angga Muhamad; Subiyanto, Sunardiyo, Said

    2017-01-01

    Development of non-linear loading in the application of industry and distribution system and also harmonic compensation becomes important. Harmonic pollution is an urgent problem in increasing power quality. The main contribution of the study is the modeling approach used to design a shunt active filter and the application of the cascade multilevel inverter topology to improve the power quality of electrical energy. In this study, shunt active filter was aimed to eliminate dominant harmonic component by injecting opposite currents with the harmonic component system. The active filter was designed by shunt configuration with cascaded multilevel inverter method controlled by PID controller and SPWM. With this shunt active filter, the harmonic current can be reduced so that the current wave pattern of the source is approximately sinusoidal. Design and simulation were conducted by using Power Simulator (PSIM) software. Shunt active filter performance experiment was conducted on the IEEE four bus test system. The result of shunt active filter installation on the system (IEEE four bus) could reduce THD current from 28.68% to 3.09%. With this result, the active filter can be applied as an effective method to reduce harmonics.

  10. Illustration interface of accident progression in PWR by quick inference based on multilevel flow models

    International Nuclear Information System (INIS)

    Yoshikawa, H.; Ouyang, J.; Niwa, Y.

    2006-01-01

    In this paper, a new accident inference method is proposed by using a goal and function oriented modeling method called Multilevel Flow Model focusing on explaining the causal-consequence relations and the objective of automatic action in the accident of nuclear power plant. Users can easily grasp how the various plant parameters will behave and how the various safety facilities will be activated sequentially to cope with the accident until the nuclear power plants are settled into safety state, i.e., shutdown state. The applicability of the developed method was validated by the conduction of internet-based 'view' experiment to the voluntary respondents, and in the future, further elaboration of interface design and the further introduction of instruction contents will be developed to make it become the usable CAI system. (authors)

  11. Real-Time Model and Simulation Architecture for Half- and Full-Bridge Modular Multilevel Converters

    Science.gov (United States)

    Ashourloo, Mojtaba

    This work presents an equivalent model and simulation architecture for real-time electromagnetic transient analysis of either half-bridge or full-bridge modular multilevel converter (MMC) with 400 sub-modules (SMs) per arm. The proposed CPU/FPGA-based architecture is optimized for the parallel implementation of the presented MMC model on the FPGA and is beneficiary of a high-throughput floating-point computational engine. The developed real-time simulation architecture is capable of simulating MMCs with 400 SMs per arm at 825 nanoseconds. To address the difficulties of the sorting process implementation, a modified Odd-Even Bubble sorting is presented in this work. The comparison of the results under various test scenarios reveals that the proposed real-time simulator is representing the system responses in the same way of its corresponding off-line counterpart obtained from the PSCAD/EMTDC program.

  12. From least squares to multilevel modeling: A graphical introduction to Bayesian inference

    Science.gov (United States)

    Loredo, Thomas J.

    2016-01-01

    This tutorial presentation will introduce some of the key ideas and techniques involved in applying Bayesian methods to problems in astrostatistics. The focus will be on the big picture: understanding the foundations (interpreting probability, Bayes's theorem, the law of total probability and marginalization), making connections to traditional methods (propagation of errors, least squares, chi-squared, maximum likelihood, Monte Carlo simulation), and highlighting problems where a Bayesian approach can be particularly powerful (Poisson processes, density estimation and curve fitting with measurement error). The "graphical" component of the title reflects an emphasis on pictorial representations of some of the math, but also on the use of graphical models (multilevel or hierarchical models) for analyzing complex data. Code for some examples from the talk will be available to participants, in Python and in the Stan probabilistic programming language.

  13. PARALLEL ADAPTIVE MULTILEVEL SAMPLING ALGORITHMS FOR THE BAYESIAN ANALYSIS OF MATHEMATICAL MODELS

    KAUST Repository

    Prudencio, Ernesto; Cheung, Sai Hung

    2012-01-01

    In recent years, Bayesian model updating techniques based on measured data have been applied to many engineering and applied science problems. At the same time, parallel computational platforms are becoming increasingly more powerful and are being used more frequently by the engineering and scientific communities. Bayesian techniques usually require the evaluation of multi-dimensional integrals related to the posterior probability density function (PDF) of uncertain model parameters. The fact that such integrals cannot be computed analytically motivates the research of stochastic simulation methods for sampling posterior PDFs. One such algorithm is the adaptive multilevel stochastic simulation algorithm (AMSSA). In this paper we discuss the parallelization of AMSSA, formulating the necessary load balancing step as a binary integer programming problem. We present a variety of results showing the effectiveness of load balancing on the overall performance of AMSSA in a parallel computational environment.

  14. How structure shapes dynamics: knowledge development in Wikipedia--a network multilevel modeling approach.

    Directory of Open Access Journals (Sweden)

    Iassen Halatchliyski

    Full Text Available Using a longitudinal network analysis approach, we investigate the structural development of the knowledge base of Wikipedia in order to explain the appearance of new knowledge. The data consists of the articles in two adjacent knowledge domains: psychology and education. We analyze the development of networks of knowledge consisting of interlinked articles at seven snapshots from 2006 to 2012 with an interval of one year between them. Longitudinal data on the topological position of each article in the networks is used to model the appearance of new knowledge over time. Thus, the structural dimension of knowledge is related to its dynamics. Using multilevel modeling as well as eigenvector and betweenness measures, we explain the significance of pivotal articles that are either central within one of the knowledge domains or boundary-crossing between the two domains at a given point in time for the future development of new knowledge in the knowledge base.

  15. Work information and emotional support of self-initiated expatriates: multilevel mediation model

    DEFF Research Database (Denmark)

    Kubovcikova, Annamária; van Bakel, Marian

    of the network members with the type and amount of support they provide. The dataset consisted of 165 expatriates who rated 575 of their network members on the following learned characteristics: host country knowledge, employment status, and host country origin. The ego-centered network that consists...... of the rated ties is the context in which expatriates are embedded. It was therefore analyzed utilizing a multilevel mediation model. We have hypothesized that all learned characteristics will be determining the frequency of interaction and thus the level and type of support received. Host country knowledge......This article explores the immediate network context of self-initiated expatriates and how it influences their work information and emotional support. Building on the information seeking theory and the theory of weak and strong ties, we have created a model connecting specific characteristics...

  16. Study on reliability analysis based on multilevel flow models and fault tree method

    International Nuclear Information System (INIS)

    Chen Qiang; Yang Ming

    2014-01-01

    Multilevel flow models (MFM) and fault tree method describe the system knowledge in different forms, so the two methods express an equivalent logic of the system reliability under the same boundary conditions and assumptions. Based on this and combined with the characteristics of MFM, a method mapping MFM to fault tree was put forward, thus providing a way to establish fault tree rapidly and realizing qualitative reliability analysis based on MFM. Taking the safety injection system of pressurized water reactor nuclear power plant as an example, its MFM was established and its reliability was analyzed qualitatively. The analysis result shows that the logic of mapping MFM to fault tree is correct. The MFM is easily understood, created and modified. Compared with the traditional fault tree analysis, the workload is greatly reduced and the modeling time is saved. (authors)

  17. Multi-level emulation of complex climate model responses to boundary forcing data

    Science.gov (United States)

    Tran, Giang T.; Oliver, Kevin I. C.; Holden, Philip B.; Edwards, Neil R.; Sóbester, András; Challenor, Peter

    2018-04-01

    Climate model components involve both high-dimensional input and output fields. It is desirable to efficiently generate spatio-temporal outputs of these models for applications in integrated assessment modelling or to assess the statistical relationship between such sets of inputs and outputs, for example, uncertainty analysis. However, the need for efficiency often compromises the fidelity of output through the use of low complexity models. Here, we develop a technique which combines statistical emulation with a dimensionality reduction technique to emulate a wide range of outputs from an atmospheric general circulation model, PLASIM, as functions of the boundary forcing prescribed by the ocean component of a lower complexity climate model, GENIE-1. Although accurate and detailed spatial information on atmospheric variables such as precipitation and wind speed is well beyond the capability of GENIE-1's energy-moisture balance model of the atmosphere, this study demonstrates that the output of this model is useful in predicting PLASIM's spatio-temporal fields through multi-level emulation. Meaningful information from the fast model, GENIE-1 was extracted by utilising the correlation between variables of the same type in the two models and between variables of different types in PLASIM. We present here the construction and validation of several PLASIM variable emulators and discuss their potential use in developing a hybrid model with statistical components.

  18. Three-level multilevel growth models for nested change data: a guide for group treatment researchers.

    Science.gov (United States)

    Tasca, Giorgio A; Illing, Vanessa; Joyce, Anthony S; Ogrodniczuk, John S

    2009-07-01

    Researchers have known for years about the negative impact on Type I error rates caused by dependencies in hierarchically nested and longitudinal data. Despite this, group treatment researchers do not consistently use methods such as multilevel models (MLMs) to assess dependence and appropriately analyse their nested data. The goals of this study are to review some of the study design issues with regard to hierarchically nested and longitudinal data, discuss MLMs for assessing and handling dependence in data, and present a guide for developing a three-level growth MLM that is appropriate for group treatment data, design, and research questions. The authors present an example from group treatment research to illustrate these issues and methods.

  19. What it takes to get proactive: An integrative multilevel model of the antecedents of personal initiative.

    Science.gov (United States)

    Hong, Ying; Liao, Hui; Raub, Steffen; Han, Joo Hun

    2016-05-01

    Building upon and extending Parker, Bindl, and Strauss's (2010) theory of proactive motivation, we develop an integrated, multilevel model to examine how contextual factors shape employees' proactive motivational states and, through these proactive motivational states, influence their personal initiative behavior. Using data from a sample of hotels collected from 3 sources and over 2 time periods, we show that establishment-level initiative-enhancing human resource management (HRM) systems were positively related to departmental initiative climate, which was positively related to employee personal initiative through employee role-breadth self-efficacy. Further, department-level empowering leadership was positively related to initiative climate only when initiative-enhancing HRM systems were low. These findings offer interesting implications for research on personal initiative and for the management of employee proactivity in organizations. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  20. Does inequality erode social trust? Results from multilevel models of US states and counties.

    Science.gov (United States)

    Fairbrother, Malcolm; Martin, Isaac W

    2013-03-01

    Previous research has argued that income inequality reduces people's trust in other people, and that declining social trust in the United States in recent decades has been due to rising levels of income inequality. Using multilevel models fitted to data from the General Social Survey, this paper substantially qualifies these arguments. We show that while people are less trusting in US states with higher income inequality, this association holds only cross-sectionally, not longitudinally; since the 1970s, states experiencing larger increases in inequality have not suffered systematically larger declines in trust. For counties, there is no statistically significant relationship either cross-sectionally or longitudinally. There is therefore only limited empirical support for the argument that inequality influences generalized social trust; and the declining trust of recent decades certainly cannot be attributed to rising inequality. Copyright © 2012 Elsevier Inc. All rights reserved.

  1. A Multilevel Latent Growth Modelling of the Longitudinal Changes in Motivation Regulations in Physical Education

    Directory of Open Access Journals (Sweden)

    Timo Jaakkola

    2015-03-01

    Full Text Available The purpose of this study was to examine individual- and classroom-level differences in the longitudinal change in motivational regulations during physical education students’ transition from elementary (Grade 6 across middle school (Grades 7 to 9. A sample of 757 Finnish adolescents (M = 12.71, SD = 0.23 participated in this study. Participants of the study responded to questionnaires collected six times. A multilevel latent growth modelling approach was used to analyze the data. Results showed that motivational regulations in physical education developed at different rates during middle school. More specifically, students’: (a identified regulation increased across Grades 6 to 9; (b amotivation increased during middle school transition from Grade 6 to 7; and (c introjected regulation declined from Grade 8 to 9. Other motivational regulations remained stable across time. The changes in amotivation and introjected regulation were largely due to individual factors, whereas the changes in identified regulation were due to environmental factors.

  2. Workplace accommodations for employees with disabilities: A multilevel model of employer decision-making.

    Science.gov (United States)

    Telwatte, Apsara; Anglim, Jeromy; Wynton, Sarah K A; Moulding, Richard

    2017-02-01

    Existing research suggests that the decision to grant or deny workplace accommodations for people with disabilities is influenced by a range of legal and nonlegal factors. However, less is known about how these factors operate at the within-person level. Thus, we proposed and tested a multilevel model of the accommodation decision-making process, which we applied to better understand why people with psychological disabilities often experience greater challenges in obtaining accommodations. A sample of 159 Australian adults, composed mostly of managers and HR professionals, read 12 vignettes involving requests for accommodations from existing employees. The requests differed in whether they were for psychological or physical disabilities. For each vignette, participants rated their empathy with the employee, the legitimacy of the employee's disability, the necessity for productivity, the perceived cost, and the reasonableness, and indicated whether they would grant the accommodation. Multilevel modeling indicated that greater empathy, legitimacy, and necessity, and lower perceived cost predicted perceptions of greater reasonableness and greater granting. Accommodation requests from employees with psychological disabilities were seen as less reasonable and were less likely to be granted; much of this effect seemed to be driven by perceptions that such accommodations were less necessary for productivity. Ratings on accommodations were influenced both by general between-person tendencies and within-person appraisals of particular scenarios. The study points to a need for organizations to more clearly establish guidelines for how decision-makers should fairly evaluate accommodation requests for employees with psychological disabilities and disability more broadly. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  3. Explaining Variance and Identifying Predictors of Children's Communication via a Multilevel Model of Single-Case Design Research: Brief Report

    Science.gov (United States)

    Ottley, Jennifer Riggie; Ferron, John M.; Hanline, Mary Frances

    2016-01-01

    The purpose of this study was to explain the variability in data collected from a single-case design study and to identify predictors of communicative outcomes for children with developmental delays or disabilities (n = 4). Using SAS® University Edition, we fit multilevel models with time nested within children. Children's level of baseline…

  4. Correction: Keep Calm and Learn Multilevel Logistic Modeling: A Simplified Three-Step Procedure Using Stata, R, Mplus, and SPSS

    Directory of Open Access Journals (Sweden)

    Nicolas Sommet

    2017-12-01

    Full Text Available This article details a correction to the article: Sommet, N. & Morselli, D., (2017. Keep Calm and Learn Multilevel Logistic Modeling: A Simplified Three-Step Procedure Using Stata, R, Mplus, and SPSS. 'International Review of Social Psychology'. 30(1, pp. 203–218. DOI: https://doi.org/10.5334/irsp.90

  5. Pretest-Posttest-Posttest Multilevel IRT Modeling of Competence Growth of Students in Higher Education in Germany

    NARCIS (Netherlands)

    Schmidt, Susanne; Zlatkin-Troitschanskaia, Olga; Fox, Gerardus J.A.

    2016-01-01

    Longitudinal research in higher education faces several challenges. Appropriate methods of analyzing competence growth of students are needed to deal with those challenges and thereby obtain valid results. In this article, a pretest-posttest-posttest multivariate multilevel IRT model for repeated

  6. Taiwanese Students' Science Learning Self-Efficacy and Teacher and Student Science Hardiness: A Multilevel Model Approach

    Science.gov (United States)

    Wang, Ya-Ling; Tsai, Chin-Chung

    2016-01-01

    This study aimed to investigate the factors accounting for science learning self-efficacy (the specific beliefs that people have in their ability to complete tasks in science learning) from both the teacher and the student levels. We thus propose a multilevel model to delineate its relationships with teacher and student science hardiness (i.e.,…

  7. Friendship Dissolution Within Social Networks Modeled Through Multilevel Event History Analysis

    Science.gov (United States)

    Dean, Danielle O.; Bauer, Daniel J.; Prinstein, Mitchell J.

    2018-01-01

    A social network perspective can bring important insight into the processes that shape human behavior. Longitudinal social network data, measuring relations between individuals over time, has become increasingly common—as have the methods available to analyze such data. A friendship duration model utilizing discrete-time multilevel survival analysis with a multiple membership random effect structure is developed and applied here to study the processes leading to undirected friendship dissolution within a larger social network. While the modeling framework is introduced in terms of understanding friendship dissolution, it can be used to understand microlevel dynamics of a social network more generally. These models can be fit with standard generalized linear mixed-model software, after transforming the data to a pair-period data set. An empirical example highlights how the model can be applied to understand the processes leading to friendship dissolution between high school students, and a simulation study is used to test the use of the modeling framework under representative conditions that would be found in social network data. Advantages of the modeling framework are highlighted, and potential limitations and future directions are discussed. PMID:28463022

  8. The Effects of Autonomy and Empowerment on Employee Turnover: Test of a Multilevel Model in Teams

    Science.gov (United States)

    Liu, Dong; Zhang, Shu; Wang, Lei; Lee, Thomas W.

    2011-01-01

    Extending research on voluntary turnover in the team setting, this study adopts a multilevel self-determination theoretical approach to examine the unique roles of individual and social-contextual motivational precursors, autonomy orientation and autonomy support, in reducing team member voluntary turnover. Analysis of multilevel time-lagged data…

  9. Multilevel regression models describing regional patterns of invertebrate and algal responses to urbanization across the USA

    Science.gov (United States)

    Cuffney, T.F.; Kashuba, R.; Qian, S.S.; Alameddine, I.; Cha, Y.K.; Lee, B.; Coles, J.F.; McMahon, G.

    2011-01-01

    Multilevel hierarchical regression was used to examine regional patterns in the responses of benthic macroinvertebrates and algae to urbanization across 9 metropolitan areas of the conterminous USA. Linear regressions established that responses (intercepts and slopes) to urbanization of invertebrates and algae varied among metropolitan areas. Multilevel hierarchical regression models were able to explain these differences on the basis of region-scale predictors. Regional differences in the type of land cover (agriculture or forest) being converted to urban and climatic factors (precipitation and air temperature) accounted for the differences in the response of macroinvertebrates to urbanization based on ordination scores, total richness, Ephemeroptera, Plecoptera, Trichoptera richness, and average tolerance. Regional differences in climate and antecedent agriculture also accounted for differences in the responses of salt-tolerant diatoms, but differences in the responses of other diatom metrics (% eutraphenic, % sensitive, and % silt tolerant) were best explained by regional differences in soils (mean % clay soils). The effects of urbanization were most readily detected in regions where forest lands were being converted to urban land because agricultural development significantly degraded assemblages before urbanization and made detection of urban effects difficult. The effects of climatic factors (temperature, precipitation) on background conditions (biogeographic differences) and rates of response to urbanization were most apparent after accounting for the effects of agricultural development. The effects of climate and land cover on responses to urbanization provide strong evidence that monitoring, mitigation, and restoration efforts must be tailored for specific regions and that attainment goals (background conditions) may not be possible in regions with high levels of prior disturbance (e.g., agricultural development). ?? 2011 by The North American

  10. Big data privacy protection model based on multi-level trusted system

    Science.gov (United States)

    Zhang, Nan; Liu, Zehua; Han, Hongfeng

    2018-05-01

    This paper introduces and inherit the multi-level trusted system model that solves the Trojan virus by encrypting the privacy of user data, and achieve the principle: "not to read the high priority hierarchy, not to write the hierarchy with low priority". Thus ensuring that the low-priority data privacy leak does not affect the disclosure of high-priority data privacy. This paper inherits the multi-level trustworthy system model of Trojan horse and divides seven different risk levels. The priority level 1˜7 represent the low to high value of user data privacy, and realize seven kinds of encryption with different execution efficiency Algorithm, the higher the priority, the greater the value of user data privacy, at the expense of efficiency under the premise of choosing a more encrypted encryption algorithm to ensure data security. For enterprises, the price point is determined by the unit equipment users to decide the length of time. The higher the risk sub-group algorithm, the longer the encryption time. The model assumes that users prefer the lower priority encryption algorithm to ensure efficiency. This paper proposes a privacy cost model for each of the seven risk subgroups. Among them, the higher the privacy cost, the higher the priority of the risk sub-group, the higher the price the user needs to pay to ensure the privacy of the data. Furthermore, by introducing the existing pricing model of economics and the human traffic model proposed by this paper and fluctuating with the market demand, this paper improves the price of unit products when the market demand is low. On the other hand, when the market demand increases, the profit of the enterprise will be guaranteed under the guidance of the government by reducing the price per unit of product. Then, this paper introduces the dynamic factors of consumers' mood and age to optimize. At the same time, seven algorithms are selected from symmetric and asymmetric encryption algorithms to define the enterprise

  11. MKEM: a Multi-level Knowledge Emergence Model for mining undiscovered public knowledge

    Directory of Open Access Journals (Sweden)

    Song Min

    2010-04-01

    Full Text Available Abstract Background Since Swanson proposed the Undiscovered Public Knowledge (UPK model, there have been many approaches to uncover UPK by mining the biomedical literature. These earlier works, however, required substantial manual intervention to reduce the number of possible connections and are mainly applied to disease-effect relation. With the advancement in biomedical science, it has become imperative to extract and combine information from multiple disjoint researches, studies and articles to infer new hypotheses and expand knowledge. Methods We propose MKEM, a Multi-level Knowledge Emergence Model, to discover implicit relationships using Natural Language Processing techniques such as Link Grammar and Ontologies such as Unified Medical Language System (UMLS MetaMap. The contribution of MKEM is as follows: First, we propose a flexible knowledge emergence model to extract implicit relationships across different levels such as molecular level for gene and protein and Phenomic level for disease and treatment. Second, we employ MetaMap for tagging biological concepts. Third, we provide an empirical and systematic approach to discover novel relationships. Results We applied our system on 5000 abstracts downloaded from PubMed database. We performed the performance evaluation as a gold standard is not yet available. Our system performed with a good precision and recall and we generated 24 hypotheses. Conclusions Our experiments show that MKEM is a powerful tool to discover hidden relationships residing in extracted entities that were represented by our Substance-Effect-Process-Disease-Body Part (SEPDB model.

  12. A systematic fault tree analysis based on multi-level flow modeling

    International Nuclear Information System (INIS)

    Gofuku, Akio; Ohara, Ai

    2010-01-01

    The fault tree analysis (FTA) is widely applied for the safety evaluation of a large-scale and mission-critical system. Because the potential of the FTA, however, strongly depends on human skill of analyzers, problems are pointed out in (1) education and training, (2) unreliable quality, (3) necessity of expertise knowledge, and (4) update of FTA results after the reconstruction of a target system. To get rid of these problems, many techniques to systematize FTA activities by applying computer technologies have been proposed. However, these techniques only use structural information of a target system and do not use functional information that is one of important properties of an artifact. The principle of FTA is to trace comprehensively cause-effect relations from a top undesirable effect to anomaly causes. The tracing is similar to the causality estimation technique that the authors proposed to find plausible counter actions to prevent or to mitigate the undesirable behavior of plants based on the model by a functional modeling technique, Multilevel Flow Modeling (MFM). The authors have extended this systematic technique to construct a fault tree (FT). This paper presents an algorithm of systematic construction of FT based on MFM models and demonstrates the applicability of the extended technique by the FT construction result of a cooling plant of nitric acid. (author)

  13. Research on Fault Diagnosis of HTR-PM Based on Multilevel Flow Model

    International Nuclear Information System (INIS)

    Zhang Yong; Zhou Yangping

    2014-01-01

    In this paper, we focus on the application of Multilevel Flow Model (MFM) in the automatic real-time fault diagnosis of High Temperature Gas-cooled Reactor Pebble-bed Module (HTR-PM) accidents. In the MFM, the plant process is described abstractly in function level by mass, energy and information flows, which reveal the interaction between different components and capacitate the causal reasoning between functions according to the flow properties. Thus, in the abnormal status, a goal-function-component oriented fault diagnosis can be performed with the model at a very quick speed and abnormal alarms can be also precisely explained by the reasoning relationship of the model. By using MFM, a fault diagnosis model of HTR-PM plant is built, and the detailed process of fault diagnosis is also shown by the flowcharts. Due to lack of simulation data about HTR-PM, experiments are not conducted to evaluate the fault diagnosis performance, but analysis of algorithm feasibility and complexity shows that the diagnosis system will have a good ability to detect and diagnosis accidents timely. (author)

  14. Identifying the environmental factors that effect within canopy BVOC loss using a multilevel canopy model

    Science.gov (United States)

    Chan, W. S.; Fuentes, J. D.; Lerdau, M.

    2010-12-01

    This presentation will provide research findings to evaluate the hypothesis that the loss of biogenic volatile organic compound (BVOC) within plant canopies is dynamic and depends on factors such as plant canopy architecture (height and leaf area distribution), atmospheric turbulence, concentration of oxidants (OH, O3, NO3), and the reactivity of BVOC species. Results will be presented from a new one dimensional, multilevel canopy model that couples algorithms for canopy microclimate, leaf physiology, BVOC emission, turbulent transport, and atmospheric chemistry to investigate the relative importance of factors that impact BVOC loss within a forest canopy. Model sensitivity tests will be presented and discussed to identify factors driving canopy loss. Results show isoprene and monoterpene canopy losses as high as 9 and 18%, respectively, for tall canopies during the daytime. We hypothesize that canopy height and wind speed (i.e. canopy residence time) may be the most important in dictating within-canopy loss. This work will reduce the error in bottom-up flux estimates of BVOCs and ultimately improve parameterizations of BVOC sources in air quality models by accounting for within canopy processes.

  15. DESTINY: A Comprehensive Tool with 3D and Multi-Level Cell Memory Modeling Capability

    Directory of Open Access Journals (Sweden)

    Sparsh Mittal

    2017-09-01

    Full Text Available To enable the design of large capacity memory structures, novel memory technologies such as non-volatile memory (NVM and novel fabrication approaches, e.g., 3D stacking and multi-level cell (MLC design have been explored. The existing modeling tools, however, cover only a few memory technologies, technology nodes and fabrication approaches. We present DESTINY, a tool for modeling 2D/3D memories designed using SRAM, resistive RAM (ReRAM, spin transfer torque RAM (STT-RAM, phase change RAM (PCM and embedded DRAM (eDRAM and 2D memories designed using spin orbit torque RAM (SOT-RAM, domain wall memory (DWM and Flash memory. In addition to single-level cell (SLC designs for all of these memories, DESTINY also supports modeling MLC designs for NVMs. We have extensively validated DESTINY against commercial and research prototypes of these memories. DESTINY is very useful for performing design-space exploration across several dimensions, such as optimizing for a target (e.g., latency, area or energy-delay product for a given memory technology, choosing the suitable memory technology or fabrication method (i.e., 2D v/s 3D for a given optimization target, etc. We believe that DESTINY will boost studies of next-generation memory architectures used in systems ranging from mobile devices to extreme-scale supercomputers. The latest source-code of DESTINY is available from the following git repository: https://bitbucket.org/sparshmittal/destinyv2.

  16. Raetrad model extensions for radon entry into multi-level buildings with basements or crawl spaces.

    Science.gov (United States)

    Nielson, K K; Rogers, V C; Rogers, V; Holt, R B

    1997-10-01

    The RAETRAD model was generalized to characterize radon generation and movement from soils and building materials into multi-level buildings with basements or crawl spaces. With the generalization, the model retains its original simplicity and ease of use. The model calculates radon entry rates that are consistent with measurements published for basement test structures at Colorado State University, confirming approximately equal contributions from diffusion and pressure-driven air flow at indoor-outdoor air pressure differences of deltaP(i-o) = -3.5 Pa. About one-fourth of the diffusive radon entry comes from concrete slabs and three-fourths comes from the surrounding soils. Calculated radon entry rates with and without a barrier over floor-wall shrinkage cracks generally agree with Colorado State University measurements when a sustained pressure of deltaP(i-o) = -2 Pa is used to represent calm wind (<1 m s(-1)) conditions. Calculated radon distributions in a 2-level house also are consistent with published measurements and equations.

  17. Multilevel Hierarchical Modeling of Benthic Macroinvertebrate Responses to Urbanization in Nine Metropolitan Regions across the Conterminous United States

    Science.gov (United States)

    Kashuba, Roxolana; Cha, YoonKyung; Alameddine, Ibrahim; Lee, Boknam; Cuffney, Thomas F.

    2010-01-01

    Multilevel hierarchical modeling methodology has been developed for use in ecological data analysis. The effect of urbanization on stream macroinvertebrate communities was measured across a gradient of basins in each of nine metropolitan regions across the conterminous United States. The hierarchical nature of this dataset was harnessed in a multi-tiered model structure, predicting both invertebrate response at the basin scale and differences in invertebrate response at the region scale. Ordination site scores, total taxa richness, Ephemeroptera, Plecoptera, Trichoptera (EPT) taxa richness, and richness-weighted mean tolerance of organisms at a site were used to describe invertebrate responses. Percentage of urban land cover was used as a basin-level predictor variable. Regional mean precipitation, air temperature, and antecedent agriculture were used as region-level predictor variables. Multilevel hierarchical models were fit to both levels of data simultaneously, borrowing statistical strength from the complete dataset to reduce uncertainty in regional coefficient estimates. Additionally, whereas non-hierarchical regressions were only able to show differing relations between invertebrate responses and urban intensity separately for each region, the multilevel hierarchical regressions were able to explain and quantify those differences within a single model. In this way, this modeling approach directly establishes the importance of antecedent agricultural conditions in masking the response of invertebrates to urbanization in metropolitan regions such as Milwaukee-Green Bay, Wisconsin; Denver, Colorado; and Dallas-Fort Worth, Texas. Also, these models show that regions with high precipitation, such as Atlanta, Georgia; Birmingham, Alabama; and Portland, Oregon, start out with better regional background conditions of invertebrates prior to urbanization but experience faster negative rates of change with urbanization. Ultimately, this urbanization

  18. Hazard Identification of the Offshore Three-phase Separation Process Based on Multilevel Flow Modeling and HAZOP

    DEFF Research Database (Denmark)

    Wu, Jing; Zhang, Laibin; Lind, Morten

    2013-01-01

    on function-oriented modeling, Multilevel Flow Modeling (MFM), is extended with function roles. A graphical MFM editor, which is combined with the reasoning capabilities of the MFM Workbench developed by DTU is applied to automate HAZOP studies. The method is proposed to support the “brain-storming” sessions...... is the first paper discussing and demonstrate the potential of the roles concept in MFM to supplement the integrity of HAZOP analysis....

  19. A method of Modelling and Simulating the Back-to-Back Modular Multilevel Converter HVDC Transmission System

    Science.gov (United States)

    Wang, Lei; Fan, Youping; Zhang, Dai; Ge, Mengxin; Zou, Xianbin; Li, Jingjiao

    2017-09-01

    This paper proposes a method to simulate a back-to-back modular multilevel converter (MMC) HVDC transmission system. In this paper we utilize an equivalent networks to simulate the dynamic power system. Moreover, to account for the performance of converter station, core components of model of the converter station gives a basic model of simulation. The proposed method is applied to an equivalent real power system.

  20. Using Multilevel Modeling to Assess Case-Mix Adjusters in Consumer Experience Surveys in Health Care

    NARCIS (Netherlands)

    Damman, Olga C.; Stubbe, Janine H.; Hendriks, Michelle; Arah, Onyebuchi A.; Spreeuwenberg, Peter; Delnoij, Diana M. J.; Groenewegen, Peter P.

    2009-01-01

    Background: Ratings on the quality of healthcare from the consumer's perspective need to be adjusted for consumer characteristics to ensure fair and accurate comparisons between healthcare providers or health plans. Although multilevel analysis is already considered an appropriate method for

  1. Linear spline multilevel models for summarising childhood growth trajectories: A guide to their application using examples from five birth cohorts.

    Science.gov (United States)

    Howe, Laura D; Tilling, Kate; Matijasevich, Alicia; Petherick, Emily S; Santos, Ana Cristina; Fairley, Lesley; Wright, John; Santos, Iná S; Barros, Aluísio Jd; Martin, Richard M; Kramer, Michael S; Bogdanovich, Natalia; Matush, Lidia; Barros, Henrique; Lawlor, Debbie A

    2016-10-01

    Childhood growth is of interest in medical research concerned with determinants and consequences of variation from healthy growth and development. Linear spline multilevel modelling is a useful approach for deriving individual summary measures of growth, which overcomes several data issues (co-linearity of repeat measures, the requirement for all individuals to be measured at the same ages and bias due to missing data). Here, we outline the application of this methodology to model individual trajectories of length/height and weight, drawing on examples from five cohorts from different generations and different geographical regions with varying levels of economic development. We describe the unique features of the data within each cohort that have implications for the application of linear spline multilevel models, for example, differences in the density and inter-individual variation in measurement occasions, and multiple sources of measurement with varying measurement error. After providing example Stata syntax and a suggested workflow for the implementation of linear spline multilevel models, we conclude with a discussion of the advantages and disadvantages of the linear spline approach compared with other growth modelling methods such as fractional polynomials, more complex spline functions and other non-linear models. © The Author(s) 2013.

  2. AN AUTOMATIC OPTICAL AND SAR IMAGE REGISTRATION METHOD USING ITERATIVE MULTI-LEVEL AND REFINEMENT MODEL

    Directory of Open Access Journals (Sweden)

    C. Xu

    2016-06-01

    Full Text Available Automatic image registration is a vital yet challenging task, particularly for multi-sensor remote sensing images. Given the diversity of the data, it is unlikely that a single registration algorithm or a single image feature will work satisfactorily for all applications. Focusing on this issue, the mainly contribution of this paper is to propose an automatic optical-to-SAR image registration method using –level and refinement model: Firstly, a multi-level strategy of coarse-to-fine registration is presented, the visual saliency features is used to acquire coarse registration, and then specific area and line features are used to refine the registration result, after that, sub-pixel matching is applied using KNN Graph. Secondly, an iterative strategy that involves adaptive parameter adjustment for re-extracting and re-matching features is presented. Considering the fact that almost all feature-based registration methods rely on feature extraction results, the iterative strategy improve the robustness of feature matching. And all parameters can be automatically and adaptively adjusted in the iterative procedure. Thirdly, a uniform level set segmentation model for optical and SAR images is presented to segment conjugate features, and Voronoi diagram is introduced into Spectral Point Matching (VSPM to further enhance the matching accuracy between two sets of matching points. Experimental results show that the proposed method can effectively and robustly generate sufficient, reliable point pairs and provide accurate registration.

  3. Contextual and individual determinants of periodontal disease: Multilevel analysis based on Andersen's model.

    Science.gov (United States)

    Valente, Maria I B; Vettore, Mario V

    2018-04-01

    To investigate the relationship of contextual and individual factors with periodontal disease in dentate adults and older people using the Andersen's behavioural model. Secondary individual data from 6011 adults and 2369 older people from the Brazilian Oral Health Survey (2010) were combined with contextual data for 27 cities. Attachment loss (AL) categories for each sextant were coded and summed to obtain the periodontal disease measure. The association of predisposing, enabling and need characteristics at city and individual level with periodontal disease was assessed using an adapted version of the Andersen's behavioural model. Multilevel Poisson regression was used to estimate rate ratios (RR) and 95% CIs. Periodontal disease was associated with contextual predisposing (RR 0.93; 95% CI = 0.87-0.99) and enabling factors (RR 0.99; 95% CI = 0.98-0.99) in adults. Contextual predisposing was also associated with periodontal disease in older people (RR 0.82; 95% CI = 0.73-0.92). Individual predisposing (age, sex and schooling) and need characteristics (perceived treatment need) were common predictors of periodontal disease in adults and older people. Periodontal disease was also associated with behaviours in the latter age group. Contextual predisposing factors and individual characteristics influenced periodontal disease experience in adults and older people. Contextual enabling factors were also meaningful determinants of periodontal disease in the former age group. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  4. Keep Calm and Learn Multilevel Logistic Modeling: A Simplified Three-Step Procedure Using Stata, R, Mplus, and SPSS

    Directory of Open Access Journals (Sweden)

    Nicolas Sommet

    2017-09-01

    Full Text Available This paper aims to introduce multilevel logistic regression analysis in a simple and practical way. First, we introduce the basic principles of logistic regression analysis (conditional probability, logit transformation, odds ratio. Second, we discuss the two fundamental implications of running this kind of analysis with a nested data structure: In multilevel logistic regression, the odds that the outcome variable equals one (rather than zero may vary from one cluster to another (i.e. the intercept may vary and the effect of a lower-level variable may also vary from one cluster to another (i.e. the slope may vary. Third and finally, we provide a simplified three-step “turnkey” procedure for multilevel logistic regression modeling: -Preliminary phase: Cluster- or grand-mean centering variables -Step #1: Running an empty model and calculating the intraclass correlation coefficient (ICC -Step #2: Running a constrained and an augmented intermediate model and performing a likelihood ratio test to determine whether considering the cluster-based variation of the effect of the lower-level variable improves the model fit -Step #3 Running a final model and interpreting the odds ratio and confidence intervals to determine whether data support your hypothesis Command syntax for Stata, R, Mplus, and SPSS are included. These steps will be applied to a study on Justin Bieber, because everybody likes Justin Bieber.1

  5. An exploration of multilevel modeling for estimating access to drinking-water and sanitation.

    Science.gov (United States)

    Wolf, Jennyfer; Bonjour, Sophie; Prüss-Ustün, Annette

    2013-03-01

    Monitoring progress towards the targets for access to safe drinking-water and sanitation under the Millennium Development Goals (MDG) requires reliable estimates and indicators. We analyzed trends and reviewed current indicators used for those targets. We developed continuous time series for 1990 to 2015 for access to improved drinking-water sources and improved sanitation facilities by country using multilevel modeling (MLM). We show that MLM is a reliable and transparent tool with many advantages over alternative approaches to estimate access to facilities. Using current indicators, the MDG target for water would be met, but the target for sanitation missed considerably. The number of people without access to such services is still increasing in certain regions. Striking differences persist between urban and rural areas. Consideration of water quality and different classification of shared sanitation facilities would, however, alter estimates considerably. To achieve improved monitoring we propose: (1) considering the use of MLM as an alternative for estimating access to safe drinking-water and sanitation; (2) completing regular assessments of water quality and supporting the development of national regulatory frameworks as part of capacity development; (3) evaluating health impacts of shared sanitation; (4) using a more equitable presentation of countries' performances in providing improved services.

  6. Policy implications of achievement testing using multilevel models: The case of Brazilian elementary schools

    Directory of Open Access Journals (Sweden)

    Igor Gomes Menezes

    2016-11-01

    Full Text Available Large-scale educational assessment has been established as source of descriptive, evaluative and interpretative information that influence educational policies worldwide throughout the last third of the 20th century. In the 1990s the Brazilian Ministry of Education developed the National Basic Education Assessment System (SAEB that regularly measures management, resource and contextual school features and academic achievement in public and private institutions. In 2005, after significant piloting and review of the SAEB, a new sampling strategy was taken and Prova Brasil became the new instrument used by the Ministry to assess skills in Portuguese (reading comprehension and Mathematics (problem solving, as well as collecting contextual information concerning the school, principal, teacher, and the students. This study aims to identify which variables are predictors of academic achievement of fifth grade students on Prova Brasil. Across a large sample of students, multilevel models tested a large number of variables relevant to student achievement. This approach uncovered critical variables not commonly seen as significant in light of other achievement determinants, including student habits, teacher ethnicity, and school technological resources. As such, this approach demonstrates the value of MLM to appropriately nuanced educational policies that reflect critical influences on student achievement. Its implications for wider application for psychology studies that may have relevant impacts for policy are also discussed.

  7. Sequence analysis in multilevel models. A study on different sources of patient cues in medical consultations.

    Science.gov (United States)

    Del Piccolo, Lidia; Mazzi, Maria Angela; Dunn, Graham; Sandri, Marco; Zimmermann, Christa

    2007-12-01

    The aims of the study were to explore the importance of macro (patient, physician, consultation) and micro (doctor-patient speech sequences) variables in promoting patient cues (unsolicited new information or expressions of feelings), and to describe the methodological implications related to the study of speech sequences. Patient characteristics, a consultation index of partnership and doctor-patient speech sequences were recorded for 246 primary care consultations in six primary care surgeries in Verona, Italy. Homogeneity and stationarity conditions of speech sequences allowed the creation of a hierarchy of multilevel logit models including micro and macro level variables, with the presence/absence of cues as the dependent variable. We found that emotional distress of the patient increased cues and that cues appeared among other patient expressions and were preceded by physicians' facilitations and handling of emotion. Partnership, in terms of open-ended inquiry, active listening skills and handling of emotion by the physician and active participation by the patient throughout the consultation, reduced cue frequency.

  8. A multilevel latent growth modelling of the longitudinal changes in motivation regulations in physical education.

    Science.gov (United States)

    Jaakkola, Timo; Wang, John; Yli-Piipari, Sami; Liukkonen, Jarmo

    2015-03-01

    The purpose of this study was to examine individual- and classroom-level differences in the longitudinal change in motivational regulations during physical education students' transition from elementary (Grade 6) across middle school (Grades 7 to 9). A sample of 757 Finnish adolescents (M = 12.71, SD = 0.23) participated in this study. Participants of the study responded to questionnaires collected six times. A multilevel latent growth modelling approach was used to analyze the data. Results showed that motivational regulations in physical education developed at different rates during middle school. More specifically, students': (a) identified regulation increased across Grades 6 to 9; (b) amotivation increased during middle school transition from Grade 6 to 7; and (c) introjected regulation declined from Grade 8 to 9. Other motivational regulations remained stable across time. The changes in amotivation and introjected regulation were largely due to individual factors, whereas the changes in identified regulation were due to environmental factors. Key pointsStudents' identified regulation increased across Grades 6 to 9.Students' amotivation increased across middle school transition from Grade 6 to 7.Students' introjected regulation declined from Grade 8 to 9.Other motivational regulations remained stable across time.

  9. On multilevel RBF collocation to solve nonlinear PDEs arising from endogenous stochastic volatility models

    Science.gov (United States)

    Bastani, Ali Foroush; Dastgerdi, Maryam Vahid; Mighani, Abolfazl

    2018-06-01

    The main aim of this paper is the analytical and numerical study of a time-dependent second-order nonlinear partial differential equation (PDE) arising from the endogenous stochastic volatility model, introduced in [Bensoussan, A., Crouhy, M. and Galai, D., Stochastic equity volatility related to the leverage effect (I): equity volatility behavior. Applied Mathematical Finance, 1, 63-85, 1994]. As the first step, we derive a consistent set of initial and boundary conditions to complement the PDE, when the firm is financed by equity and debt. In the sequel, we propose a Newton-based iteration scheme for nonlinear parabolic PDEs which is an extension of a method for solving elliptic partial differential equations introduced in [Fasshauer, G. E., Newton iteration with multiquadrics for the solution of nonlinear PDEs. Computers and Mathematics with Applications, 43, 423-438, 2002]. The scheme is based on multilevel collocation using radial basis functions (RBFs) to solve the resulting locally linearized elliptic PDEs obtained at each level of the Newton iteration. We show the effectiveness of the resulting framework by solving a prototypical example from the field and compare the results with those obtained from three different techniques: (1) a finite difference discretization; (2) a naive RBF collocation and (3) a benchmark approximation, introduced for the first time in this paper. The numerical results confirm the robustness, higher convergence rate and good stability properties of the proposed scheme compared to other alternatives. We also comment on some possible research directions in this field.

  10. Examining School-Based Bullying Interventions Using Multilevel Discrete Time Hazard Modeling

    Science.gov (United States)

    Wagaman, M. Alex; Geiger, Jennifer Mullins; Bermudez-Parsai, Monica; Hedberg, E. C.

    2014-01-01

    Although schools have been trying to address bulling by utilizing different approaches that stop or reduce the incidence of bullying, little remains known about what specific intervention strategies are most successful in reducing bullying in the school setting. Using the social-ecological framework, this paper examines school-based disciplinary interventions often used to deliver consequences to deter the reoccurrence of bullying and aggressive behaviors among school-aged children. Data for this study are drawn from the School-Wide Information System (SWIS) with the final analytic sample consisting of 1,221 students in grades K – 12 who received an office disciplinary referral for bullying during the first semester. Using Kaplan-Meier Failure Functions and Multi-level discrete time hazard models, determinants of the probability of a student receiving a second referral over time were examined. Of the seven interventions tested, only Parent-Teacher Conference (AOR=0.65, pbullying and aggressive behaviors. By using a social-ecological framework, schools can develop strategies that deter the reoccurrence of bullying by identifying key factors that enhance a sense of connection between the students’ mesosystems as well as utilizing disciplinary strategies that take into consideration student’s microsystem roles. PMID:22878779

  11. Impact of community capacity on the health status of residents: understanding with the contextual multilevel model.

    Science.gov (United States)

    Jung, Minsoo; Choi, Mankyu

    2013-01-01

    There has been little conceptual understanding as to how community capacity works, although it allows for an important, population-based health promotional strategy. In this study, the mechanism of community capacity was studied through literature reviews to suggest a comprehensive conceptual model. The research results found that the key to community capacity prevailed in how actively the capacities of individuals and their communities are able to interact with one another. Under active interactions, community-based organizations, which are a type of voluntary association, were created within the community, and cohesion among residents was enhanced. In addition, people were more willing to address community issues. During the process, many services were initiated to meet the people's health needs and strengthen their social and psychological ties. The characteristics of community capacity were named as the contextual multilevel effects. Because an increase in community capacity contributes to a boosted health status, encourages health behaviors, and eventually leads to the overall prosperity of the community, more public health-related attention is required.

  12. Empirical valence bond models for reactive potential energy surfaces: a parallel multilevel genetic program approach.

    Science.gov (United States)

    Bellucci, Michael A; Coker, David F

    2011-07-28

    We describe a new method for constructing empirical valence bond potential energy surfaces using a parallel multilevel genetic program (PMLGP). Genetic programs can be used to perform an efficient search through function space and parameter space to find the best functions and sets of parameters that fit energies obtained by ab initio electronic structure calculations. Building on the traditional genetic program approach, the PMLGP utilizes a hierarchy of genetic programming on two different levels. The lower level genetic programs are used to optimize coevolving populations in parallel while the higher level genetic program (HLGP) is used to optimize the genetic operator probabilities of the lower level genetic programs. The HLGP allows the algorithm to dynamically learn the mutation or combination of mutations that most effectively increase the fitness of the populations, causing a significant increase in the algorithm's accuracy and efficiency. The algorithm's accuracy and efficiency is tested against a standard parallel genetic program with a variety of one-dimensional test cases. Subsequently, the PMLGP is utilized to obtain an accurate empirical valence bond model for proton transfer in 3-hydroxy-gamma-pyrone in gas phase and protic solvent. © 2011 American Institute of Physics

  13. Multilevel linear modelling of the response-contingent learning of young children with significant developmental delays.

    Science.gov (United States)

    Raab, Melinda; Dunst, Carl J; Hamby, Deborah W

    2018-02-27

    The purpose of the study was to isolate the sources of variations in the rates of response-contingent learning among young children with multiple disabilities and significant developmental delays randomly assigned to contrasting types of early childhood intervention. Multilevel, hierarchical linear growth curve modelling was used to analyze four different measures of child response-contingent learning where repeated child learning measures were nested within individual children (Level-1), children were nested within practitioners (Level-2), and practitioners were nested within the contrasting types of intervention (Level-3). Findings showed that sources of variations in rates of child response-contingent learning were associated almost entirely with type of intervention after the variance associated with differences in practitioners nested within groups were accounted for. Rates of child learning were greater among children whose existing behaviour were used as the building blocks for promoting child competence (asset-based practices) compared to children for whom the focus of intervention was promoting child acquisition of missing skills (needs-based practices). The methods of analysis illustrate a practical approach to clustered data analysis and the presentation of results in ways that highlight sources of variations in the rates of response-contingent learning among young children with multiple developmental disabilities and significant developmental delays. Copyright © 2018 The Author(s). Published by Elsevier Ltd.. All rights reserved.

  14. Multilevel discretized random field models with 'spin' correlations for the simulation of environmental spatial data

    International Nuclear Information System (INIS)

    Žukovič, Milan; Hristopulos, Dionissios T

    2009-01-01

    A current problem of practical significance is how to analyze large, spatially distributed, environmental data sets. The problem is more challenging for variables that follow non-Gaussian distributions. We show by means of numerical simulations that the spatial correlations between variables can be captured by interactions between 'spins'. The spins represent multilevel discretizations of environmental variables with respect to a number of pre-defined thresholds. The spatial dependence between the 'spins' is imposed by means of short-range interactions. We present two approaches, inspired by the Ising and Potts models, that generate conditional simulations of spatially distributed variables from samples with missing data. Currently, the sampling and simulation points are assumed to be at the nodes of a regular grid. The conditional simulations of the 'spin system' are forced to respect locally the sample values and the system statistics globally. The second constraint is enforced by minimizing a cost function representing the deviation between normalized correlation energies of the simulated and the sample distributions. In the approach based on the N c -state Potts model, each point is assigned to one of N c classes. The interactions involve all the points simultaneously. In the Ising model approach, a sequential simulation scheme is used: the discretization at each simulation level is binomial (i.e., ± 1). Information propagates from lower to higher levels as the simulation proceeds. We compare the two approaches in terms of their ability to reproduce the target statistics (e.g., the histogram and the variogram of the sample distribution), to predict data at unsampled locations, as well as in terms of their computational complexity. The comparison is based on a non-Gaussian data set (derived from a digital elevation model of the Walker Lake area, Nevada, USA). We discuss the impact of relevant simulation parameters, such as the domain size, the number of

  15. Multilevel discretized random field models with 'spin' correlations for the simulation of environmental spatial data

    Science.gov (United States)

    Žukovič, Milan; Hristopulos, Dionissios T.

    2009-02-01

    A current problem of practical significance is how to analyze large, spatially distributed, environmental data sets. The problem is more challenging for variables that follow non-Gaussian distributions. We show by means of numerical simulations that the spatial correlations between variables can be captured by interactions between 'spins'. The spins represent multilevel discretizations of environmental variables with respect to a number of pre-defined thresholds. The spatial dependence between the 'spins' is imposed by means of short-range interactions. We present two approaches, inspired by the Ising and Potts models, that generate conditional simulations of spatially distributed variables from samples with missing data. Currently, the sampling and simulation points are assumed to be at the nodes of a regular grid. The conditional simulations of the 'spin system' are forced to respect locally the sample values and the system statistics globally. The second constraint is enforced by minimizing a cost function representing the deviation between normalized correlation energies of the simulated and the sample distributions. In the approach based on the Nc-state Potts model, each point is assigned to one of Nc classes. The interactions involve all the points simultaneously. In the Ising model approach, a sequential simulation scheme is used: the discretization at each simulation level is binomial (i.e., ± 1). Information propagates from lower to higher levels as the simulation proceeds. We compare the two approaches in terms of their ability to reproduce the target statistics (e.g., the histogram and the variogram of the sample distribution), to predict data at unsampled locations, as well as in terms of their computational complexity. The comparison is based on a non-Gaussian data set (derived from a digital elevation model of the Walker Lake area, Nevada, USA). We discuss the impact of relevant simulation parameters, such as the domain size, the number of

  16. Risk factors of chronic periodontitis on healing response: a multilevel modelling analysis.

    Science.gov (United States)

    Song, J; Zhao, H; Pan, C; Li, C; Liu, J; Pan, Y

    2017-09-15

    Chronic periodontitis is a multifactorial polygenetic disease with an increasing number of associated factors that have been identified over recent decades. Longitudinal epidemiologic studies have demonstrated that the risk factors were related to the progression of the disease. A traditional multivariate regression model was used to find risk factors associated with chronic periodontitis. However, the approach requirement of standard statistical procedures demands individual independence. Multilevel modelling (MLM) data analysis has widely been used in recent years, regarding thorough hierarchical structuring of the data, decomposing the error terms into different levels, and providing a new analytic method and framework for solving this problem. The purpose of our study is to investigate the relationship of clinical periodontal index and the risk factors in chronic periodontitis through MLM analysis and to identify high-risk individuals in the clinical setting. Fifty-four patients with moderate to severe periodontitis were included. They were treated by means of non-surgical periodontal therapy, and then made follow-up visits regularly at 3, 6, and 12 months after therapy. Each patient answered a questionnaire survey and underwent measurement of clinical periodontal parameters. Compared with baseline, probing depth (PD) and clinical attachment loss (CAL) improved significantly after non-surgical periodontal therapy with regular follow-up visits at 3, 6, and 12 months after therapy. The null model and variance component models with no independent variables included were initially obtained to investigate the variance of the PD and CAL reductions across all three levels, and they showed a statistically significant difference (P periodontal therapy with regular follow-up visits had a remarkable curative effect. All three levels had a substantial influence on the reduction of PD and CAL. Site-level had the largest effect on PD and CAL reductions.

  17. Multilevel latent class casemix modelling: a novel approach to accommodate patient casemix.

    Science.gov (United States)

    Gilthorpe, Mark S; Harrison, Wendy J; Downing, Amy; Forman, David; West, Robert M

    2011-03-01

    Using routinely collected patient data we explore the utility of multilevel latent class (MLLC) models to adjust for patient casemix and rank Trust performance. We contrast this with ranks derived from Trust standardised mortality ratios (SMRs). Patients with colorectal cancer diagnosed between 1998 and 2004 and resident in Northern and Yorkshire regions were identified from the cancer registry database (n = 24,640). Patient age, sex, stage-at-diagnosis (Dukes), and Trust of diagnosis/treatment were extracted. Socioeconomic background was derived using the Townsend Index. Outcome was survival at 3 years after diagnosis. MLLC-modelled and SMR-generated Trust ranks were compared. Patients were assigned to two classes of similar size: one with reasonable prognosis (63.0% died within 3 years), and one with better prognosis (39.3% died within 3 years). In patient class one, all patients diagnosed at stage B or C died within 3 years; in patient class two, all patients diagnosed at stage A, B or C survived. Trusts were assigned two classes with 51.3% and 53.2% of patients respectively dying within 3 years. Differences in the ranked Trust performance between the MLLC model and SMRs were all within estimated 95% CIs. A novel approach to casemix adjustment is illustrated, ranking Trust performance whilst facilitating the evaluation of factors associated with the patient journey (e.g. treatments) and factors associated with the processes of healthcare delivery (e.g. delays). Further research can demonstrate the value of modelling patient pathways and evaluating healthcare processes across provider institutions.

  18. Multilevel latent class casemix modelling: a novel approach to accommodate patient casemix

    Directory of Open Access Journals (Sweden)

    Forman David

    2011-03-01

    Full Text Available Abstract Background Using routinely collected patient data we explore the utility of multilevel latent class (MLLC models to adjust for patient casemix and rank Trust performance. We contrast this with ranks derived from Trust standardised mortality ratios (SMRs. Methods Patients with colorectal cancer diagnosed between 1998 and 2004 and resident in Northern and Yorkshire regions were identified from the cancer registry database (n = 24,640. Patient age, sex, stage-at-diagnosis (Dukes, and Trust of diagnosis/treatment were extracted. Socioeconomic background was derived using the Townsend Index. Outcome was survival at 3 years after diagnosis. MLLC-modelled and SMR-generated Trust ranks were compared. Results Patients were assigned to two classes of similar size: one with reasonable prognosis (63.0% died within 3 years, and one with better prognosis (39.3% died within 3 years. In patient class one, all patients diagnosed at stage B or C died within 3 years; in patient class two, all patients diagnosed at stage A, B or C survived. Trusts were assigned two classes with 51.3% and 53.2% of patients respectively dying within 3 years. Differences in the ranked Trust performance between the MLLC model and SMRs were all within estimated 95% CIs. Conclusions A novel approach to casemix adjustment is illustrated, ranking Trust performance whilst facilitating the evaluation of factors associated with the patient journey (e.g. treatments and factors associated with the processes of healthcare delivery (e.g. delays. Further research can demonstrate the value of modelling patient pathways and evaluating healthcare processes across provider institutions.

  19. A Solution to Modeling Multilevel Confirmatory Factor Analysis with Data Obtained from Complex Survey Sampling to Avoid Conflated Parameter Estimates

    Directory of Open Access Journals (Sweden)

    Jiun-Yu Wu

    2017-09-01

    Full Text Available The issue of equality in the between-and within-level structures in Multilevel Confirmatory Factor Analysis (MCFA models has been influential for obtaining unbiased parameter estimates and statistical inferences. A commonly seen condition is the inequality of factor loadings under equal level-varying structures. With mathematical investigation and Monte Carlo simulation, this study compared the robustness of five statistical models including two model-based (a true and a mis-specified models, one design-based, and two maximum models (two models where the full rank of variance-covariance matrix is estimated in between level and within level, respectively in analyzing complex survey measurement data with level-varying factor loadings. The empirical data of 120 3rd graders' (from 40 classrooms perceived Harter competence scale were modeled using MCFA and the parameter estimates were used as true parameters to perform the Monte Carlo simulation study. Results showed maximum models was robust to unequal factor loadings while the design-based and the miss-specified model-based approaches produced conflated results and spurious statistical inferences. We recommend the use of maximum models if researchers have limited information about the pattern of factor loadings and measurement structures. Measurement models are key components of Structural Equation Modeling (SEM; therefore, the findings can be generalized to multilevel SEM and CFA models. Mplus codes are provided for maximum models and other analytical models.

  20. The Impact of School Climate and School Identification on Academic Achievement: Multilevel Modeling with Student and Teacher Data

    OpenAIRE

    Maxwell, Sophie; Reynolds, Katherine J.; Lee, Eunro; Subasic, Emina; Bromhead, David

    2017-01-01

    School climate is a leading factor in explaining student learning and achievement. Less work has explored the impact of both staff and student perceptions of school climate raising interesting questions about whether staff school climate experiences can add “value” to students' achievement. In the current research, multiple sources were integrated into a multilevel model, including staff self-reports, student self-reports, objective school records of academic achievement, and socio-economic d...

  1. Modeling Learning in Doubly Multilevel Binary Longitudinal Data Using Generalized Linear Mixed Models: An Application to Measuring and Explaining Word Learning.

    Science.gov (United States)

    Cho, Sun-Joo; Goodwin, Amanda P

    2016-04-01

    When word learning is supported by instruction in experimental studies for adolescents, word knowledge outcomes tend to be collected from complex data structure, such as multiple aspects of word knowledge, multilevel reader data, multilevel item data, longitudinal design, and multiple groups. This study illustrates how generalized linear mixed models can be used to measure and explain word learning for data having such complexity. Results from this application provide deeper understanding of word knowledge than could be attained from simpler models and show that word knowledge is multidimensional and depends on word characteristics and instructional contexts.

  2. Transportation and socioeconomic impacts of bypasses on communities : an integrated synthesis of panel data, multilevel, and spatial econometric models with case studies.

    Science.gov (United States)

    2011-09-21

    Title: Transportation and Socioeconomic Impacts of Bypasses on Communities: An Integrated Synthesis of Panel Data, Multilevel, and Spatial Econometric Models with Case Studies. The title used at the start of this project was Transportation and Soc...

  3. Coupling Longitudinal Data and Multilevel Modeling to Examine the Antecedents and Consequences of Jealousy Experiences in Romantic Relationships: A Test of the Relational Turbulence Model

    Science.gov (United States)

    Theiss, Jennifer A.; Solomon, Denise Haunani

    2006-01-01

    We used longitudinal data and multilevel modeling to examine how intimacy, relational uncertainty, and failed attempts at interdependence influence emotional, cognitive, and communicative responses to romantic jealousy, and how those experiences shape subsequent relationship characteristics. The relational turbulence model (Solomon & Knobloch,…

  4. Use of multilevel modeling for determining optimal parameters of heat supply systems

    Science.gov (United States)

    Stennikov, V. A.; Barakhtenko, E. A.; Sokolov, D. V.

    2017-07-01

    The problem of finding optimal parameters of a heat-supply system (HSS) is in ensuring the required throughput capacity of a heat network by determining pipeline diameters and characteristics and location of pumping stations. Effective methods for solving this problem, i.e., the method of stepwise optimization based on the concept of dynamic programming and the method of multicircuit optimization, were proposed in the context of the hydraulic circuit theory developed at Melentiev Energy Systems Institute (Siberian Branch, Russian Academy of Sciences). These methods enable us to determine optimal parameters of various types of piping systems due to flexible adaptability of the calculation procedure to intricate nonlinear mathematical models describing features of used equipment items and methods of their construction and operation. The new and most significant results achieved in developing methodological support and software for finding optimal parameters of complex heat supply systems are presented: a new procedure for solving the problem based on multilevel decomposition of a heat network model that makes it possible to proceed from the initial problem to a set of interrelated, less cumbersome subproblems with reduced dimensionality; a new algorithm implementing the method of multicircuit optimization and focused on the calculation of a hierarchical model of a heat supply system; the SOSNA software system for determining optimum parameters of intricate heat-supply systems and implementing the developed methodological foundation. The proposed procedure and algorithm enable us to solve engineering problems of finding the optimal parameters of multicircuit heat supply systems having large (real) dimensionality, and are applied in solving urgent problems related to the optimal development and reconstruction of these systems. The developed methodological foundation and software can be used for designing heat supply systems in the Central and the Admiralty regions in

  5. Longitudinal associations between exercise identity and exercise motivation: A multilevel growth curve model approach.

    Science.gov (United States)

    Ntoumanis, N; Stenling, A; Thøgersen-Ntoumani, C; Vlachopoulos, S; Lindwall, M; Gucciardi, D F; Tsakonitis, C

    2018-02-01

    Past work linking exercise identity and exercise motivation has been cross-sectional. This is the first study to model the relations between different types of exercise identity and exercise motivation longitudinally. Understanding the dynamic associations between these sets of variables has implications for theory development and applied research. This was a longitudinal survey study. Participants were 180 exercisers (79 men, 101 women) from Greece, who were recruited from fitness centers and were asked to complete questionnaires assessing exercise identity (exercise beliefs and role-identity) and exercise motivation (intrinsic, identified, introjected, external motivation, and amotivation) three times within a 6 month period. Multilevel growth curve modeling examined the role of motivational regulations as within- and between-level predictors of exercise identity, and a model in which exercise identity predicted exercise motivation at the within- and between-person levels. Results showed that within-person changes in intrinsic motivation, introjected, and identified regulations were positively and reciprocally related to within-person changes in exercise beliefs; intrinsic motivation was also a positive predictor of within-person changes in role-identity but not vice versa. Between-person differences in the means of predictor variables were predictive of initial levels and average rates of change in the outcome variables. The findings show support to the proposition that a strong exercise identity (particularly exercise beliefs) can foster motivation for behaviors that reinforce this identity. We also demonstrate that such relations can be reciprocal overtime and can depend on the type of motivation in question as well as between-person differences in absolute levels of these variables. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  6. Multilevel corporate environmental responsibility.

    Science.gov (United States)

    Karassin, Orr; Bar-Haim, Aviad

    2016-12-01

    The multilevel empirical study of the antecedents of corporate social responsibility (CSR) has been identified as "the first knowledge gap" in CSR research. Based on an extensive literature review, the present study outlines a conceptual multilevel model of CSR, then designs and empirically validates an operational multilevel model of the principal driving factors affecting corporate environmental responsibility (CER), as a measure of CSR. Both conceptual and operational models incorporate three levels of analysis: institutional, organizational, and individual. The multilevel nature of the design allows for the assessment of the relative importance of the levels and of their components in the achievement of CER. Unweighted least squares (ULS) regression analysis reveals that the institutional-level variables have medium relationships with CER, some variables having a negative effect. The organizational level is revealed as having strong and positive significant relationships with CER, with organizational culture and managers' attitudes and behaviors as significant driving forces. The study demonstrates the importance of multilevel analysis in improving the understanding of CSR drivers, relative to single level models, even if the significance of specific drivers and levels may vary by context. Copyright © 2016 Elsevier Ltd. All rights reserved.

  7. Handbook of multilevel analysis

    National Research Council Canada - National Science Library

    Leeuw, Jan de; Meijer, Erik

    2008-01-01

    ... appropriate and efficient model-based methods have become available to deal with this issue, that we have come to appreciate the power that more complex models provide for describing the world and providing new insights. This book sets out to present some of the most recent developments in what has come to be known as multilevel modelling. An...

  8. Clarifying the use of aggregated exposures in multilevel models: self-included vs. self-excluded measures.

    Directory of Open Access Journals (Sweden)

    Etsuji Suzuki

    Full Text Available Multilevel analyses are ideally suited to assess the effects of ecological (higher level and individual (lower level exposure variables simultaneously. In applying such analyses to measures of ecologies in epidemiological studies, individual variables are usually aggregated into the higher level unit. Typically, the aggregated measure includes responses of every individual belonging to that group (i.e. it constitutes a self-included measure. More recently, researchers have developed an aggregate measure which excludes the response of the individual to whom the aggregate measure is linked (i.e. a self-excluded measure. In this study, we clarify the substantive and technical properties of these two measures when they are used as exposures in multilevel models.Although the differences between the two aggregated measures are mathematically subtle, distinguishing between them is important in terms of the specific scientific questions to be addressed. We then show how these measures can be used in two distinct types of multilevel models-self-included model and self-excluded model-and interpret the parameters in each model by imposing hypothetical interventions. The concept is tested on empirical data of workplace social capital and employees' systolic blood pressure.Researchers assume group-level interventions when using a self-included model, and individual-level interventions when using a self-excluded model. Analytical re-parameterizations of these two models highlight their differences in parameter interpretation. Cluster-mean centered self-included models enable researchers to decompose the collective effect into its within- and between-group components. The benefit of cluster-mean centering procedure is further discussed in terms of hypothetical interventions.When investigating the potential roles of aggregated variables, researchers should carefully explore which type of model-self-included or self-excluded-is suitable for a given situation

  9. ML-Space: Hybrid Spatial Gillespie and Particle Simulation of Multi-Level Rule-Based Models in Cell Biology.

    Science.gov (United States)

    Bittig, Arne T; Uhrmacher, Adelinde M

    2017-01-01

    Spatio-temporal dynamics of cellular processes can be simulated at different levels of detail, from (deterministic) partial differential equations via the spatial Stochastic Simulation algorithm to tracking Brownian trajectories of individual particles. We present a spatial simulation approach for multi-level rule-based models, which includes dynamically hierarchically nested cellular compartments and entities. Our approach ML-Space combines discrete compartmental dynamics, stochastic spatial approaches in discrete space, and particles moving in continuous space. The rule-based specification language of ML-Space supports concise and compact descriptions of models and to adapt the spatial resolution of models easily.

  10. Teacher-student interpersonal relationships do change and affect academic motivation: a multilevel growth curve modelling.

    Science.gov (United States)

    Maulana, Ridwan; Opdenakker, Marie-Christine; Bosker, Roel

    2014-09-01

    Research has shown that the teacher-student interpersonal relationship (TSIR) is important for student motivation. Although TSIR has received a growing interest, there are only few studies that focus on changes and links between TSIR and student academic motivation in a longitudinal fashion in non-Western contexts. This study investigated changes in TSIR and links with academic motivation as perceived by first-grade secondary school students in Indonesia. TSIR was studied from the perspective of interpersonal behaviour in terms of Influence and Proximity. Students' academic motivation was studied from the perspective of self-determination theory. A total of 504 first-grade secondary school students of 16 mathematics and English classes participated in the study. Surveys were administered in five waves throughout the school year. Multilevel growth curve modelling was applied. Contrary to the (limited) general research findings from Western contexts, we found that the quality of TSIR (student perceptions) increased over time. The increase was slightly more pronounced for Proximity than for Influence. In accordance with the findings for the Western countries, the level of students' controlled motivation increased, while that of autonomous motivation decreased over time. However, the negative change in autonomous motivation was less pronounced. As in Western countries, TSIR was longitudinally linked with academic motivation, in particular, with autonomous motivation. Evidence is found that TSIR can change in a favourable way, and this positively affects student motivation. Future research could benefit from unravelling the influences of cultures on changes in TSIR in broader contexts. © 2013 The British Psychological Society.

  11. Using multilevel modelling to assess case-mix adjusters in consumers experience surveys in health care

    NARCIS (Netherlands)

    Damman, O.C.; Stubbe, J.H.; Hendriks, M.; Arah, O.A.; Spreeuwenberg, P.; Delnoij, D.M.J.; Groenewegen, P.P.

    2009-01-01

    Background: Ratings on the quality of healthcare from the consumer’s perspective need to be adjusted for consumer characteristics to ensure fair and accurate comparisons between healthcare providers or health plans. Although multilevel analysis is already considered an appropriate method for

  12. Using multilevel modeling to assess case-mix adjusters in consumer experience surveys in health care.

    NARCIS (Netherlands)

    Damman, O.C.; Stubbe, J.H.; Hendriks, M.; Arah, O.A.; Spreeuwenberg, P.; Delnoij, D.M.J.; Groenewegen, P.P.

    2009-01-01

    Background: Ratings on the quality of healthcare from the consumer’s perspective need to be adjusted for consumer characteristics to ensure fair and accurate comparisons between healthcare providers or health plans. Although multilevel analysis is already considered an appropriate method for

  13. Commitment to the Study of International Business and Cultural Intelligence: A Multilevel Model

    Science.gov (United States)

    Ramsey, Jase R.; Barakat, Livia L.; Aad, Amine Abi

    2014-01-01

    Adopting a multilevel theoretical framework, we examined how metacognitive and motivational cultural intelligence influence an individual's commitment to the study of international business (IB). Data from 292 undergraduate and graduate business students nested in 12 U.S. business school classes demonstrated that individuals' metacognitive and…

  14. Incorporating Gender Specific Approaches for Incarcerated Female Adolescents: Multilevel Risk Model for Practice

    Science.gov (United States)

    Welch, Chiquitia L.; Roberts-Lewis, Amelia C.; Parker, Sharon

    2009-01-01

    The rise in female delinquency has resulted in large numbers of girls being incarcerated in Youth Development Centers (YDC). However, there are few gender specific treatment programs for incarcerated female adolescent offenders, particularly for those with a history of substance dependency. In this article, we present a Multi-level Risk Model…

  15. Modelling the multilevel structure and mixed effects of the factors influencing the energy consumption of electric vehicles

    International Nuclear Information System (INIS)

    Liu, Kai; Wang, Jiangbo; Yamamoto, Toshiyuki; Morikawa, Takayuki

    2016-01-01

    Highlights: • The impacts of driving heterogeneity on EVs’ energy efficiency are examined. • Several multilevel mixed-effects regression models are proposed and compared. • The most reasonable nested structure is extracted from the long term GPS data. • Proposed model improves the energy estimation accuracy by 7.5%. - Abstract: To improve the accuracy of estimation of the energy consumption of electric vehicles (EVs) and to enable the alleviation of range anxiety through the introduction of EV charging stations at suitable locations for the near future, multilevel mixed-effects linear regression models were used in this study to estimate the actual energy efficiency of EVs. The impacts of the heterogeneity in driving behaviour among various road environments and traffic conditions on EV energy efficiency were extracted from long-term daily trip-based energy consumption data, which were collected over 12 months from 68 in-use EVs in Aichi Prefecture in Japan. Considering the variations in energy efficiency associated with different types of EV ownership, different external environments, and different driving habits, a two-level random intercept model, three two-level mixed-effects models, and two three-level mixed-effects models were developed and compared. The most reasonable nesting structure was determined by comparing the models, which were designed with different nesting structures and different random variance component specifications, thereby revealing the potential correlations and non-constant variability of the energy consumption per kilometre (ECPK) and improving the estimation accuracy by 7.5%.

  16. The design of multi-core DSP parallel model based on message passing and multi-level pipeline

    Science.gov (United States)

    Niu, Jingyu; Hu, Jian; He, Wenjing; Meng, Fanrong; Li, Chuanrong

    2017-10-01

    Currently, the design of embedded signal processing system is often based on a specific application, but this idea is not conducive to the rapid development of signal processing technology. In this paper, a parallel processing model architecture based on multi-core DSP platform is designed, and it is mainly suitable for the complex algorithms which are composed of different modules. This model combines the ideas of multi-level pipeline parallelism and message passing, and summarizes the advantages of the mainstream model of multi-core DSP (the Master-Slave model and the Data Flow model), so that it has better performance. This paper uses three-dimensional image generation algorithm to validate the efficiency of the proposed model by comparing with the effectiveness of the Master-Slave and the Data Flow model.

  17. Multilevel models for multiple-baseline data: modeling across-participant variation in autocorrelation and residual variance.

    Science.gov (United States)

    Baek, Eun Kyeng; Ferron, John M

    2013-03-01

    Multilevel models (MLM) have been used as a method for analyzing multiple-baseline single-case data. However, some concerns can be raised because the models that have been used assume that the Level-1 error covariance matrix is the same for all participants. The purpose of this study was to extend the application of MLM of single-case data in order to accommodate across-participant variation in the Level-1 residual variance and autocorrelation. This more general model was then used in the analysis of single-case data sets to illustrate the method, to estimate the degree to which the autocorrelation and residual variances differed across participants, and to examine whether inferences about treatment effects were sensitive to whether or not the Level-1 error covariance matrix was allowed to vary across participants. The results from the analyses of five published studies showed that when the Level-1 error covariance matrix was allowed to vary across participants, some relatively large differences in autocorrelation estimates and error variance estimates emerged. The changes in modeling the variance structure did not change the conclusions about which fixed effects were statistically significant in most of the studies, but there was one exception. The fit indices did not consistently support selecting either the more complex covariance structure, which allowed the covariance parameters to vary across participants, or the simpler covariance structure. Given the uncertainty in model specification that may arise when modeling single-case data, researchers should consider conducting sensitivity analyses to examine the degree to which their conclusions are sensitive to modeling choices.

  18. Design of multilevel flow modelling-based decision support system by using multiagent platform

    DEFF Research Database (Denmark)

    Zhang, Xinxin; Lind, Morten; Ravn, Ole

    2015-01-01

    For complex engineering systems, there is an increasing demand forsafety and reliability. Decision support system (DSS) is designed to offersupervision and analysis about operational situations. A proper modelrepresentation is required for DSS to understand the process knowledge.Multilevel flow...... available techniques of MFM reasoning and less matureyet relevant MFM concepts are considered. It also offers an architecture designof task organisation for MFM software tools by using the concept of agent andtechnology of multiagent software system...

  19. The Master model on multi-actor and multilevel social responsibilities

    OpenAIRE

    Ashley, P.A.

    2011-01-01

    This working paper contributes to a collective discussion in a workshop occurring in January 2011 at the International Institute of Social Studies, bringing scholars from Europe and Brazil and aiming inter-university research collaboration on linking policies on social responsibility to development and equity. The paper serves as an introductory discussion for reframing the concept of corporate social responsibility into a broader umbrella concept of multi-actor and multilevel social responsi...

  20. Multi-level policies and adaptive social networks – a conceptual modeling study for maintaining a polycentric governance system

    Directory of Open Access Journals (Sweden)

    Jean-Denis Mathias

    2017-03-01

    Full Text Available Information and collaboration patterns embedded in social networks play key roles in multilevel and polycentric modes of governance. However, modeling the dynamics of such social networks in multilevel settings has been seldom addressed in the literature. Here we use an adaptive social network model to elaborate the interplay between a central and a local government in order to maintain a polycentric governance. More specifically, our analysis explores in what ways specific policy choices made by a central agent affect the features of an emerging social network composed of local organizations and local users. Using two types of stylized policies, adaptive co-management and adaptive one-level management, we focus on the benefits of multi-level adaptive cooperation for network management. Our analysis uses viability theory to explore and to quantify the ability of these policies to achieve specific network properties. Viability theory gives the family of policies that enables maintaining the polycentric governance unlike optimal control that gives a unique blueprint. We found that the viability of the policies can change dramatically depending on the goals and features of the social network. For some social networks, we also found a very large difference between the viability of the adaptive one-level management and adaptive co-management policies. However, results also show that adaptive co-management doesn’t always provide benefits. Hence, we argue that applying viability theory to governance networks can help policy design by analyzing the trade-off between the costs of adaptive co-management and the benefits associated with its ability to maintain desirable social network properties in a polycentric governance framework.

  1. The Relationship Among School Safety, School Liking, and Students' Self-Esteem: Based on a Multilevel Mediation Model.

    Science.gov (United States)

    Zhang, Xinghui; Xuan, Xin; Chen, Fumei; Zhang, Cai; Luo, Yuhan; Wang, Yun

    2016-03-01

    Perceptions of school safety have an important effect on students' development. Based on the model of "context-process-outcomes," we examined school safety as a context variable to explore how school safety at the school level affected students' self-esteem. We used hierarchical linear modeling to examine the link between school safety at the school level and students' self-esteem, including school liking as a mediator. The data were from the National Children's Study of China (NCSC), in which 6618 fourth- to fifth-grade students in 79 schools were recruited from 100 counties in 31 provinces in China. Multilevel mediation analyses showed that the positive relationship between school safety at the school level and self-esteem was partially mediated by school liking, controlling for demographics at both student and school levels. Furthermore, a sex difference existed in the multilevel mediation model. For boys, school liking fully mediated the relationship between school safety at the school level and self-esteem. However, school liking partially mediated the relationship between school safety at the school level and self-esteem among girls. School safety should receive increasing attention from policymakers because of its impact on students' self-esteem. © 2016, American School Health Association.

  2. The use of simple reparameterizations to improve the efficiency of Markov chain Monte Carlo estimation for multilevel models with applications to discrete time survival models.

    Science.gov (United States)

    Browne, William J; Steele, Fiona; Golalizadeh, Mousa; Green, Martin J

    2009-06-01

    We consider the application of Markov chain Monte Carlo (MCMC) estimation methods to random-effects models and in particular the family of discrete time survival models. Survival models can be used in many situations in the medical and social sciences and we illustrate their use through two examples that differ in terms of both substantive area and data structure. A multilevel discrete time survival analysis involves expanding the data set so that the model can be cast as a standard multilevel binary response model. For such models it has been shown that MCMC methods have advantages in terms of reducing estimate bias. However, the data expansion results in very large data sets for which MCMC estimation is often slow and can produce chains that exhibit poor mixing. Any way of improving the mixing will result in both speeding up the methods and more confidence in the estimates that are produced. The MCMC methodological literature is full of alternative algorithms designed to improve mixing of chains and we describe three reparameterization techniques that are easy to implement in available software. We consider two examples of multilevel survival analysis: incidence of mastitis in dairy cattle and contraceptive use dynamics in Indonesia. For each application we show where the reparameterization techniques can be used and assess their performance.

  3. Multilevel nonlinear mixed-effects models for the modeling of earlywood and latewood microfibril angle

    Science.gov (United States)

    Lewis Jordon; Richard F. Daniels; Alexander Clark; Rechun He

    2005-01-01

    Earlywood and latewood microfibril angle (MFA) was determined at I-millimeter intervals from disks at 1.4 meters, then at 3-meter intervals to a height of 13.7 meters, from 18 loblolly pine (Pinus taeda L.) trees grown in southeastern Texas. A modified three-parameter logistic function with mixed effects is used for modeling earlywood and latewood...

  4. The Effects of State Medicaid Expansion on Low-Income Individuals' Access to Health Care: Multilevel Modeling.

    Science.gov (United States)

    Choi, Sunha; Lee, Sungkyu; Matejkowski, Jason

    2018-06-01

    This study aimed to examine how states' Medicaid expansion affected insurance status and access to health care among low-income expansion state residents in 2015, the second year of the expansion. Data from the 2012 and 2015 Behavioral Risk Factor Surveillance System were linked to state-level data. A nationally representative sample of 544,307 adults (ages 26-64 years) from 50 states and Washington, DC were analyzed using multilevel modeling. The results indicate substantial increases in health care access between 2012 and 2015 among low-income adults in Medicaid expansion states. The final conditional multilevel models with low-income adults who had income at or below 138% of the poverty line indicate that, after controlling for individual- and state-level covariates, those who resided in the Medicaid expansion states were more likely to have health insurance (OR = 1.97, P income residents in non-expansion states in 2015. Moreover, the significant interaction terms indicate that adults living in non-expansion states with income below 100% of the poverty line are the most vulnerable compared with their counterparts in expansion states and with those with income between 100%-138% of the poverty line. This study demonstrates that state-level Medicaid expansion improved health care access among low-income US residents. However, residents with income below 100% of the poverty line in non-expansion states were disproportionately negatively affected by states' decision to not expand Medicaid coverage.

  5. Explaining Differences in Subjective Well-Being Across 33 Nations Using Multilevel Models: Universal Personality, Cultural Relativity, and National Income.

    Science.gov (United States)

    Cheng, Cecilia; Cheung, Mike W-L; Montasem, Alex

    2016-02-01

    This multinational study simultaneously tested three prominent hypotheses--universal disposition, cultural relativity, and livability--that explained differences in subjective well-being across nations. We performed multilevel structural equation modeling to examine the hypothesized relationships at both individual and cultural levels in 33 nations. Participants were 6,753 university students (2,215 men; 4,403 women; 135 did not specify), and the average age of the entire sample was 20.97 years (SD = 2.39). Both individual- and cultural-level analyses supported the universal disposition and cultural relativity hypotheses by revealing significant associations of subjective well-being with Extraversion, Neuroticism, and independent self-construal. In addition, interdependent self-construal was positively related to life satisfaction at the individual level only, whereas aggregated negative affect was positively linked with aggregate levels of Extraversion and interdependent self-construal at the cultural level only. Consistent with the livability hypothesis, gross national income (GNI) was related to aggregate levels of negative affect and life satisfaction. There was also a quadratic relationship between GNI and aggregated positive affect. Our findings reveal that universal disposition, cultural self-construal, and national income can elucidate differences in subjective well-being, but the multilevel analyses advance the literature by yielding new findings that cannot be identified in studies using individual-level analyses alone. © 2014 Wiley Periodicals, Inc.

  6. A 2 × 2 taxonomy of multilevel latent contextual models: accuracy-bias trade-offs in full and partial error correction models.

    Science.gov (United States)

    Lüdtke, Oliver; Marsh, Herbert W; Robitzsch, Alexander; Trautwein, Ulrich

    2011-12-01

    In multilevel modeling, group-level variables (L2) for assessing contextual effects are frequently generated by aggregating variables from a lower level (L1). A major problem of contextual analyses in the social sciences is that there is no error-free measurement of constructs. In the present article, 2 types of error occurring in multilevel data when estimating contextual effects are distinguished: unreliability that is due to measurement error and unreliability that is due to sampling error. The fact that studies may or may not correct for these 2 types of error can be translated into a 2 × 2 taxonomy of multilevel latent contextual models comprising 4 approaches: an uncorrected approach, partial correction approaches correcting for either measurement or sampling error (but not both), and a full correction approach that adjusts for both sources of error. It is shown mathematically and with simulated data that the uncorrected and partial correction approaches can result in substantially biased estimates of contextual effects, depending on the number of L1 individuals per group, the number of groups, the intraclass correlation, the number of indicators, and the size of the factor loadings. However, the simulation study also shows that partial correction approaches can outperform full correction approaches when the data provide only limited information in terms of the L2 construct (i.e., small number of groups, low intraclass correlation). A real-data application from educational psychology is used to illustrate the different approaches.

  7. Multilevel models in the explanation of the relationship between safety climate and safe behavior.

    Science.gov (United States)

    Cheyne, Alistair; Tomás, José M; Oliver, Amparo

    2013-01-01

    This study examines the relationships between components of organizational safety climate, including employee attitudes to organizational safety issues; perceptions of the physical working environment, and evaluations of worker engagement with safety issues; and relates these to self-reported levels of safety behavior. It attempts to explore the relationships between these variables in 1189 workers across 78 work groups in a large transportation organization. Evaluations of safety climate, the working environment and worker engagement, as well as safe behaviors, were collected using a self report questionnaire. The multilevel analysis showed that both levels of evaluation (the work group and the individual), and some cross-level interactions, were significant in explaining safe behaviors. Analyses revealed that a number of variables, at both levels, were associated with worker engagement and safe behaviors. The results suggest that, while individual evaluations of safety issues are important, there is also a role for the fostering of collective safety climates in encouraging safe behaviors and therefore reducing accidents.

  8. Comparing intergroup contact effects on blatant and subtle prejudice in adolescents: a multivariate multilevel model.

    Science.gov (United States)

    Herrero Olaizola, Juan; Rodríguez Díaz, Francisco Javier; Musitu Ochoa, Gonzalo

    2014-01-01

    The literature has rarely paid attention to the differential influence of intergroup contact on subtle and blatant prejudice. In this study, we hypothesized that the influence of intergroup contact on subtle prejudice will be smaller than its influence on blatant prejudice. This hypothesis was tested with data from a cross-sectional design on 1,655 school-aged native Spanish adolescents. Prejudice was measured with a shortened version of the Meertens and Pettigrew scale of blatant and subtle prejudice adapted to Spanish adolescent population. Results from multivariate multilevel analyses for correlated outcome variables supported the hypothesis. Students tended to score higher on the subtle prejudice scale; contact with the outgroup was statistically related both to levels of blatant and subtle prejudice; and, the negative relationship of contact with the outgroup and prejudice is greater for blatant prejudice as compared to subtle prejudice. Overall, results provide statistical evidence supporting the greater resistance to change of subtle forms of prejudice.

  9. Study of risk factors affecting both hypertension and obesity outcome by using multivariate multilevel logistic regression models

    Directory of Open Access Journals (Sweden)

    Sepedeh Gholizadeh

    2016-07-01

    Full Text Available Background:Obesity and hypertension are the most important non-communicable diseases thatin many studies, the prevalence and their risk factors have been performedin each geographic region univariately.Study of factors affecting both obesity and hypertension may have an important role which to be adrressed in this study. Materials &Methods:This cross-sectional study was conducted on 1000 men aged 20-70 living in Bushehr province. Blood pressure was measured three times and the average of them was considered as one of the response variables. Hypertension was defined as systolic blood pressure ≥140 (and-or diastolic blood pressure ≥90 and obesity was defined as body mass index ≥25. Data was analyzed by using multilevel, multivariate logistic regression model by MlwiNsoftware. Results:Intra class correlations in cluster level obtained 33% for high blood pressure and 37% for obesity, so two level model was fitted to data. The prevalence of obesity and hypertension obtained 43.6% (0.95%CI; 40.6-46.5, 29.4% (0.95%CI; 26.6-32.1 respectively. Age, gender, smoking, hyperlipidemia, diabetes, fruit and vegetable consumption and physical activity were the factors affecting blood pressure (p≤0.05. Age, gender, hyperlipidemia, diabetes, fruit and vegetable consumption, physical activity and place of residence are effective on obesity (p≤0.05. Conclusion: The multilevel models with considering levels distribution provide more precise estimates. As regards obesity and hypertension are the major risk factors for cardiovascular disease, by knowing the high-risk groups we can d careful planning to prevention of non-communicable diseases and promotion of society health.

  10. Small Convenience Stores and the Local Food Environment: An Analysis of Resident Shopping Behavior Using Multilevel Modeling.

    Science.gov (United States)

    Ruff, Ryan Richard; Akhund, Ali; Adjoian, Tamar

    2016-01-01

    Local food environments can influence the diet and health of individuals through food availability, proximity to retail stores, pricing, and promotion. This study focused on how small convenience stores, known in New York City as bodegas, influence resident shopping behavior and the food environment. Using a cross-sectional design, 171 bodegas and 2118 shoppers were sampled. Small convenience stores in New York City. Any bodega shopper aged 18+ who purchased food or beverage from a participating store. Data collection consisted of a store assessment, a health and behavior survey given to exiting customers, and a bag check that recorded product information for all customer purchases. Descriptive statistics were generated for bodega store characteristics, shopper demographics, and purchase behavior. Multilevel models were used to assess the influence of product availability, placement, and advertising on consumer purchases of sugar-sweetened beverages (SSBs), water, and fruits and vegetables. Seventy-one percent of participants reported shopping at bodegas five or more times per week, and 35% reported purchasing all or most of their monthly food allotment at bodegas. Model results indicated that lower amounts of available fresh produce were significantly and independently associated with a higher likelihood of SSB purchases. A second, stratified multilevel model showed that the likelihood of purchasing an SSB increased with decreasing varieties of produce when produce was located at the front of the store. No significant effects were found for water placement and beverage advertising. Small convenience stores in New York City are an easily accessible source of foods and beverages. Bodegas may be suitable for interventions designed to improve food choice and diet.

  11. Statistical Model and Performance Analysis of a Novel Multilevel Polarization Modulation in Local “Twisted” Fibers

    Directory of Open Access Journals (Sweden)

    Pierluigi Perrone

    2017-01-01

    Full Text Available Transmission demand continues to grow and higher capacity optical communication systems are required to economically meet this ever-increasing need for communication services. This article expands and deepens the study of a novel optical communication system for high-capacity Local Area Networks (LANs, based on twisted optical fibers. The complete statistical behavior of this system is shown, designed for more efficient use of the fiber single-channel capacity by adopting an unconventional multilevel polarization modulation (called “bands of polarization”. Starting from simulative results, a possible reference mathematical model is proposed. Finally, the system performance is analyzed in the presence of shot-noise (coherent detection or thermal noise (direct detection.

  12. The Impact of Mission Profile Models on the Predicted Lifetime of IGBT Modules in the Modular Multilevel Converter

    DEFF Research Database (Denmark)

    Zhang, Yi; Wang, Huai; Wang, Zhongxu

    2017-01-01

    and electrical power modeling methods on the estimated lifetime of IGBT modules in an MMC for offshore wind power application. In a 30 MW MMC case study, an annual wind speed profile with a resolution of 1 s/data, 10 minute/data, and 1 hour/data are considered, respectively. A method to re-generate higher......The reliability aspect study of Modular Multilevel Converter (MMC) is of great interest in industry applications, such as offshore wind. Lifetime prediction of key components is an important tool to design MMC with fulfilled reliability specifications. While many efforts have been made...... to the lifetime prediction of IGBT modules in renewable energy applications by considering long-term varying operation conditions (i.e., mission profile), the justifications of using the associated mission profiles are still missed. This paper investigates the impact of mission profile data resolutions...

  13. Development of an alarm analysis system based on multi-level flow models for nuclear power plant

    International Nuclear Information System (INIS)

    Zhang Jiande; Yang Ming; Zhang Zhijian

    2008-01-01

    An alarm analysis system based on Multi-level Flow Models (MFM) was developed for a PWR NPP. By automatically identifying the primary root causes in complex fault situations, the workload of the operators can be reduced. In addition, because MFM also provides a set of graphical symbols that implies causalities, operators can confirm diagnosis results by semiotic analysis, and hence the understandability of the process of alarm analysis as well as the reliability of maintenance task can be increased. 19 cases of simulation data from RELAP5/MOD2 code were utilized for evaluating the performance of the proposed system. The simulation results show that the proposed alarm analysis system has a good ability to detect and diagnose accidents earlier in time before reactor trip. (authors)

  14. EMPIRICAL STUDY OF DIFFERENT FACTORS EFFECTS ON ARTICLES PUBLICATION REGARDING SURVEY INTERVIEWER CHARACTERISTICS USING MULTILEVEL REGRESSION MODEL

    Directory of Open Access Journals (Sweden)

    Alina MOROŞANU

    2013-06-01

    Full Text Available The purpose of this research work is to evaluate the effects which some factors could have on articles publication regarding survey interviewer characteristics. For this, the author studied the existing literature from the various fields in which articles on survey interviewer characteristics has been published and which can be found in online articles database. The analysis was performed on 243 articles achieved by researchers in the time period 1949-2012. Using statistical software R and applying multilevel regression model, the results showed that the time period when the studied articles are made and the interaction between the number of authors and the number of pages affect the most their publication in journals with a certain level of impact factor.

  15. The effect of source herd and abattoir factors on pig carcass Salmonella contamination evaluated by multilevel modelling

    DEFF Research Database (Denmark)

    Baptista, Filipa Matos; Dahl, Jan; Nielsen, Liza Rosenbaum

    2010-01-01

    In Denmark, a Surveillance-and-Control Programme for Salmonella in pigs has been in place for several years. This study investigated factors associated with Salmonella pig carcass contamination, namely estimated daily number of Salmonella seropositive pigs delivered to slaughter, average Salmonella...... seroprevalence of the source herds that delivered each of five pigs contributing to the pool, weekday, year, season and abattoir size. A total of 20128 pooled carcass swabs collected in 22 Danish abattoirs, from 2002 to 2008, were included in a multilevel logistic regression model. Study results indicate...... that the probability of Salmonella positive carcasses is mainly influenced by the Salmonella herd seroprevalence of the swabbed pigs, the number of seropositive pigs delivered to the abattoir on the same day and weekday. Further reduction in carcass pool Salmonella prevalence may require new or improved methods...

  16. The influence of socioeconomic status on women's preferences for modern contraceptive providers in Nigeria: a multilevel choice modeling

    Directory of Open Access Journals (Sweden)

    Aremu O

    2013-12-01

    Full Text Available Olatunde Aremu School of Health, Sport, and Bioscience, Health Studies Field, University of East London, London, United Kingdom Background: Contraceptives are one of the most cost effective public health interventions. An understanding of the factors influencing users' preferences for contraceptives sources, in addition to their preferred methods of contraception, is an important factor in increasing contraceptive uptake. This study investigates the effect of women’s contextual and individual socioeconomic positions on their preference for contraceptive sources among current users in Nigeria. Methods: A multilevel modeling analysis was conducted using the most recent 2008 Nigerian Demographic and Health Surveys data of women aged between 15 and 49 years old. The analysis included 1,834 ever married women from 888 communities across the 36 states of the federation, including the Federal Capital Territory of Abuja. Three outcome variables, private, public, and informal provisions of contraceptive sources, were considered in the modeling. Results: There was variability in women's preferences for providers across communities. The result shows that change in variance accounted for about 31% and 19% in the odds of women's preferences for both private and public providers across communities. Younger age and being from the richest households are strongly associated with preference for both private and public providers. Living in rural areas and economically deprived neighborhoods were the community level determinants of women's preferences. Conclusion: This study documents the independent association of contextual socioeconomic characteristics and individual level socioeconomic factors with women's preferences for contraceptive commodity providers in Nigeria. Initiatives that seek to improve modern contraceptive uptake should jointly consider users’ preferences for sources of these commodities in addition to their preference for contraceptive type

  17. Longitudinal Assessment of Intellectual Abilities of Children with Williams Syndrome: Multilevel Modeling of Performance on the Kaufman Brief Intelligence Test--Second Edition

    Science.gov (United States)

    Mervis, Carolyn B.; Kistler, Doris J.; John, Angela E.; Morris, Colleen A.

    2012-01-01

    Multilevel modeling was used to address the longitudinal stability of standard scores (SSs) measuring intellectual ability for children with Williams syndrome (WS). Participants were 40 children with genetically confirmed WS who completed the Kaufman Brief Intelligence Test--Second Edition (KBIT-2; A. S. Kaufman & N. L. Kaufman, 2004) 4-7…

  18. Longitudinal Multilevel Models of the Big Fish Little Pond Effect on Academic Self-Concept: Counterbalancing Contrast and Reflected Glory Effects in Hong Kong Schools.

    Science.gov (United States)

    Marsh, Herbert W.; Kong, Chit-Kwong; Hau, Kit-Tai

    Longitudinal multilevel path models (7,997 students, 44 high schools, 4 years) evaluated the effects of school-average achievement and perceived school status on academic self-concept in Hong Kong, a collectivist culture with a highly achievement-segregated high school system. Consistent with a priori predictions based on the big-fish-little-pond…

  19. Exploring the Association between Transformational Leadership and Teacher's Self-Efficacy in Greek Education System: A Multilevel SEM Model

    Science.gov (United States)

    Gkolia, Aikaterini; Koustelios, Athanasios; Belias, Dimitrios

    2018-01-01

    The main aim of this study is to examine the effect of principals' transformational leadership on teachers' self-efficacy across 77 different Greek elementary and secondary schools based on a centralized education system. For the investigation of the above effect multilevel Structural Equation Modelling analysis was conducted, recognizing the…

  20. Semi-Analysis for the Pseudo-Colloid Migration of Multi-member Decay Chains in the Fractured Porous Medium with the Flux Boundary

    International Nuclear Information System (INIS)

    Jeong, Mi Seon; Hwang, Yong Soo; Kang, Chul Hyung

    2010-01-01

    Far-field modeling of radionuclide transport is an important component of general safety assessment studies carried out within the framework of storage of high-level radioactive waste in underground repositories. After a canister failure, radionuclides are leached from the backfilling and penetrate the surrounding bedrock, the final barrier between pollutant and Man's environment. Migration by pure diffusion through a hard tock or clay barrier is a rather slow process. In Fractured porous media, all of the groundwater flow occur within the fractures because fractures have permeabilities of several orders of magnitude larger than those of the rock matrix, if the geological layers are fully saturated with water. So radionuclides dissolved in groundwater will be transported along a fracture with molecular diffusion from the fracture to the rock matrix. Molecular diffusion from the fractures into the porous matrix constitutes an attenuation mechanism that can be highly order to prepare for extreme cases, it is assumed that the pollutants arrive rapidly in a fractured zone where transport takes place at much higher velocities. The specific problem of radionuclide transport through a fractured medium has been tackled by many scientists.According to the electromagnetic interaction between the solute and the colloid, solutes are absorbed by the colloid, and then we are called the pseudo-colloid. The natural colloid can exist inside a fracture with a density of 105 particles per one liter of a liquid. When the radionuclide migrates through a fractured rock, solutes sorb on natural colloids as well as the stationary fracture wall solid surface. Due to natural colloids, whose particle size is larger than that of solutes, colloids can migrate faster than solutes. Therefore, these pseudo-colloids, which are the sorbed solute molecules on the natural colloids, can also migrate faster than the solute. Both the solute and the pseudocolloid are sorbed onto and desorbed from

  1. A Multi-Level Approach to Modeling Rapidly Growing Mega-Regions as a Coupled Human-Natural System

    Science.gov (United States)

    Koch, J. A.; Tang, W.; Meentemeyer, R. K.

    2013-12-01

    The FUTure Urban-Regional Environment Simulation (FUTURES) integrates information on nonstationary drivers of land change (per capita land area demand, site suitability, and spatial structure of conversion events) into spatial-temporal projections of changes in landscape patterns (Meentemeyer et al., 2013). One striking feature of FUTURES is its patch-growth algorithm that includes feedback effects of former development events across several temporal and spatial scales: cell-level transition events are aggregated into patches of land change and their further growth is based on empirically derived parameters controlling its size, shape, and dispersion. Here, we augment the FUTURES modeling framework by expanding its multilevel structure and its representation of human decision making. The new modeling framework is hierarchically organized as nested subsystems including the latest theory on telecouplings in coupled human-natural systems (Liu et al., 2013). Each subsystem represents a specific level of spatial scale and embraces agents that have decision making authority at a particular level. The subsystems are characterized with regard to their spatial representation and are connected via flows of information (e.g. regulations and policies) or material (e.g. population migration). To provide a modeling framework that is applicable to a wide range of settings and geographical regions and to keep it computationally manageable, we implement a 'zooming factor' that allows to enable or disable subsystems (and hence the represented processes), based on the extent of the study region. The implementation of the FUTURES modeling framework for a specific case study follows the observational modeling approach described in Grimm et al. (2005), starting from the analysis of empirical data in order to capture the processes relevant for specific scales and to allow a rigorous calibration and validation of the model application. In this paper, we give an introduction to the basic

  2. Settings for Physical Activity – Developing a Site-specific Physical Activity Behavior Model based on Multi-level Intervention Studies

    DEFF Research Database (Denmark)

    Troelsen, Jens; Klinker, Charlotte Demant; Breum, Lars

    Settings for Physical Activity – Developing a Site-specific Physical Activity Behavior Model based on Multi-level Intervention Studies Introduction: Ecological models of health behavior have potential as theoretical framework to comprehend the multiple levels of factors influencing physical...... to be taken into consideration. A theoretical implication of this finding is to develop a site-specific physical activity behavior model adding a layered structure to the ecological model representing the determinants related to the specific site. Support: This study was supported by TrygFonden, Realdania...... activity (PA). The potential is shown by the fact that there has been a dramatic increase in application of ecological models in research and practice. One proposed core principle is that an ecological model is most powerful if the model is behavior-specific. However, based on multi-level interventions...

  3. Examining Differences in Within- and Between-Person Simple Structures of an Engineering Qualification Test Using Multilevel MIMIC Structural Equation Modeling

    Directory of Open Access Journals (Sweden)

    Ioannis Tsaousis

    2018-02-01

    Full Text Available The current study sought to meet three aims: (a to understand the optimal factor structure of the Professional Engineering (ProfEng test, a measure aiming to assess competency in engineering, within a multilevel (nested perspective; (b to examine the psychometric measurement invariance of the ProfEng test across levels due to nesting and across gender at the person level, and, (c to examine the internal consistency of the engineering competency measure at both levels in the analysis. Data involved 1,696 individuals across 21 universities who took a national licensure test as part of the professional accreditation process to obtain a work permit and practice the engineering profession in the Kingdom of Saudi Arabia. Data were analyzed by use of Multilevel Structural Equation Modeling (MLSEM. Results indicated that a 2-factor model at both levels of analysis provided the best fit to the data. We also examined violation of measurement invariance across clusters (cluster bias. Results showed that all factor loadings were invariant across levels, suggesting the presence of strong measurement invariance. Last, invariance across gender was tested by use of the MIMIC multilevel model. Results pointed to the existence of significant differences between genders on levels of personal and professional skills with females having higher levels on personal skills and males on professional. Estimates of internal consistency reliability also varied markedly due to nesting. It is concluded that ignoring a multilevel structure is associated with errors and inaccuracies in the measurement of person abilities as both measurement wise and precision wise the multilevel model provides increased accuracy at each level in the analysis.

  4. Engineering-Geological Data Model - The First Step to Build National Polish Standard for Multilevel Information Management

    Science.gov (United States)

    Ryżyński, Grzegorz; Nałęcz, Tomasz

    2016-10-01

    The efficient geological data management in Poland is necessary to support multilevel decision processes for government and local authorities in case of spatial planning, mineral resources and groundwater supply and the rational use of subsurface. Vast amount of geological information gathered in the digital archives and databases of Polish Geological Survey (PGS) is a basic resource for multi-scale national subsurface management. Data integration is the key factor to allow development of GIS and web tools for decision makers, however the main barrier for efficient geological information management is the heterogeneity of data in the resources of the Polish Geological Survey. Engineering-geological database is the first PGS thematic domain applied in the whole data integration plan. The solutions developed within this area will facilitate creation of procedures and standards for multilevel data management in PGS. Twenty years of experience in delivering digital engineering-geological mapping in 1:10 000 scale and archival geotechnical reports acquisition and digitisation allowed gathering of more than 300 thousands engineering-geological boreholes database as well as set of 10 thematic spatial layers (including foundation conditions map, depth to the first groundwater level, bedrock level, geohazards). Historically, the desktop approach was the source form of the geological-engineering data storage, resulting in multiple non-correlated interbase datasets. The need for creation of domain data model emerged and an object-oriented modelling (UML) scheme has been developed. The aim of the aforementioned development was to merge all datasets in one centralised Oracle server and prepare the unified spatial data structure for efficient web presentation and applications development. The presented approach will be the milestone toward creation of the Polish national standard for engineering-geological information management. The paper presents the approach and methodology

  5. Full Random Coefficients Multilevel Modeling of the Relationship between Land Use and Trip Time on Weekdays and Weekends

    Directory of Open Access Journals (Sweden)

    Tae-Hyoung Tommy Gim

    2017-10-01

    Full Text Available Interests in weekend trips are increasing, but few have studied how they are affected by land use. In this study, we analyze the relationship between compact land use characteristics and trip time in Seoul, Korea by comparing two research models, each of which uses the weekday and weekend data of the same travelers. To secure sufficient numbers of subjects and groups, full random coefficients multilevel models define the trip as level one and the neighborhood as level two, and find that level-two land use characteristics account for less variation in trip time than level-one individual characteristics. At level one, weekday trip time is found to be reduced by the choice of the automobile as a travel mode, but not by its ownership per se. In addition, it becomes reduced if made by high income travelers and extended to travel to quality jobs. Among four land use characteristics at level two, population density, road connectivity, and subway availability are shown to be significant in the weekday model. Only subway availability has a positive relationship with trip time and this finding is consistent with the level-one result that the choice of automobile alternatives increases trip time. The other land use characteristic, land use balance, turns out to be a single significant land use variable in the weekend model, implying that it is concerned mainly with non-work, non-mandatory travel.

  6. A multilevel model for cardiovascular disease prevalence in the US and its application to micro area prevalence estimates

    Directory of Open Access Journals (Sweden)

    Congdon Peter

    2009-01-01

    Full Text Available Abstract Background Estimates of disease prevalence for small areas are increasingly required for the allocation of health funds according to local need. Both individual level and geographic risk factors are likely to be relevant to explaining prevalence variations, and in turn relevant to the procedure for small area prevalence estimation. Prevalence estimates are of particular importance for major chronic illnesses such as cardiovascular disease. Methods A multilevel prevalence model for cardiovascular outcomes is proposed that incorporates both survey information on patient risk factors and the effects of geographic location. The model is applied to derive micro area prevalence estimates, specifically estimates of cardiovascular disease for Zip Code Tabulation Areas in the USA. The model incorporates prevalence differentials by age, sex, ethnicity and educational attainment from the 2005 Behavioral Risk Factor Surveillance System survey. Influences of geographic context are modelled at both county and state level, with the county effects relating to poverty and urbanity. State level influences are modelled using a random effects approach that allows both for spatial correlation and spatial isolates. Results To assess the importance of geographic variables, three types of model are compared: a model with person level variables only; a model with geographic effects that do not interact with person attributes; and a full model, allowing for state level random effects that differ by ethnicity. There is clear evidence that geographic effects improve statistical fit. Conclusion Geographic variations in disease prevalence partly reflect the demographic composition of area populations. However, prevalence variations may also show distinct geographic 'contextual' effects. The present study demonstrates by formal modelling methods that improved explanation is obtained by allowing for distinct geographic effects (for counties and states and for

  7. Multilevel Empirical Bayes Modeling for Improved Estimation of Toxicant Formulations to Suppress Parasitic Sea Lamprey in the Upper Great Lakes

    Science.gov (United States)

    Hatfield, L.A.; Gutreuter, S.; Boogaard, M.A.; Carlin, B.P.

    2011-01-01

    Estimation of extreme quantal-response statistics, such as the concentration required to kill 99.9% of test subjects (LC99.9), remains a challenge in the presence of multiple covariates and complex study designs. Accurate and precise estimates of the LC99.9 for mixtures of toxicants are critical to ongoing control of a parasitic invasive species, the sea lamprey, in the Laurentian Great Lakes of North America. The toxicity of those chemicals is affected by local and temporal variations in water chemistry, which must be incorporated into the modeling. We develop multilevel empirical Bayes models for data from multiple laboratory studies. Our approach yields more accurate and precise estimation of the LC99.9 compared to alternative models considered. This study demonstrates that properly incorporating hierarchical structure in laboratory data yields better estimates of LC99.9 stream treatment values that are critical to larvae control in the field. In addition, out-of-sample prediction of the results of in situ tests reveals the presence of a latent seasonal effect not manifest in the laboratory studies, suggesting avenues for future study and illustrating the importance of dual consideration of both experimental and observational data. ?? 2011, The International Biometric Society.

  8. Testing the effects of safety climate and disruptive children behavior on school bus drivers performance: A multilevel model.

    Science.gov (United States)

    Zohar, Dov; Lee, Jin

    2016-10-01

    The study was designed to test a multilevel path model whose variables exert opposing effects on school bus drivers' performance. Whereas departmental safety climate was expected to improve driving safety, the opposite was true for in-vehicle disruptive children behavior. The driving safety path in this model consists of increasing risk-taking practices starting with safety shortcuts leading to rule violations and to near-miss events. The study used a sample of 474 school bus drivers in rural areas, driving children to school and school-related activities. Newly developed scales for measuring predictor, mediator and outcome variables were validated with video data taken from inner and outer cameras, which were installed in 29 buses. Results partially supported the model by indicating that group-level safety climate and individual-level children distraction exerted opposite effects on the driving safety path. Furthermore, as hypothesized, children disruption moderated the strength of the safety rule violation-near miss relationship, resulting in greater strength under high disruptiveness. At the same time, the hypothesized interaction between the two predictor variables was not supported. Theoretical and practical implications for studying safety climate in general and distracted driving in particular for professional drivers are discussed. Copyright © 2016 Elsevier Ltd. All rights reserved.

  9. Fitting and Calibrating a Multilevel Mixed-Effects Stem Taper Model for Maritime Pine in NW Spain

    Science.gov (United States)

    Arias-Rodil, Manuel; Castedo-Dorado, Fernando; Cámara-Obregón, Asunción; Diéguez-Aranda, Ulises

    2015-01-01

    Stem taper data are usually hierarchical (several measurements per tree, and several trees per plot), making application of a multilevel mixed-effects modelling approach essential. However, correlation between trees in the same plot/stand has often been ignored in previous studies. Fitting and calibration of a variable-exponent stem taper function were conducted using data from 420 trees felled in even-aged maritime pine (Pinus pinaster Ait.) stands in NW Spain. In the fitting step, the tree level explained much more variability than the plot level, and therefore calibration at plot level was omitted. Several stem heights were evaluated for measurement of the additional diameter needed for calibration at tree level. Calibration with an additional diameter measured at between 40 and 60% of total tree height showed the greatest improvement in volume and diameter predictions. If additional diameter measurement is not available, the fixed-effects model fitted by the ordinary least squares technique should be used. Finally, we also evaluated how the expansion of parameters with random effects affects the stem taper prediction, as we consider this a key question when applying the mixed-effects modelling approach to taper equations. The results showed that correlation between random effects should be taken into account when assessing the influence of random effects in stem taper prediction. PMID:26630156

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

    Science.gov (United States)

    Konold, Timothy R; Cornell, Dewey

    2015-12-01

    This 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. Copyright © 2015 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

  11. Keep Calm and Learn Multilevel Logistic Modeling: A Simplified Three-Step Procedure Using Stata, R, Mplus, and SPSS

    OpenAIRE

    Nicolas Sommet; Davide Morselli

    2017-01-01

    This paper aims to introduce multilevel logistic regression analysis in a simple and practical way. First, we introduce the basic principles of logistic regression analysis (conditional probability, logit transformation, odds ratio). Second, we discuss the two fundamental implications of running this kind of analysis with a nested data structure: In multilevel logistic regression, the odds that the outcome variable equals one (rather than zero) may vary from one cluster to another (i.e. the i...

  12. Determinants of wind and solar energy system adoption by U.S. farms: A multilevel modeling approach

    International Nuclear Information System (INIS)

    Borchers, Allison M.; Xiarchos, Irene; Beckman, Jayson

    2014-01-01

    This article offers the first national examination of the determinants of adoption of wind and solar energy generation on U.S. farming operations. The inclusion of state policies and characteristics in a multilevel modeling approach distinguishes this study from past research utilizing logit models of technology adoption which focus only on the characteristics of the farm operation. Results suggest the propensity to adopt is higher for livestock operations, larger farms, operators with internet access, organic operations, and newer farmers. The results find state characteristics such as solar resources, per capita income levels, and predominantly democratic voting increasing the odds of farm adoption. This research suggests the relevance of state policy variables in explaining farm level outcomes is limited, although in combination best practice net metering and interconnection policies—policies designed to encourage the development of small scale distributed applications—are shown to increase the likelihood of farm solar and wind adoption. The prevalence of electric cooperatives—which are often not subject to state renewable energy policies and often service farms—is negatively related with the propensity to adopt and suggests that policy design may be a factor. - Highlights: • This is the first national examination of wind and solar energy adoption on U.S. farms. • Controlling for state policies distinguishes this study from past research of technology adoption. • We find net metering and interconnection policies increase the likelihood of farm adoption. • Results suggest that the design of renewable energy policies may limit their impact on farms

  13. Fast multilevel radiative transfer

    Science.gov (United States)

    Paletou, Frédéric; Léger, Ludovick

    2007-01-01

    The vast majority of recent advances in the field of numerical radiative transfer relies on approximate operator methods better known in astrophysics as Accelerated Lambda-Iteration (ALI). A superior class of iterative schemes, in term of rates of convergence, such as Gauss-Seidel and Successive Overrelaxation methods were therefore quite naturally introduced in the field of radiative transfer by Trujillo Bueno & Fabiani Bendicho (1995); it was thoroughly described for the non-LTE two-level atom case. We describe hereafter in details how such methods can be generalized when dealing with non-LTE unpolarised radiation transfer with multilevel atomic models, in monodimensional geometry.

  14. Scalable Adaptive Multilevel Solvers for Multiphysics Problems

    Energy Technology Data Exchange (ETDEWEB)

    Xu, Jinchao [Pennsylvania State Univ., University Park, PA (United States). Dept. of Mathematics

    2014-11-26

    In this project, we carried out many studies on adaptive and parallel multilevel methods for numerical modeling for various applications, including Magnetohydrodynamics (MHD) and complex fluids. We have made significant efforts and advances in adaptive multilevel methods of the multiphysics problems: multigrid methods, adaptive finite element methods, and applications.

  15. Multilevel Regression Models for Mean and (Co)variance: with Applications in Nursing Research

    OpenAIRE

    Li, Bayoue

    2014-01-01

    markdownabstract__Abstract__ In this chapter, a concise overview is provided for the statistical techniques that are applied in this thesis. This includes two classes of statistical modeling approaches which have been commonly applied in plenty of research areas for many decades. Namely, we will describe the fundamental ideas about mixed effects models and factor analytic (FA) models. To be specific, this chapter covers several types of these two classes of modeling approaches. For the mixed ...

  16. Multi-level hydrodynamic modelling of a scaled 10MW TLP wind turbine

    DEFF Research Database (Denmark)

    Pegalajar Jurado, Antonio Manuel; Bredmose, Henrik; Borg, Michael

    2016-01-01

    and focused waves is run in the three models, where only wave loads are considered. The simulation results are compared against the test data, and the numerical models are assessed based on their ability to reproduce the test results. Finally, the possibility of enhancing the simple model by using...

  17. [Multivariate and multilevel model analysis on factors that influencing the literacy of health among high school students in Guangdong province].

    Science.gov (United States)

    Ye, Xiao-hua; Xu, Ya; Zhou, Shu-dong; Gao, Yan-hui; Li, Yan-fen

    2011-09-01

    To analyze the awareness on health among high school students and its influencing factors in Guangdong. Multi-stage sampling and questionnaire "2009 health awareness survey of the Chinese citizens" developed by our Department of Health, were used. Data were analyzed by multivariate multilevel model under MLwinN 2.19 software. The mean scores on knowledge and ideas, behaviors and related skills among 1606 high school students of Guangdong province, were 69.08 ± 14.81, 60.05 ± 16.85 and 74.99 ± 21.17 respectively. Three items on health showed that they all related to each other and relations between grades (0.972, 0.715 and 0.855) were greater than the individuals (0.565, 0.426 and 0.438). Factors as students from outside the Pearl River Delta region or from the rural areas, being male, at general secondary schools, at grade one, with poor academic performance and more pocket money etc., had lower levels on those related information of health.

  18. How do leader-member exchange quality and differentiation affect performance in teams? An integrated multilevel dual process model.

    Science.gov (United States)

    Li, Alex Ning; Liao, Hui

    2014-09-01

    Integrating leader-member exchange (LMX) research with role engagement theory (Kahn, 1990) and role system theory (Katz & Kahn, 1978), we propose a multilevel, dual process model to understand the mechanisms through which LMX quality at the individual level and LMX differentiation at the team level simultaneously affect individual and team performance. With regard to LMX differentiation, we introduce a new configural approach focusing on the pattern of LMX differentiation to complement the traditional approach focusing on the degree of LMX differentiation. Results based on multiphase, multisource data from 375 employees of 82 teams revealed that, at the individual level, LMX quality positively contributed to customer-rated employee performance through enhancing employee role engagement. At the team level, LMX differentiation exerted negative influence on teams' financial performance through disrupting team coordination. In particular, teams with the bimodal form of LMX configuration (i.e., teams that split into 2 LMX-based subgroups with comparable size) suffered most in team performance because they experienced greatest difficulty in coordinating members' activities. Furthermore, LMX differentiation strengthened the relationship between LMX quality and role engagement, and team coordination strengthened the relationship between role engagement and employee performance. Theoretical and practical implications of the findings are discussed. PsycINFO Database Record (c) 2014 APA, all rights reserved.

  19. Comparative Analysis of Public Attitudes toward Nuclear Power Energy across 27 European Countries by Applying the Multilevel Model

    Directory of Open Access Journals (Sweden)

    Jaesun Wang

    2018-05-01

    Full Text Available Despite its potential risks, nuclear power energy offers some economic benefits including cheap electricity. This benefit clarifies part of the reason why people support nuclear energy. Our research examined whether there was a difference in the acceptance of nuclear energy across 27 European countries in 2009, before the Fukushima accident. In particular, we analyzed how each factor at the individual and contextual level influences the acceptance. To answer this question, we set up the acceptance of nuclear energy as a dependent variable, and 5 perception variables at the individual level and 11 structural ones at the contextual level as independent variables. We executed multilevel modeling by using a Eurobarometer survey, which covered 27 European countries. The analysis results showed that at the individual level, the perceived benefit explained the largest variance of the acceptance, followed by perceived risk and trust. At the contextual level, the share of the energy supply by nuclear power, environmentalism and ideology influenced the acceptance of nuclear energy. This study shows that individuals’ acceptance of nuclear energy is based on individual beliefs and perceptions, but it is also influenced by the institutional and socio-cultural context which each country faces.

  20. The Impact of School Climate and School Identification on Academic Achievement: Multilevel Modeling with Student and Teacher Data.

    Science.gov (United States)

    Maxwell, Sophie; Reynolds, Katherine J; Lee, Eunro; Subasic, Emina; Bromhead, David

    2017-01-01

    School climate is a leading factor in explaining student learning and achievement. Less work has explored the impact of both staff and student perceptions of school climate raising interesting questions about whether staff school climate experiences can add "value" to students' achievement. In the current research, multiple sources were integrated into a multilevel model, including staff self-reports, student self-reports, objective school records of academic achievement, and socio-economic demographics. Achievement was assessed using a national literacy and numeracy tests ( N = 760 staff and 2,257 students from 17 secondary schools). In addition, guided by the "social identity approach," school identification is investigated as a possible psychological mechanism to explain the relationship between school climate and achievement. In line with predictions, results show that students' perceptions of school climate significantly explain writing and numeracy achievement and this effect is mediated by students' psychological identification with the school. Furthermore, staff perceptions of school climate explain students' achievement on numeracy, writing and reading tests (while accounting for students' responses). However, staff's school identification did not play a significant role. Implications of these findings for organizational, social, and educational research are discussed.

  1. The Impact of School Climate and School Identification on Academic Achievement: Multilevel Modeling with Student and Teacher Data

    Directory of Open Access Journals (Sweden)

    Sophie Maxwell

    2017-12-01

    Full Text Available School climate is a leading factor in explaining student learning and achievement. Less work has explored the impact of both staff and student perceptions of school climate raising interesting questions about whether staff school climate experiences can add “value” to students' achievement. In the current research, multiple sources were integrated into a multilevel model, including staff self-reports, student self-reports, objective school records of academic achievement, and socio-economic demographics. Achievement was assessed using a national literacy and numeracy tests (N = 760 staff and 2,257 students from 17 secondary schools. In addition, guided by the “social identity approach,” school identification is investigated as a possible psychological mechanism to explain the relationship between school climate and achievement. In line with predictions, results show that students' perceptions of school climate significantly explain writing and numeracy achievement and this effect is mediated by students' psychological identification with the school. Furthermore, staff perceptions of school climate explain students' achievement on numeracy, writing and reading tests (while accounting for students' responses. However, staff's school identification did not play a significant role. Implications of these findings for organizational, social, and educational research are discussed.

  2. Analysing the relationship between family planning workers' contact and contraceptive switching in rural Bangladesh using multilevel modelling.

    Science.gov (United States)

    Hossain, Mian B

    2005-09-01

    With a population of over 131 million and a fertility rate of 29.9 per 1000, population growth constitutes a primary threat to continued economic growth and development in Bangladesh. One strategy that has been used to cease further increases in fertility in Bangladesh involves using family planning outreach workers who travel throughout rural and urban areas educating women regarding contraceptive alternatives. This study uses a longitudinal database to assess the impact of family planning outreach workers' contact upon contraceptive switching and upon the risk of an unintended pregnancy. Using longitudinal data on contraceptive use from the Operations Research Project (ORP) of the International Centre for Diarrhoeal Disease Research (ICDDR,B) in Bangladesh, multiple decrement life table analysis and multilevel, discrete-time competing risk hazards models were used to estimate the cumulative probabilities of switching to an alternative form of contraceptive use after a woman engaged in a discussion with an outreach worker. After controlling for the effects of socio-demographic and economic characteristics, the analysis revealed that family planning outreach workers' contact with women significantly decreases the risk of transitioning to the non-use of contraceptives. This contact also reduces the risk of an unintended pregnancy. Family planning workers' contact with women is associated with the increased risk of a woman switching from one modern method to another modern method. The study results indicate that side-effects and other method-related reasons are the two primary reasons for contraceptive discontinuation in rural Bangladesh.

  3. A multilevel structural equation modeling analysis of vulnerabilities and resilience resources influencing affective adaptation to chronic pain.

    Science.gov (United States)

    Sturgeon, John A; Zautra, Alex J; Arewasikporn, Anne

    2014-02-01

    The processes of individual adaptation to chronic pain are complex and occur across multiple domains. We examined the social, cognitive, and affective context of daily pain adaptation in individuals with fibromyalgia and osteoarthritis. By using a sample of 260 women with fibromyalgia or osteoarthritis, we examined the contributions of pain catastrophizing, negative interpersonal events, and positive interpersonal events to daily negative and positive affect across 30days of daily diary data. Individual differences and daily fluctuations in predictor variables were estimated simultaneously by utilizing multilevel structural equation modeling techniques. The relationships between pain and negative and positive affect were mediated by stable and day-to-day levels of pain catastrophizing as well as day-to-day positive interpersonal events, but not negative interpersonal events. There were significant and independent contributions of pain catastrophizing and positive interpersonal events to adaptation to pain and pain-related affective dysregulation. These effects occur both between persons and within a person's everyday life. Copyright © 2013 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.

  4. River modeling and multi-level fish health assessment to evaluate impacts from oil sands water releases (Part 2)

    International Nuclear Information System (INIS)

    Shaw, R.; Swanson, S.M.; Lagimodiere, M.; Gulley, J.

    1995-01-01

    A multi-level, multi-scale approach was used to assess potential impacts to fish health from oil sands water releases. The method used to arrive at predicted impacts involved assembling experimental data on the effects of chronic exposure to oil sands wastewaters on biochemical, physiological and whole-organism endpoint. This information was used to determine no effect levels (NOELs) and lowest effect levels (LOELs) for the suite of fish health parameters used in laboratory experiments (primarily biochemical and physiological measurement endpoints). LOELs and NOELs were compared to modeled concentrations of wastewater in the Athabasca River for five time snapshots. For each time period, concentrations were predicted based on mean annual flows and 7Q10 flows (low flows). This comparison was used to predict impacts on biochemical/physiological endpoints. Impacts on at the whole-organism and population-level were determined by comparing what the laboratory data would predict with what was observed in the field. This process was used to draw a conclusion regarding the health and sustainability of fish populations

  5. Nurses' practice environment and work-family conflict in relation to burn out: a multilevel modelling approach.

    Science.gov (United States)

    Leineweber, Constanze; Westerlund, Hugo; Chungkham, Holendro Singh; Lindqvist, Rikard; Runesdotter, Sara; Tishelman, Carol

    2014-01-01

    To investigate associations between nurse work practice environment measured at department level and individual level work-family conflict on burnout, measured as emotional exhaustion, depersonalization and personal accomplishment among Swedish RNs. A multilevel model was fit with the individual RN at the 1st, and the hospital department at the 2nd level using cross-sectional RN survey data from the Swedish part of RN4CAST, an EU 7th framework project. The data analysed here is based on a national sample of 8,620 RNs from 369 departments in 53 hospitals. Generally, RNs reported high values of personal accomplishment and lower values of emotional exhaustion and depersonalization. High work-family conflict increased the risk for emotional exhaustion, but for neither depersonalization nor personal accomplishment. On department level adequate staffing and good leadership and support for nurses reduced the risk for emotional exhaustion and depersonalization. Personal accomplishment was statistically significantly related to staff adequacy. The findings suggest that adequate staffing, good leadership, and support for nurses are crucial for RNs' mental health. Our findings also highlight the importance of hospital managers developing policies and practices to facilitate the successful combination of work with private life for employees.

  6. A multilevel simulation approach to derive the slip boundary condition of the solid phase in two-fluid models

    Science.gov (United States)

    Feng, Zhi-Gang; Michaelides, Efstathios; Mao, Shaolin

    2011-11-01

    The simulation of particulate flows for industrial applications often requires the use of a two-fluid model (TFM), where the solid particles are considered as a separate continuous phase. One of the underlining uncertainties in the use of aTFM in multiphase computations comes from the boundary condition of the solid phase. The no-slip condition at a solid boundary is not a valid assumption for the solid phase. Instead, several researchers advocate a slip condition as a more appropriate boundary condition. However, the question on the selection of an exact slip length or a slip velocity coefficient is still unanswered. In the present work we propose a multilevel simulation approach to compute the slip length that is applicable to a TFM. We investigate the motion of a number of particles near a vertical solid wall, while the particles are in fluidization using a direct numerical simulation (DNS); the positions and velocities of the particles are being tracked and analyzed at each time step. It is found that the time- and vertical-space averaged values of the particle velocities converge, yielding velocity profiles that can be used to deduce the particle slip length close to a solid wall. This work was supported by a grant from the DOE-NETL (DE-NT0008064) and by a grant from NSF (HRD-0932339).

  7. A multilevel simultaneous equations model for within-cluster dynamic effects, with an application to reciprocal parent–child and sibling effects

    OpenAIRE

    Fiona Steele; Jon Rasbash; Jennifer Jenkins

    2013-01-01

    There has been substantial interest in the social and health sciences in the reciprocal causal influences that people in close relationships have on one another. Most research has considered reciprocal processes involving only 2 units, although many social relationships of interest occur within a larger group (e.g., families, work groups, peer groups, classrooms). This article presents a general longitudinal multilevel modeling framework for the simultaneous estimation of reciprocal relations...

  8. A 3D multilevel model of damage and strength of wood: Analysis of microstructural effects

    DEFF Research Database (Denmark)

    Qing, Hai; Mishnaevsky, Leon

    2011-01-01

    A 3D hierarchical computational model of damage and strength of wood is developed. The model takes into account the four scale microstructures of wood, including the microfibril reinforced structure at nanoscale, multilayered cell walls at microscale, hexagon-shape-tube cellular structure...

  9. Evaluating multi-level models to test occupancy state responses of Plethodontid salamanders

    Science.gov (United States)

    Kroll, Andrew J.; Garcia, Tiffany S.; Jones, Jay E.; Dugger, Catherine; Murden, Blake; Johnson, Josh; Peerman, Summer; Brintz, Ben; Rochelle, Michael

    2015-01-01

    Plethodontid salamanders are diverse and widely distributed taxa and play critical roles in ecosystem processes. Due to salamander use of structurally complex habitats, and because only a portion of a population is available for sampling, evaluation of sampling designs and estimators is critical to provide strong inference about Plethodontid ecology and responses to conservation and management activities. We conducted a simulation study to evaluate the effectiveness of multi-scale and hierarchical single-scale occupancy models in the context of a Before-After Control-Impact (BACI) experimental design with multiple levels of sampling. Also, we fit the hierarchical single-scale model to empirical data collected for Oregon slender and Ensatina salamanders across two years on 66 forest stands in the Cascade Range, Oregon, USA. All models were fit within a Bayesian framework. Estimator precision in both models improved with increasing numbers of primary and secondary sampling units, underscoring the potential gains accrued when adding secondary sampling units. Both models showed evidence of estimator bias at low detection probabilities and low sample sizes; this problem was particularly acute for the multi-scale model. Our results suggested that sufficient sample sizes at both the primary and secondary sampling levels could ameliorate this issue. Empirical data indicated Oregon slender salamander occupancy was associated strongly with the amount of coarse woody debris (posterior mean = 0.74; SD = 0.24); Ensatina occupancy was not associated with amount of coarse woody debris (posterior mean = -0.01; SD = 0.29). Our simulation results indicate that either model is suitable for use in an experimental study of Plethodontid salamanders provided that sample sizes are sufficiently large. However, hierarchical single-scale and multi-scale models describe different processes and estimate different parameters. As a result, we recommend careful consideration of study questions

  10. Evaluating Multi-Level Models to Test Occupancy State Responses of Plethodontid Salamanders.

    Directory of Open Access Journals (Sweden)

    Andrew J Kroll

    Full Text Available Plethodontid salamanders are diverse and widely distributed taxa and play critical roles in ecosystem processes. Due to salamander use of structurally complex habitats, and because only a portion of a population is available for sampling, evaluation of sampling designs and estimators is critical to provide strong inference about Plethodontid ecology and responses to conservation and management activities. We conducted a simulation study to evaluate the effectiveness of multi-scale and hierarchical single-scale occupancy models in the context of a Before-After Control-Impact (BACI experimental design with multiple levels of sampling. Also, we fit the hierarchical single-scale model to empirical data collected for Oregon slender and Ensatina salamanders across two years on 66 forest stands in the Cascade Range, Oregon, USA. All models were fit within a Bayesian framework. Estimator precision in both models improved with increasing numbers of primary and secondary sampling units, underscoring the potential gains accrued when adding secondary sampling units. Both models showed evidence of estimator bias at low detection probabilities and low sample sizes; this problem was particularly acute for the multi-scale model. Our results suggested that sufficient sample sizes at both the primary and secondary sampling levels could ameliorate this issue. Empirical data indicated Oregon slender salamander occupancy was associated strongly with the amount of coarse woody debris (posterior mean = 0.74; SD = 0.24; Ensatina occupancy was not associated with amount of coarse woody debris (posterior mean = -0.01; SD = 0.29. Our simulation results indicate that either model is suitable for use in an experimental study of Plethodontid salamanders provided that sample sizes are sufficiently large. However, hierarchical single-scale and multi-scale models describe different processes and estimate different parameters. As a result, we recommend careful consideration of

  11. High frequent modelling of a modular multilevel converter using passive components

    DEFF Research Database (Denmark)

    El-Khatib, Walid Ziad; Holbøll, Joachim; Rasmussen, Tonny Wederberg

    2013-01-01

    ). This means that a high frequency model of the converter has to be designed, which gives a better overview of the impact of high frequency transients etc. The functionality of the model is demonstrated by application to grid connections of off-shore wind power plants. Grid connection of an offshore wind power...... wind power plant employing HVDC. In the present study, a back to back HVDC transmission system is designed in PSCAD/EMTDC. Simulations and results showing the importance of high frequent modeling are presented....... plant using HVDC fundamentally changes the electrical environment for the power plant. Detailed knowledge and understanding of the characteristics and behavior of all relevant power system components under all conditions, including under transients, are required in order to develop reliable offshore...

  12. 93-106, 2015 93 Multilevel random effect and marginal models

    African Journals Online (AJOL)

    injected by the candidate vaccine have a lower or higher risk for the occurrence of ... outcome relationship and test whether subjects inject- ... contains an agent that resembles a disease-causing ... to have different random effect variability at each cat- ... In the marginal models settings, the responses are ... Behavior as usual.

  13. A Comparison of Joint Model and Fully Conditional Specification Imputation for Multilevel Missing Data

    Science.gov (United States)

    Mistler, Stephen A.; Enders, Craig K.

    2017-01-01

    Multiple imputation methods can generally be divided into two broad frameworks: joint model (JM) imputation and fully conditional specification (FCS) imputation. JM draws missing values simultaneously for all incomplete variables using a multivariate distribution, whereas FCS imputes variables one at a time from a series of univariate conditional…

  14. The Impact of School Environment and Grade Level on Student Delinquency: A Multilevel Modeling Approach

    Science.gov (United States)

    Lo, Celia C.; Kim, Young S.; Allen, Thomas M.; Allen, Andrea N.; Minugh, P. Allison; Lomuto, Nicoletta

    2011-01-01

    Effects on delinquency made by grade level, school type (based on grade levels accommodated), and prosocial school climate were assessed, controlling for individual-level risk and protective factors. Data were obtained from the Substance Abuse Services Division of Alabama's state mental health agency and analyzed via hierarchical linear modeling,…

  15. Families, schools, and student achievement inequality: a multilevel MIMIC model approach

    Czech Academy of Sciences Publication Activity Database

    Tsai, S. L.; Smith, Michael; Hauser, R. M.

    2017-01-01

    Roč. 90, č. 1 (2017), s. 64-88 ISSN 0038-0407 R&D Projects: GA ČR GCP404/12/J006; GA ČR GB14-36154G Institutional support: RVO:67985998 Keywords : MIMIC model * educational inequality * academic performance Subject RIV: AO - Sociology, Demography OBOR OECD: Sociology Impact factor: 2.697, year: 2016

  16. Multilevel Regression Models for Mean and (Co)variance: with Applications in Nursing Research

    NARCIS (Netherlands)

    B. Li (Bayoue)

    2014-01-01

    markdownabstract__Abstract__ In this chapter, a concise overview is provided for the statistical techniques that are applied in this thesis. This includes two classes of statistical modeling approaches which have been commonly applied in plenty of research areas for many decades. Namely, we

  17. Developing a computationally efficient dynamic multilevel hybrid optimization scheme using multifidelity model interactions.

    Energy Technology Data Exchange (ETDEWEB)

    Hough, Patricia Diane (Sandia National Laboratories, Livermore, CA); Gray, Genetha Anne (Sandia National Laboratories, Livermore, CA); Castro, Joseph Pete Jr. (; .); Giunta, Anthony Andrew

    2006-01-01

    Many engineering application problems use optimization algorithms in conjunction with numerical simulators to search for solutions. The formulation of relevant objective functions and constraints dictate possible optimization algorithms. Often, a gradient based approach is not possible since objective functions and constraints can be nonlinear, nonconvex, non-differentiable, or even discontinuous and the simulations involved can be computationally expensive. Moreover, computational efficiency and accuracy are desirable and also influence the choice of solution method. With the advent and increasing availability of massively parallel computers, computational speed has increased tremendously. Unfortunately, the numerical and model complexities of many problems still demand significant computational resources. Moreover, in optimization, these expenses can be a limiting factor since obtaining solutions often requires the completion of numerous computationally intensive simulations. Therefore, we propose a multifidelity optimization algorithm (MFO) designed to improve the computational efficiency of an optimization method for a wide range of applications. In developing the MFO algorithm, we take advantage of the interactions between multi fidelity models to develop a dynamic and computational time saving optimization algorithm. First, a direct search method is applied to the high fidelity model over a reduced design space. In conjunction with this search, a specialized oracle is employed to map the design space of this high fidelity model to that of a computationally cheaper low fidelity model using space mapping techniques. Then, in the low fidelity space, an optimum is obtained using gradient or non-gradient based optimization, and it is mapped back to the high fidelity space. In this paper, we describe the theory and implementation details of our MFO algorithm. We also demonstrate our MFO method on some example problems and on two applications: earth penetrators and

  18. Multilevel index decomposition analysis: Approaches and application

    International Nuclear Information System (INIS)

    Xu, X.Y.; Ang, B.W.

    2014-01-01

    With the growing interest in using the technique of index decomposition analysis (IDA) in energy and energy-related emission studies, such as to analyze the impacts of activity structure change or to track economy-wide energy efficiency trends, the conventional single-level IDA may not be able to meet certain needs in policy analysis. In this paper, some limitations of single-level IDA studies which can be addressed through applying multilevel decomposition analysis are discussed. We then introduce and compare two multilevel decomposition procedures, which are referred to as the multilevel-parallel (M-P) model and the multilevel-hierarchical (M-H) model. The former uses a similar decomposition procedure as in the single-level IDA, while the latter uses a stepwise decomposition procedure. Since the stepwise decomposition procedure is new in the IDA literature, the applicability of the popular IDA methods in the M-H model is discussed and cases where modifications are needed are explained. Numerical examples and application studies using the energy consumption data of the US and China are presented. - Highlights: • We discuss the limitations of single-level decomposition in IDA applied to energy study. • We introduce two multilevel decomposition models, study their features and discuss how they can address the limitations. • To extend from single-level to multilevel analysis, necessary modifications to some popular IDA methods are discussed. • We further discuss the practical significance of the multilevel models and present examples and cases to illustrate

  19. Mechanical analyses on the digital behaviour of the Tokay gecko (Gekko gecko) based on a multi-level directional adhesion model

    OpenAIRE

    Wu, Xuan; Wang, Xiaojie; Mei, Tao; Sun, Shaoming

    2015-01-01

    This paper proposes a multi-level hierarchical model for the Tokay gecko (Gekko gecko) adhesive system and analyses the digital behaviour of the G. gecko under macro/meso-level scale. The model describes the structures of G. gecko's adhesive system from the nano-level spatulae to the sub-millimetre-level lamella. The G. gecko's seta is modelled using inextensible fibril based on Euler's elastica theorem. Considering the side contact of the spatular pads of the seta on the flat and rigid subst...

  20. A multi-level adaptation model of circulation for the western Indian Ocean

    Digital Repository Service at National Institute of Oceanography (India)

    Shaji, C.; Bahulayan, N.; Dube, S.K.; Rao, A.D.

    and diffusion terms in the momentum equations and also in the resultant vorticity balance. The results of the calculation indicated realistic climatological Gulf Stream behaviour in the South Atlantic Bight. Sarmiento and Bryan [7] also developed a robust... be balanced. In case the volume flux or the velocities are not balanced, appropriate corrections should be applied to the velocity fields at the boundary so that the velocities are balanced to the maximum extent possible. We have used a quasi-geostrophic model...

  1. More Precise Estimation of Lower-Level Interaction Effects in Multilevel Models.

    Science.gov (United States)

    Loeys, Tom; Josephy, Haeike; Dewitte, Marieke

    2018-01-01

    In hierarchical data, the effect of a lower-level predictor on a lower-level outcome may often be confounded by an (un)measured upper-level factor. When such confounding is left unaddressed, the effect of the lower-level predictor is estimated with bias. Separating this effect into a within- and between-component removes such bias in a linear random intercept model under a specific set of assumptions for the confounder. When the effect of the lower-level predictor is additionally moderated by another lower-level predictor, an interaction between both lower-level predictors is included into the model. To address unmeasured upper-level confounding, this interaction term ought to be decomposed into a within- and between-component as well. This can be achieved by first multiplying both predictors and centering that product term next, or vice versa. We show that while both approaches, on average, yield the same estimates of the interaction effect in linear models, the former decomposition is much more precise and robust against misspecification of the effects of cross-level and upper-level terms, compared to the latter.

  2. Multi-level emulation of a volcanic ash transport and dispersion model to quantify sensitivity to uncertain parameters

    Science.gov (United States)

    Harvey, Natalie J.; Huntley, Nathan; Dacre, Helen F.; Goldstein, Michael; Thomson, David; Webster, Helen

    2018-01-01

    Following the disruption to European airspace caused by the eruption of Eyjafjallajökull in 2010 there has been a move towards producing quantitative predictions of volcanic ash concentration using volcanic ash transport and dispersion simulators. However, there is no formal framework for determining the uncertainties of these predictions and performing many simulations using these complex models is computationally expensive. In this paper a Bayesian linear emulation approach is applied to the Numerical Atmospheric-dispersion Modelling Environment (NAME) to better understand the influence of source and internal model parameters on the simulator output. Emulation is a statistical method for predicting the output of a computer simulator at new parameter choices without actually running the simulator. A multi-level emulation approach is applied using two configurations of NAME with different numbers of model particles. Information from many evaluations of the computationally faster configuration is combined with results from relatively few evaluations of the slower, more accurate, configuration. This approach is effective when it is not possible to run the accurate simulator many times and when there is also little prior knowledge about the influence of parameters. The approach is applied to the mean ash column loading in 75 geographical regions on 14 May 2010. Through this analysis it has been found that the parameters that contribute the most to the output uncertainty are initial plume rise height, mass eruption rate, free tropospheric turbulence levels and precipitation threshold for wet deposition. This information can be used to inform future model development and observational campaigns and routine monitoring. The analysis presented here suggests the need for further observational and theoretical research into parameterisation of atmospheric turbulence. Furthermore it can also be used to inform the most important parameter perturbations for a small operational

  3. Multi-level emulation of a volcanic ash transport and dispersion model to quantify sensitivity to uncertain parameters

    Directory of Open Access Journals (Sweden)

    N. J. Harvey

    2018-01-01

    Full Text Available Following the disruption to European airspace caused by the eruption of Eyjafjallajökull in 2010 there has been a move towards producing quantitative predictions of volcanic ash concentration using volcanic ash transport and dispersion simulators. However, there is no formal framework for determining the uncertainties of these predictions and performing many simulations using these complex models is computationally expensive. In this paper a Bayesian linear emulation approach is applied to the Numerical Atmospheric-dispersion Modelling Environment (NAME to better understand the influence of source and internal model parameters on the simulator output. Emulation is a statistical method for predicting the output of a computer simulator at new parameter choices without actually running the simulator. A multi-level emulation approach is applied using two configurations of NAME with different numbers of model particles. Information from many evaluations of the computationally faster configuration is combined with results from relatively few evaluations of the slower, more accurate, configuration. This approach is effective when it is not possible to run the accurate simulator many times and when there is also little prior knowledge about the influence of parameters. The approach is applied to the mean ash column loading in 75 geographical regions on 14 May 2010. Through this analysis it has been found that the parameters that contribute the most to the output uncertainty are initial plume rise height, mass eruption rate, free tropospheric turbulence levels and precipitation threshold for wet deposition. This information can be used to inform future model development and observational campaigns and routine monitoring. The analysis presented here suggests the need for further observational and theoretical research into parameterisation of atmospheric turbulence. Furthermore it can also be used to inform the most important parameter perturbations

  4. Using clinical data to predict high-cost performance coding issues associated with pressure ulcers: a multilevel cohort model.

    Science.gov (United States)

    Padula, William V; Gibbons, Robert D; Pronovost, Peter J; Hedeker, Donald; Mishra, Manish K; Makic, Mary Beth F; Bridges, John Fp; Wald, Heidi L; Valuck, Robert J; Ginensky, Adam J; Ursitti, Anthony; Venable, Laura Ruth; Epstein, Ziv; Meltzer, David O

    2017-04-01

    Hospital-acquired pressure ulcers (HAPUs) have a mortality rate of 11.6%, are costly to treat, and result in Medicare reimbursement penalties. Medicare codes HAPUs according to Agency for Healthcare Research and Quality Patient-Safety Indicator 3 (PSI-03), but they are sometimes inappropriately coded. The objective is to use electronic health records to predict pressure ulcers and to identify coding issues leading to penalties. We evaluated all hospitalized patient electronic medical records at an academic medical center data repository between 2011 and 2014. These data contained patient encounter level demographic variables, diagnoses, prescription drugs, and provider orders. HAPUs were defined by PSI-03: stages III, IV, or unstageable pressure ulcers not present on admission as a secondary diagnosis, excluding cases of paralysis. Random forests reduced data dimensionality. Multilevel logistic regression of patient encounters evaluated associations between covariates and HAPU incidence. The approach produced a sample population of 21 153 patients with 1549 PSI-03 cases. The greatest odds ratio (OR) of HAPU incidence was among patients diagnosed with spinal cord injury (ICD-9 907.2: OR = 14.3; P  coded for paralysis, leading to a PSI-03 flag. Other high ORs included bed confinement (ICD-9 V49.84: OR = 3.1, P  coded without paralysis, leading to PSI-03 flags. The resulting statistical model can be tested to predict HAPUs during hospitalization. Inappropriate coding of conditions leads to poor hospital performance measures and Medicare reimbursement penalties. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  5. Requirements for multi-level systems pharmacology models to reach end-usage : The case of type 2 diabetes

    NARCIS (Netherlands)

    Nyman, E.; Rozendaal, Y.J.W.; Helmlinger, G.; Hamrén, B.; Kjellsson, M.C.; Strålfors, P.; van Riel, N.A.W.; Gennemark, P.; Cedersund, G.

    2016-01-01

    We are currently in the middle of a major shift in biomedical research: unprecedented and rapidly growing amounts of data may be obtained today, from in vitro, in vivo and clinical studies, at molecular, physiological and clinical levels. To make use of these large-scale, multi-level datasets,

  6. Requirements for multi-level systems pharmacology models to reach end-usage: the case of type 2 diabetes

    NARCIS (Netherlands)

    Nyman, Elin; Rozendaal, Yvonne J. W.; Helmlinger, Gabriel; Hamrén, Bengt; Kjellsson, Maria C.; Strålfors, Peter; van Riel, Natal A. W.; Gennemark, Peter; Cedersund, Gunnar

    2016-01-01

    We are currently in the middle of a major shift in biomedical research: unprecedented and rapidly growing amounts of data may be obtained today, from in vitro, in vivo and clinical studies, at molecular, physiological and clinical levels. To make use of these large-scale, multi-level datasets,

  7. Examining the Rule of Thumb of Not Using Multilevel Modeling: The "Design Effect Smaller than Two" Rule

    Science.gov (United States)

    Lai, Mark H. C.; Kwok, Oi-man

    2015-01-01

    Educational researchers commonly use the rule of thumb of "design effect smaller than 2" as the justification of not accounting for the multilevel or clustered structure in their data. The rule, however, has not yet been systematically studied in previous research. In the present study, we generated data from three different models…

  8. Modeling Multilevel Supplier Selection Problem Based on Weighted-Directed Network and Its Solution

    Directory of Open Access Journals (Sweden)

    Chia-Te Wei

    2017-01-01

    Full Text Available With the rapid development of economy, the supplier network is becoming more and more complicated. It is important to choose the right suppliers for improving the efficiency of the supply chain, so how to choose the right ones is one of the important research directions of supply chain management. This paper studies the partner selection problem from the perspective of supplier network global optimization. Firstly, this paper discusses and forms the evaluation system to estimate the supplier from the two indicators of risk and greenness and then applies the value as the weight of the network between two nodes to build a weighted-directed supplier network; secondly, the study establishes the optimal combination model of supplier selection based on the global network perspective and solves the model by the dynamic programming-tabu search algorithm and the improved ant colony algorithm, respectively; finally, different scale simulation examples are given to testify the efficiency of the two algorithms. The results show that the ant colony algorithm is superior to the tabu search one as a whole, but the latter is slightly better than the former when network scale is small.

  9. Hostility, job attitudes, and workplace deviance: test of a multilevel model.

    Science.gov (United States)

    Judge, Timothy A; Scott, Brent A; Ilies, Remus

    2006-01-01

    The authors tested a model, inspired by affective events theory (H. M. Weiss & R. Cropanzano, 1996), that examines the dynamic nature of emotions at work, work attitudes, and workplace deviance. Sixty-four employees completed daily surveys over 3 weeks, reporting their mood, job satisfaction, perceived interpersonal treatment, and deviance. Supervisors and significant others also evaluated employees' workplace deviance and trait hostility, respectively. Over half of the total variance in workplace deviance was within-individual, and this intraindividual variance was predicted by momentary hostility, interpersonal justice, and job satisfaction. Moreover, trait hostility moderated the interpersonal justice-state hostility relation such that perceived injustice was more strongly related to state hostility for individuals high in trait hostility. (c) 2006 APA, all rights reserved.

  10. Multilevel modeling of micromechanics and phase formation for microstructural evolution of magnetic zones

    International Nuclear Information System (INIS)

    Suwa, Yoshihiro; Aizawa, Tatsuhiko; Takaya, Shigeru; Nagae, Yuji; Aoto, Kazumi

    2005-03-01

    The present research aims at a proposal of theoretical treatise to describe the local phase transformation from austenite to ferrite in the stainless steels under hot cyclic fatigue conditions. In experiments, this local phase transformation is detected as a magnetized region in the non-magnetic matrix after low-cycle fatigue test at the elevated temperature. The theoretical frame proposed here is composed of two methodologies. In the first approach, microstructure evolution with γ → α transformation is described by the phase field method. In the second approach, micromechanical method on the basis of the unit cell modeling is proposed to develop a new micromechanical analysis. The details of two approached are summarized in the following. (1) Phase formation simulation by the phase field method. Most of reports have started that γ-α phase transformation as a creep damage is induced by dechromization, which comes from carbide precipitation around grain boundaries. A new theoretical treatise is proposed for simulating this γ → α transformation in Fe-Cr-Ni system. Stabilities of both phases are investigated for various chemical compositions. Furthermore, in order to investigate dechromization phenomena in Fe-Cr-Ni-C system, a new theoretical frame is also proposed to handle an interstitial element in phase field method. (2) Low cycle fatigue elasto-plastic analysis by the unit-cell modeling. In experiments, the magnetized zones are generated to distribute at the vicinity of the hard, delta-phase inclusion in the austenitic matrix. The cumulative plastic region advances in the surroundings of this hard inclusion with increasing the number of cycles in the controlled strain range. This predicted profile of cumulative plastic regions corresponds to the experimentally measured, magnetized zones. In addition, the effect of geometric configuration of this inclusion on the plastic region evolution has close relationship of creep damage advancement in experiments

  11. A multi-level model of blood lead as a function of air lead.

    Science.gov (United States)

    Richmond-Bryant, Jennifer; Meng, Qingyu; Davis, J Allen; Cohen, Jonathan; Svendsgaard, David; Brown, James S; Tuttle, Lauren; Hubbard, Heidi; Rice, Joann; Kirrane, Ellen; Vinikoor-Imler, Lisa; Kotchmar, Dennis; Hines, Erin; Ross, Mary

    2013-09-01

    National and local declines in lead (Pb) in blood (PbB) over the past several years coincide with the decline in ambient air Pb (PbA) concentrations. The objective of this work is to evaluate how the relationship between PbB levels and PbA levels has changed following the phase out of leaded gasoline and tightened controls on industrial Pb emissions over the past 30 years among a national population sample. Participant-level data from the National Health and Nutrition Examination Survey (NHANES) were employed for two time periods (1988-1994 and 1999-2008), and the model was corrected for housing, demographic, socioeconomic, and other covariates present in NHANES. NHANES data for PbB and covariates were merged with PbA data from the U.S. Environmental Protection Agency. Linear mixed effects models (LMEs) were run to assess the relationship of PbB with PbA; sample weights were omitted, given biases encountered with the use of sample weights in LMEs. The 1988-1994 age-stratified results found that ln(PbB) was statistically significantly associated with ln(PbA) for all age groups. The consistent influence of PbA on PbB across age groups for the years 1988-1994 suggests a ubiquitous exposure unrelated to age of the sample population. The comparison of effect estimates for ln(PbA) shows a statistically significant effect estimate and ANOVA results for ln(PbB) for the 6- to 11-year and 12- to 19-year age groups during 1999-2008. The more recent finding suggests that PbA has less consistent influence on PbB compared with other factors. Copyright © 2013 Elsevier B.V. All rights reserved.

  12. Exploring Multilevel Factors for Family Engagement in Home Visiting Across Two National Models.

    Science.gov (United States)

    Latimore, Amanda D; Burrell, Lori; Crowne, Sarah; Ojo, Kristen; Cluxton-Keller, Fallon; Gustin, Sunday; Kruse, Lakota; Hellman, Daniela; Scott, Lenore; Riordan, Annette; Duggan, Anne

    2017-07-01

    The associations of family, home visitor and site characteristics with family engagement within the first 6 months were examined. The variation in family engagement was also explored. Home visiting program participants were drawn from 21 Healthy Families America sites (1707 families) and 9 Nurse-Family Partnership sites (650 families) in New Jersey. Three-level nested generalized linear mixed models assessed the associations of family, home visitor and site characteristics with family receipt of a high dose of services in the first 6 months of enrollment. A family was considered to have received a high dose of service in the first 6 months of enrollment if they were active at 6 months and had received at least 50% of their expected visits in the first 6 months. In general, both home visiting programs engaged, at a relatively high level (Healthy Families America (HFA) 59%, Nurse-Family Partnership (NFP) 64%), with families demonstrating high-risk characteristics such as lower maternal education, maternal smoking, and maternal mental health need. Home visitor characteristics explained more of the variation (87%) in the receipt of services for HFA, while family characteristics explained more of the variation (75%) in the receipt of services for NFP. At the family level, NFP may improve the consistency with which they engage families by increasing retention efforts among mothers with lower education and smoking mothers. HFA sites seeking to improve engagement consistency should consider increasing the flexible in home visitor job responsibilities and examining the current expected-visit policies followed by home visitors on difficult-to-engage families.

  13. Modeling Floor Effects in Standardized Vocabulary Test Scores in a Sample of Low SES Hispanic Preschool Children under the Multilevel Structural Equation Modeling Framework

    Directory of Open Access Journals (Sweden)

    Leina Zhu

    2017-12-01

    Full Text Available Researchers and practitioners often use standardized vocabulary tests such as the Peabody Picture Vocabulary Test-4 (PPVT-4; Dunn and Dunn, 2007 and its companion, the Expressive Vocabulary Test-2 (EVT-2; Williams, 2007, to assess English vocabulary skills as an indicator of children's school readiness. Despite their psychometric excellence in the norm sample, issues arise when standardized vocabulary tests are used to asses children from culturally, linguistically and ethnically diverse backgrounds (e.g., Spanish-speaking English language learners or delayed in some manner. One of the biggest challenges is establishing the appropriateness of these measures with non-English or non-standard English speaking children as often they score one to two standard deviations below expected levels (e.g., Lonigan et al., 2013. This study re-examines the issues in analyzing the PPVT-4 and EVT-2 scores in a sample of 4-to-5-year-old low SES Hispanic preschool children who were part of a larger randomized clinical trial on the effects of a supplemental English shared-reading vocabulary curriculum (Pollard-Durodola et al., 2016. It was found that data exhibited strong floor effects and the presence of floor effects made it difficult to differentiate the invention group and the control group on their vocabulary growth in the intervention. A simulation study is then presented under the multilevel structural equation modeling (MSEM framework and results revealed that in regular multilevel data analysis, ignoring floor effects in the outcome variables led to biased results in parameter estimates, standard error estimates, and significance tests. Our findings suggest caution in analyzing and interpreting scores of ethnically and culturally diverse children on standardized vocabulary tests (e.g., floor effects. It is recommended appropriate analytical methods that take into account floor effects in outcome variables should be considered.

  14. Abuse of Older Men in Seven European Countries: A Multilevel Approach in the Framework of an Ecological Model.

    Science.gov (United States)

    Melchiorre, Maria Gabriella; Di Rosa, Mirko; Lamura, Giovanni; Torres-Gonzales, Francisco; Lindert, Jutta; Stankunas, Mindaugas; Ioannidi-Kapolou, Elisabeth; Barros, Henrique; Macassa, Gloria; Soares, Joaquim J F

    2016-01-01

    Several studies on elder abuse indicate that a large number of victims are women, but others report that men in later life are also significantly abused, especially when they show symptoms of disability and poor health, and require help for their daily activities as a result. This study focused on the prevalence of different types of abuse experienced by men and on a comparison of male victims and non-victims concerning demographic/socio-economic characteristics, lifestyle/health variables, social support and quality of life. Additionally, the study identified factors associated with different types of abuse experienced by men and characteristics associated with the victims. The cross-sectional data concerning abuse in the past 12 months were collected by means of interviews and self-response during January-July 2009, from a sample of 4,467 not demented individuals aged between 60-84 years living in seven European countries (Germany, Greece, Italy, Lithuania, Portugal, Spain and Sweden). We used a multilevel approach, within the framework of an Ecological Model, to explore the phenomenon of abuse against males as the complex result of factors from multiple levels: individual, relational, community and societal. Multivariate analyses showed that older men educated to higher levels, blue-collar workers and men living in a rented accommodation were more often victims than those educated to lower levels, low-rank white-collar workers and home owners, respectively. In addition, high scores for factors such as somatic and anxiety symptoms seemed linked with an increased probability of being abused. Conversely, factors such as increased age, worries about daily expenses (financial strain) and greater social support seemed linked with a decreased probability of being abused. Male elder abuse is under-recognized, under-detected and under-reported, mainly due to the vulnerability of older men and to social/cultural norms supporting traditional male characteristics of

  15. Multilevel models for evaluating the risk of pedestrian-motor vehicle collisions at intersections and mid-blocks.

    Science.gov (United States)

    Quistberg, D Alex; Howard, Eric J; Ebel, Beth E; Moudon, Anne V; Saelens, Brian E; Hurvitz, Philip M; Curtin, James E; Rivara, Frederick P

    2015-11-01

    Walking is a popular form of physical activity associated with clear health benefits. Promoting safe walking for pedestrians requires evaluating the risk of pedestrian-motor vehicle collisions at specific roadway locations in order to identify where road improvements and other interventions may be needed. The objective of this analysis was to estimate the risk of pedestrian collisions at intersections and mid-blocks in Seattle, WA. The study used 2007-2013 pedestrian-motor vehicle collision data from police reports and detailed characteristics of the microenvironment and macroenvironment at intersection and mid-block locations. The primary outcome was the number of pedestrian-motor vehicle collisions over time at each location (incident rate ratio [IRR] and 95% confidence interval [95% CI]). Multilevel mixed effects Poisson models accounted for correlation within and between locations and census blocks over time. Analysis accounted for pedestrian and vehicle activity (e.g., residential density and road classification). In the final multivariable model, intersections with 4 segments or 5 or more segments had higher pedestrian collision rates compared to mid-blocks. Non-residential roads had significantly higher rates than residential roads, with principal arterials having the highest collision rate. The pedestrian collision rate was higher by 9% per 10 feet of street width. Locations with traffic signals had twice the collision rate of locations without a signal and those with marked crosswalks also had a higher rate. Locations with a marked crosswalk also had higher risk of collision. Locations with a one-way road or those with signs encouraging motorists to cede the right-of-way to pedestrians had fewer pedestrian collisions. Collision rates were higher in locations that encourage greater pedestrian activity (more bus use, more fast food restaurants, higher employment, residential, and population densities). Locations with higher intersection density had a lower

  16. Abuse of Older Men in Seven European Countries: A Multilevel Approach in the Framework of an Ecological Model.

    Directory of Open Access Journals (Sweden)

    Maria Gabriella Melchiorre

    Full Text Available Several studies on elder abuse indicate that a large number of victims are women, but others report that men in later life are also significantly abused, especially when they show symptoms of disability and poor health, and require help for their daily activities as a result. This study focused on the prevalence of different types of abuse experienced by men and on a comparison of male victims and non-victims concerning demographic/socio-economic characteristics, lifestyle/health variables, social support and quality of life. Additionally, the study identified factors associated with different types of abuse experienced by men and characteristics associated with the victims.The cross-sectional data concerning abuse in the past 12 months were collected by means of interviews and self-response during January-July 2009, from a sample of 4,467 not demented individuals aged between 60-84 years living in seven European countries (Germany, Greece, Italy, Lithuania, Portugal, Spain and Sweden. We used a multilevel approach, within the framework of an Ecological Model, to explore the phenomenon of abuse against males as the complex result of factors from multiple levels: individual, relational, community and societal.Multivariate analyses showed that older men educated to higher levels, blue-collar workers and men living in a rented accommodation were more often victims than those educated to lower levels, low-rank white-collar workers and home owners, respectively. In addition, high scores for factors such as somatic and anxiety symptoms seemed linked with an increased probability of being abused. Conversely, factors such as increased age, worries about daily expenses (financial strain and greater social support seemed linked with a decreased probability of being abused.Male elder abuse is under-recognized, under-detected and under-reported, mainly due to the vulnerability of older men and to social/cultural norms supporting traditional male

  17. Transport and Deposition of Micro-and Nano-Particles in Human Tracheobronchial Tree by an Asymmetric Multi-Level Bifurcation Model

    Directory of Open Access Journals (Sweden)

    Lin Tian

    2012-06-01

    Full Text Available Transport and deposition of particles in the upper tracheobronchial tree were analyzed using a multi-level asymmetric lung bifurcation model. The first three generations of tracheobronchial tree were included in the study. The laryngeal jet at the trachea entrance was modeled as an effective turbulence disturbance, and the study was focused on how to accurately simulate the airflow and predict the motion of the inhaled particles. Downstream in the lower level of the bronchial region, a laminar flow model was used, as smoother flow condition was expected. Transport and deposition of nano- and micro-scale spherical particles in the range of 0.01 μm to 30 μm were evaluated. The particle local deposition pattern and deposition rate in the lung bifurcation was discussed. The proposed multi-level asymmetric lung bifurcation model was found to be flexible, easy to use and computationally highly efficient. It was also shown that the selection of the anisotropic Reynolds stress transport turbulence model (RSTM was appropriate, and the use of the enhanced two-layer model boundary treatment was needed for accurate simulation of the turbulent airflow conditions in the upper airways.

  18. Development and validation of a multilevel model for predicting workload under routine and nonroutine conditions in an air traffic management center.

    Science.gov (United States)

    Neal, Andrew; Hannah, Sam; Sanderson, Penelope; Bolland, Scott; Mooij, Martijn; Murphy, Sean

    2014-03-01

    The aim of this study was to develop a model capable of predicting variability in the mental workload experienced by frontline operators under routine and nonroutine conditions. Excess workload is a risk that needs to be managed in safety-critical industries. Predictive models are needed to manage this risk effectively yet are difficult to develop. Much of the difficulty stems from the fact that workload prediction is a multilevel problem. A multilevel workload model was developed in Study I with data collected from an en route air traffic management center. Dynamic density metrics were used to predict variability in workload within and between work units while controlling for variability among raters.The model was cross-validated in Studies 2 and 3 with the use of a high-fidelity simulator. Reported workload generally remained within the bounds of the 90% prediction interval in Studies 2 and 3. Workload crossed the upper bound of the prediction interval only under nonroutine conditions. Qualitative analyses suggest that nonroutine events caused workload to cross the upper bound of the prediction interval because the controllers could not manage their workload strategically. The model performed well under both routine and nonroutine conditions and over different patterns of workload variation. Workload prediction models can be used to support both strategic and tactical workload management. Strategic uses include the analysis of historical and projected workflows and the assessment of staffing needs.Tactical uses include the dynamic reallocation of resources to meet changes in demand.

  19. Fast multilevel radiative transfer

    International Nuclear Information System (INIS)

    Paletou, Frederic; Leger, Ludovick

    2007-01-01

    The vast majority of recent advances in the field of numerical radiative transfer relies on approximate operator methods better known in astrophysics as Accelerated Lambda-Iteration (ALI). A superior class of iterative schemes, in term of rates of convergence, such as Gauss-Seidel and successive overrelaxation methods were therefore quite naturally introduced in the field of radiative transfer by Trujillo Bueno and Fabiani Bendicho [A novel iterative scheme for the very fast and accurate solution of non-LTE radiative transfer problems. Astrophys J 1995;455:646]; it was thoroughly described for the non-LTE two-level atom case. We describe hereafter in details how such methods can be generalized when dealing with non-LTE unpolarised radiation transfer with multilevel atomic models, in monodimensional geometry

  20. Multilevel ensemble Kalman filter

    KAUST Repository

    Chernov, Alexey; Hoel, Haakon; Law, Kody; Nobile, Fabio; Tempone, Raul

    2016-01-01

    This work embeds a multilevel Monte Carlo (MLMC) sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF). In terms of computational cost vs. approximation error the asymptotic performance of the multilevel ensemble Kalman filter (MLEnKF) is superior to the EnKF s.

  1. Multilevel ensemble Kalman filter

    KAUST Repository

    Chernov, Alexey

    2016-01-06

    This work embeds a multilevel Monte Carlo (MLMC) sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF). In terms of computational cost vs. approximation error the asymptotic performance of the multilevel ensemble Kalman filter (MLEnKF) is superior to the EnKF s.

  2. A multilevel simultaneous equations model for within-cluster dynamic effects, with an application to reciprocal parent-child and sibling effects.

    Science.gov (United States)

    Steele, Fiona; Rasbash, Jon; Jenkins, Jennifer

    2013-03-01

    There has been substantial interest in the social and health sciences in the reciprocal causal influences that people in close relationships have on one another. Most research has considered reciprocal processes involving only 2 units, although many social relationships of interest occur within a larger group (e.g., families, work groups, peer groups, classrooms). This article presents a general longitudinal multilevel modeling framework for the simultaneous estimation of reciprocal relationships among individuals with unique roles operating in a social group. We use family data for illustrative purposes, but the model is generalizable to any social group in which measurements of individuals in the social group occur over time, individuals have unique roles, and clustering of the data is evident. We allow for the possibility that the outcomes of family members are influenced by a common set of unmeasured family characteristics. The multilevel model we propose allows for residual variation in the outcomes of parents and children at the occasion, individual, and family levels and residual correlation between parents and children due to the unmeasured shared environment, genetic factors, and shared measurement. Another advantage of this method over approaches used in previous family research is it can handle mixed family sizes. The method is illustrated in an analysis of maternal depression and child delinquency using data from the Avon Brothers and Sisters Study. PsycINFO Database Record (c) 2013 APA, all rights reserved.

  3. EUROPEAN INTEGRATION: A MULTILEVEL PROCESS THAT REQUIRES A MULTILEVEL STATISTICAL ANALYSIS

    Directory of Open Access Journals (Sweden)

    Roxana-Otilia-Sonia HRITCU

    2015-11-01

    Full Text Available A process of market regulation and a system of multi-level governance and several supranational, national and subnational levels of decision making, European integration subscribes to being a multilevel phenomenon. The individual characteristics of citizens, as well as the environment where the integration process takes place, are important. To understand the European integration and its consequences it is important to develop and test multi-level theories that consider individual-level characteristics, as well as the overall context where individuals act and express their characteristics. A central argument of this paper is that support for European integration is influenced by factors operating at different levels. We review and present theories and related research on the use of multilevel analysis in the European area. This paper draws insights on various aspects and consequences of the European integration to take stock of what we know about how and why to use multilevel modeling.

  4. Differences in within- and between-person factor structure of positive and negative affect: analysis of two intensive measurement studies using multilevel structural equation modeling.

    Science.gov (United States)

    Rush, Jonathan; Hofer, Scott M

    2014-06-01

    The Positive and Negative Affect Schedule (PANAS) is a widely used measure of emotional experience. The factor structure of the PANAS has been examined predominantly with cross-sectional designs, which fails to disaggregate within-person variation from between-person differences. There is still uncertainty as to the factor structure of positive and negative affect and whether they constitute 2 distinct independent factors. The present study examined the within-person and between-person factor structure of the PANAS in 2 independent samples that reported daily affect over 7 and 14 occasions, respectively. Results from multilevel confirmatory factor analyses revealed that a 2-factor structure at both the within-person and between-person levels, with correlated specific factors for overlapping items, provided good model fit. The best-fitting solution was one where within-person factors of positive and negative affect were inversely correlated, but between-person factors were independent. The structure was further validated through multilevel structural equation modeling examining the effects of cognitive interference, daily stress, physical symptoms, and physical activity on positive and negative affect factors.

  5. Using cross-classified multilevel models to disentangle school and neighborhood effects: an example focusing on smoking behaviors among adolescents in the United States.

    Science.gov (United States)

    Dunn, Erin C; Richmond, Tracy K; Milliren, Carly E; Subramanian, S V

    2015-01-01

    Despite much interest in understanding the influence of contexts on health, most research has focused on one context at a time, ignoring the reality that individuals have simultaneous memberships in multiple settings. Using the example of smoking behavior among adolescents in the National Longitudinal Study of Adolescent Health, we applied cross-classified multilevel modeling (CCMM) to examine fixed and random effects for schools and neighborhoods. We compared the CCMM results with those obtained from a traditional multilevel model (MLM) focused on either the school and neighborhood separately. In the MLMs, 5.2% of the variation in smoking was due to differences between neighborhoods (when schools were ignored) and 6.3% of the variation in smoking was due to differences between schools (when neighborhoods were ignored). However in the CCMM examining neighborhood and school variation simultaneously, the neighborhood-level variation was reduced to 0.4%. Results suggest that using MLM, instead of CCMM, could lead to overestimating the importance of certain contexts and could ultimately lead to targeting interventions or policies to the wrong settings. Copyright © 2014 Elsevier Ltd. All rights reserved.

  6. Multilevel optimization algorithms and applications

    CERN Document Server

    Pardalos, Panos; Värbrand, Peter

    1998-01-01

    Researchers working with nonlinear programming often claim "the word is non­ linear" indicating that real applications require nonlinear modeling. The same is true for other areas such as multi-objective programming (there are always several goals in a real application), stochastic programming (all data is uncer­ tain and therefore stochastic models should be used), and so forth. In this spirit we claim: The word is multilevel. In many decision processes there is a hierarchy of decision makers, and decisions are made at different levels in this hierarchy. One way to handle such hierar­ chies is to focus on one level and include other levels' behaviors as assumptions. Multilevel programming is the research area that focuses on the whole hierar­ chy structure. In terms of modeling, the constraint domain associated with a multilevel programming problem is implicitly determined by a series of opti­ mization problems which must be solved in a predetermined sequence. If only two levels are considered, we have ...

  7. Multilevel ensemble Kalman filtering

    KAUST Repository

    Hoel, Hakon

    2016-06-14

    This work embeds a multilevel Monte Carlo sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF) in the setting of finite dimensional signal evolution and noisy discrete-time observations. The signal dynamics is assumed to be governed by a stochastic differential equation (SDE), and a hierarchy of time grids is introduced for multilevel numerical integration of that SDE. The resulting multilevel EnKF is proved to asymptotically outperform EnKF in terms of computational cost versus approximation accuracy. The theoretical results are illustrated numerically.

  8. Multilevel ensemble Kalman filtering

    KAUST Repository

    Hoel, Hakon; Law, Kody J. H.; Tempone, Raul

    2016-01-01

    This work embeds a multilevel Monte Carlo sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF) in the setting of finite dimensional signal evolution and noisy discrete-time observations. The signal dynamics is assumed to be governed by a stochastic differential equation (SDE), and a hierarchy of time grids is introduced for multilevel numerical integration of that SDE. The resulting multilevel EnKF is proved to asymptotically outperform EnKF in terms of computational cost versus approximation accuracy. The theoretical results are illustrated numerically.

  9. Federalism and multilevel governance

    NARCIS (Netherlands)

    van der Wusten, H.; Agnew, J.; Mamadouh, V.; Secor, A.J.; Sharp, J.

    2015-01-01

    Federalism and multilevel governance both emphasize polycentricity in governing arrangements. With their different intellectual pedigrees, these concepts are discussed in two separate sections. Fragments are now increasingly mixed up in hybrid forms of governance that also encompass originally

  10. Socio-economic determinants in selecting childhood diarrhoea treatment options in Sub-Saharan Africa: A multilevel model

    Directory of Open Access Journals (Sweden)

    Lawoko Stephen

    2011-03-01

    Full Text Available Abstract Background Diarrhoea disease which has been attributed to poverty constitutes a major cause of morbidity and mortality in children aged five and below in most low-and-middle income countries. This study sought to examine the contribution of individual and neighbourhood socio-economic characteristics to caregiver's treatment choices for managing childhood diarrhoea at household level in sub-Saharan Africa. Methods Multilevel multinomial logistic regression analysis was applied to Demographic and Health Survey data conducted in 11 countries in sub-Saharan Africa. The unit of analysis were the 12,988 caregivers of children who were reported to have had diarrhoea two weeks prior to the survey period. Results There were variability in selecting treatment options based on several socioeconomic characteristics. Multilevel-multinomial regression analysis indicated that higher level of education of both the caregiver and that of the partner, as well as caregivers occupation were associated with selection of medical centre, pharmacies and home care as compared to no treatment. In contrast, caregiver's partners' occupation was negatively associated with selection medical centre and home care for managing diarrhoea. In addition, a low-level of neighbourhood socio-economic disadvantage was significantly associated with selection of both medical centre and pharmacy stores and medicine vendors. Conclusion In the light of the findings from this study, intervention aimed at improving on care seeking for managing diarrhoea episode and other childhood infectious disease should jointly consider the influence of both individual SEP and the level of economic development of the communities in which caregivers of these children resides.

  11. Effect of a Multi-Level Education Intervention Model on Knowledge and Attitudes of Accidental Injuries in Rural Children in Zunyi, Southwest China

    Directory of Open Access Journals (Sweden)

    Bo-Ling Cao

    2015-04-01

    Full Text Available Objective: To explore the effect of a school-family-individual (SFI multi-level education intervention model on knowledge and attitudes about accidental injuries among school-aged children to improve injury prevention strategies and reduce the incidence of pediatric injuries. Methods: The random sample of rural school-aged children were recruited by using a multistage, stratified, cluster sampling method in Zunyi, Southwest China from 2012 to 2014, and 2342 children were randomly divided into intervention and control groups. Then children answered a baseline survey to collect knowledge and attitude scores (KAS of accidental injuries. In the intervention group, children, their parents/guardians and the school received a SFI multi-level education intervention, which included a children’s injury-prevention poster at schools, an open letter about security instruction for parents/guardians and multiple-media health education (Microsoft PowerPoint lectures, videos, handbooks, etc. to children. Children in the control group were given only handbook education. After 16 months, children answered a follow-up survey to collect data on accidental injury types and accidental injury-related KAS for comparing the intervention and control groups and baseline and follow-up data. Results: The distribution of gender was not significantly different while age was different between the baseline and follow-up survey. At baseline, the mean KAS was lower for the intervention than control group (15.37 ± 3.40 and 18.35 ± 5.01; p < 0.001. At follow-up, the mean KAS was higher for the intervention than control group (21.16 ± 3.05 and 20.02 ± 3.40; p < 0.001. The increase in KAS in the intervention and control groups was significant (p < 0.001; KAS: 5.79 vs. 1.67 and suggested that children’s injury-related KAS improved in the intervention group. Moreover, the KAS between the groups differed for most subtypes of incidental injuries (based on International

  12. The relevance of the school socioeconomic composition and school proportion of repeaters on grade repetition in Brazil: a multilevel logistic model of PISA 2012

    Directory of Open Access Journals (Sweden)

    Maria Eugénia Ferrão

    2017-02-01

    Full Text Available Abstract The paper extends the literature on grade repetition in Brazil by (a describing and synthesizing the main research findings and contributions since 1940, (b enlarging the understanding of the inequity mechanism in education, and (c providing new findings on the effects of the school socioeconomic composition and school proportion of repeaters on the individual probability of grade repetition. Based on the analyses of empirical distributions and multilevel logistic modelling of PISA 2012 data, the findings indicate that higher student socioeconomic status is associated with lower probability of repetition, there is a cumulative risk of repetition after an early repetition, the school socioeconomic composition is strongly correlated with the school proportion of repeaters, and both are related to the individual probability of repetition. The results suggest the existence of a pattern that cumulatively reinforces the effects of social disadvantage, in which the school plays a central role.

  13. Application of qualitative reasoning with functional knowledge represented by Multilevel Flow Modeling to diagnosis of accidental situation in nuclear power plant

    International Nuclear Information System (INIS)

    Yoshida, Kazuo; Tanabe, Fumiya; Kawase, Katumi.

    1996-01-01

    It has been proposed to use the Multilevel Flow Modeling (MFM) by M. Lind as a framework for functional knowledge representation for qualitative reasoning in a complex process system such as nuclear power plant. To build a knowledge base with MFM framework makes it possible to represent functional characteristics in different levels of abstraction and aggregation. A pilot inference system based on the qualitative reasoning with MFM has been developed to diagnose a cause of abnormal events in a typical PWR power plant. Some single failure events has been diagnosed with this system to verify the proposed method. In the verification study, some investigation has been also performed to clarify the effects of this knowledge representation in efficiency of reasoning and ambiguity of qualitative reasoning. (author)

  14. Space Vector Pulse Width Modulation of a Multi-Level Diode ...

    African Journals Online (AJOL)

    Space Vector Pulse Width Modulation of a Multi-Level Diode Clamped ... of MATLAB /SIMULINK modeling of the space vector pulse-width modulation and the ... two adjacent active vectors in determining the switching process of the multilevel ...

  15. Multilevel geometry optimization

    Science.gov (United States)

    Rodgers, Jocelyn M.; Fast, Patton L.; Truhlar, Donald G.

    2000-02-01

    Geometry optimization has been carried out for three test molecules using six multilevel electronic structure methods, in particular Gaussian-2, Gaussian-3, multicoefficient G2, multicoefficient G3, and two multicoefficient correlation methods based on correlation-consistent basis sets. In the Gaussian-2 and Gaussian-3 methods, various levels are added and subtracted with unit coefficients, whereas the multicoefficient Gaussian-x methods involve noninteger parameters as coefficients. The multilevel optimizations drop the average error in the geometry (averaged over the 18 cases) by a factor of about two when compared to the single most expensive component of a given multilevel calculation, and in all 18 cases the accuracy of the atomization energy for the three test molecules improves; with an average improvement of 16.7 kcal/mol.

  16. Multilevel geometry optimization

    Energy Technology Data Exchange (ETDEWEB)

    Rodgers, Jocelyn M. [Department of Chemistry and Supercomputer Institute, University of Minnesota, Minneapolis, Minnesota 55455-0431 (United States); Fast, Patton L. [Department of Chemistry and Supercomputer Institute, University of Minnesota, Minneapolis, Minnesota 55455-0431 (United States); Truhlar, Donald G. [Department of Chemistry and Supercomputer Institute, University of Minnesota, Minneapolis, Minnesota 55455-0431 (United States)

    2000-02-15

    Geometry optimization has been carried out for three test molecules using six multilevel electronic structure methods, in particular Gaussian-2, Gaussian-3, multicoefficient G2, multicoefficient G3, and two multicoefficient correlation methods based on correlation-consistent basis sets. In the Gaussian-2 and Gaussian-3 methods, various levels are added and subtracted with unit coefficients, whereas the multicoefficient Gaussian-x methods involve noninteger parameters as coefficients. The multilevel optimizations drop the average error in the geometry (averaged over the 18 cases) by a factor of about two when compared to the single most expensive component of a given multilevel calculation, and in all 18 cases the accuracy of the atomization energy for the three test molecules improves; with an average improvement of 16.7 kcal/mol. (c) 2000 American Institute of Physics.

  17. Quantifying the Variability of Internode Allometry within and between Trees for Pinus tabulaeformis Carr. Using a Multilevel Nonlinear Mixed-Effect Model

    Directory of Open Access Journals (Sweden)

    Jun Diao

    2014-11-01

    Full Text Available Allometric models of internodes are an important component of Functional-Structural Plant Models (FSPMs, which represent the shape of internodes in tree architecture and help our understanding of resource allocation in organisms. Constant allometry is always assumed in these models. In this paper, multilevel nonlinear mixed-effect models were used to characterize the variability of internode allometry, describing the relationship between the last internode length and biomass of Pinus tabulaeformis Carr. trees within the GreenLab framework. We demonstrated that there is significant variability in allometric relationships at the tree and different-order branch levels, and the variability decreases among levels from trees to first-order branches and, subsequently, to second-order branches. The variability was partially explained by the random effects of site characteristics, stand age, density, and topological position of the internode. Tree- and branch-level-specific allometric models are recommended because they produce unbiased and accurate internode length estimates. The model and method developed in this study are useful for understanding and describing the structure and functioning of trees.

  18. Applying multilevel model to the relationship of dietary patterns and colorectal cancer: an ongoing case-control study in Córdoba, Argentina.

    Science.gov (United States)

    Pou, Sonia Alejandra; Díaz, María del Pilar; Osella, Alberto Rubén

    2012-09-01

    Scientific literature has consistently shown the effects of certain diets on health but regional variations of dietary habits, and their relationship colorectal cancer (CRC) has been poorly studied in Argentina. Our aims were to identify dietary patterns and estimate their effect on CRC occurrence and to quantify the association between family history of CRC and CRC occurrence by applying multilevel models to estimate and interpret measures of variation. Principal components factor analysis was performed to identify dietary patterns that were then used in a multilevel logistic regression applied to an ongoing case-control data about dietary exposure and CRC occurrence taking into account familiar clustering. Three dietary patterns were identified: "Southern Cone pattern" (red meat, wine, and starchy vegetables), "High-sugar drinks pattern", and "Prudent pattern". The study considered 41 cases and 95 controls. There was a significant promoting effects on CRC of "Southern Cone" (OR 1.5, 95%CI 1.0-2.2) and "High-sugar drinks" (OR 3.8, 95%CI 2.0-7.1) patterns, whereas "Prudent pattern" (OR 0.3, 95%CI 0.2-0.4) showed a significant protective effect at third tertile level. BMI, use of NSAIDs, and to have medical insurance showed significant effects. Variance of the random effect of family history of CRC was highly significant. This novel approach for Argentina showed that Southern Cone and High-sugar drinks patterns were associated with a higher risk of CRC, whereas the Prudent pattern showed a protective effect. There was a significant clustering effect of family history of CRC.

  19. Hospital organizational factors influence work-family conflict in registered nurses: Multilevel modeling of a nation-wide cross-sectional survey in Sweden.

    Science.gov (United States)

    Leineweber, C; Chungkham, H S; Westerlund, H; Tishelman, C; Lindqvist, R

    2014-05-01

    The present shortage of registered nurses (RNs) in many European countries is expected to continue and worsen, which poses a substantial threat to the maintenance of healthcare in this region. Work-family conflict is a known risk factor for turnover and sickness absence. This paper empirically examines whether the nurse practice environment is associated with experienced work-family conflict. A multilevel model was fit with the individual RN at the 1st, and the hospital department at the 2nd level using cross-sectional RN survey data from the Swedish part of RN4CAST, an EU 7th framework project. The data analyzed here is based on a national sample of 8356 female and 592 male RNs from 369 hospital departments. We found that 6% of the variability in work-family conflict experienced by RNs was at the department level. Organizational level factors significantly accounted for most of the variability at this level with two of the work practice environment factors examined, staffing adequacy and nurse involvement in hospital affairs, significantly related to work-family conflict. Due to the design of the study, factors on ward and work group levels could not be analyzed, but are likely to account for additional variance which in the present analysis appears to be on the individual level, with private life factors likely explaining another major part. These results suggest that higher level organizational factors in health care have a significant impact on the risk of work-family conflict among RNs through their impact on the nurse practice environment. Lower level organizational factors should be investigated in future studies using hierarchical multilevel sampling. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

  20. Multilevel Cultural Issues

    NARCIS (Netherlands)

    van Herk, H.; Fischer, Ronald; van Herk, Hester; Torelli, Carlos J.

    2017-01-01

    Multi-level structures are omnipresent. Consumers live in geographical locations, shop in specific stores, or are members of clubs. Consumers who belong to the same group share characteristics and are expected to be more similar than consumers belonging to another group. In data analysis this

  1. Short-Term Effects of Climatic Variables on Hand, Foot, and Mouth Disease in Mainland China, 2008-2013: A Multilevel Spatial Poisson Regression Model Accounting for Overdispersion.

    Science.gov (United States)

    Liao, Jiaqiang; Yu, Shicheng; Yang, Fang; Yang, Min; Hu, Yuehua; Zhang, Juying

    2016-01-01

    Hand, Foot, and Mouth Disease (HFMD) is a worldwide infectious disease. In China, many provinces have reported HFMD cases, especially the south and southwest provinces. Many studies have found a strong association between the incidence of HFMD and climatic factors such as temperature, rainfall, and relative humidity. However, few studies have analyzed cluster effects between various geographical units. The nonlinear relationships and lag effects between weekly HFMD cases and climatic variables were estimated for the period of 2008-2013 using a polynomial distributed lag model. The extra-Poisson multilevel spatial polynomial model was used to model the exact relationship between weekly HFMD incidence and climatic variables after considering cluster effects, provincial correlated structure of HFMD incidence and overdispersion. The smoothing spline methods were used to detect threshold effects between climatic factors and HFMD incidence. The HFMD incidence spatial heterogeneity distributed among provinces, and the scale measurement of overdispersion was 548.077. After controlling for long-term trends, spatial heterogeneity and overdispersion, temperature was highly associated with HFMD incidence. Weekly average temperature and weekly temperature difference approximate inverse "V" shape and "V" shape relationships associated with HFMD incidence. The lag effects for weekly average temperature and weekly temperature difference were 3 weeks and 2 weeks. High spatial correlated HFMD incidence were detected in northern, central and southern province. Temperature can be used to explain most of variation of HFMD incidence in southern and northeastern provinces. After adjustment for temperature, eastern and Northern provinces still had high variation HFMD incidence. We found a relatively strong association between weekly HFMD incidence and weekly average temperature. The association between the HFMD incidence and climatic variables spatial heterogeneity distributed across

  2. Short-Term Effects of Climatic Variables on Hand, Foot, and Mouth Disease in Mainland China, 2008–2013: A Multilevel Spatial Poisson Regression Model Accounting for Overdispersion

    Science.gov (United States)

    Yang, Fang; Yang, Min; Hu, Yuehua; Zhang, Juying

    2016-01-01

    Background Hand, Foot, and Mouth Disease (HFMD) is a worldwide infectious disease. In China, many provinces have reported HFMD cases, especially the south and southwest provinces. Many studies have found a strong association between the incidence of HFMD and climatic factors such as temperature, rainfall, and relative humidity. However, few studies have analyzed cluster effects between various geographical units. Methods The nonlinear relationships and lag effects between weekly HFMD cases and climatic variables were estimated for the period of 2008–2013 using a polynomial distributed lag model. The extra-Poisson multilevel spatial polynomial model was used to model the exact relationship between weekly HFMD incidence and climatic variables after considering cluster effects, provincial correlated structure of HFMD incidence and overdispersion. The smoothing spline methods were used to detect threshold effects between climatic factors and HFMD incidence. Results The HFMD incidence spatial heterogeneity distributed among provinces, and the scale measurement of overdispersion was 548.077. After controlling for long-term trends, spatial heterogeneity and overdispersion, temperature was highly associated with HFMD incidence. Weekly average temperature and weekly temperature difference approximate inverse “V” shape and “V” shape relationships associated with HFMD incidence. The lag effects for weekly average temperature and weekly temperature difference were 3 weeks and 2 weeks. High spatial correlated HFMD incidence were detected in northern, central and southern province. Temperature can be used to explain most of variation of HFMD incidence in southern and northeastern provinces. After adjustment for temperature, eastern and Northern provinces still had high variation HFMD incidence. Conclusion We found a relatively strong association between weekly HFMD incidence and weekly average temperature. The association between the HFMD incidence and climatic

  3. Mechanical analyses on the digital behaviour of the Tokay gecko (Gekko gecko) based on a multi-level directional adhesion model.

    Science.gov (United States)

    Wu, Xuan; Wang, Xiaojie; Mei, Tao; Sun, Shaoming

    2015-07-08

    This paper proposes a multi-level hierarchical model for the Tokay gecko ( Gekko gecko ) adhesive system and analyses the digital behaviour of the G. gecko under macro/meso-level scale. The model describes the structures of G. gecko 's adhesive system from the nano-level spatulae to the sub-millimetre-level lamella. The G. gecko 's seta is modelled using inextensible fibril based on Euler's elastica theorem. Considering the side contact of the spatular pads of the seta on the flat and rigid substrate, the directional adhesion behaviour of the seta has been investigated. The lamella-induced attachment and detachment have been modelled to simulate the active digital hyperextension (DH) and the digital gripping (DG) phenomena. The results suggest that a tiny angular displacement within 0.25° of the lamellar proximal end is necessary in which a fast transition from attachment to detachment or vice versa is induced. The active DH helps release the torque to induce setal non-sliding detachment, while the DG helps apply torque to make the setal adhesion stable. The lamella plays a key role in saving energy during detachment to adapt to its habitat and provides another adhesive function which differs from the friction-dependent setal adhesion system controlled by the dynamic of G. gecko 's body.

  4. A multi-band, multi-level, multi-electron model for efficient FDTD simulations of electromagnetic interactions with semiconductor quantum wells

    Science.gov (United States)

    Ravi, Koustuban; Wang, Qian; Ho, Seng-Tiong

    2015-08-01

    We report a new computational model for simulations of electromagnetic interactions with semiconductor quantum well(s) (SQW) in complex electromagnetic geometries using the finite-difference time-domain method. The presented model is based on an approach of spanning a large number of electron transverse momentum states in each SQW sub-band (multi-band) with a small number of discrete multi-electron states (multi-level, multi-electron). This enables accurate and efficient two-dimensional (2-D) and three-dimensional (3-D) simulations of nanophotonic devices with SQW active media. The model includes the following features: (1) Optically induced interband transitions between various SQW conduction and heavy-hole or light-hole sub-bands are considered. (2) Novel intra sub-band and inter sub-band transition terms are derived to thermalize the electron and hole occupational distributions to the correct Fermi-Dirac distributions. (3) The terms in (2) result in an explicit update scheme which circumvents numerically cumbersome iterative procedures. This significantly augments computational efficiency. (4) Explicit update terms to account for carrier leakage to unconfined states are derived, which thermalize the bulk and SQW populations to a common quasi-equilibrium Fermi-Dirac distribution. (5) Auger recombination and intervalence band absorption are included. The model is validated by comparisons to analytic band-filling calculations, simulations of SQW optical gain spectra, and photonic crystal lasers.

  5. Critical multi-level governance issues of integrated modelling: An example of low-water management in the Adour-Garonne basin (France)

    Science.gov (United States)

    Mazzega, Pierre; Therond, Olivier; Debril, Thomas; March, Hug; Sibertin-Blanc, Christophe; Lardy, Romain; Sant'ana, Daniel

    2014-11-01

    This paper presents the experience gained related to the development of an integrated simulation model of water policy. Within this context, we analyze particular difficulties raised by the inclusion of multi-level governance that assigns the responsibility of individual or collective decision-making to a variety of actors, regarding measures of which the implementation has significant effects toward the sustainability of socio-hydrosystems. Multi-level governance procedures are compared with the potential of model-based impact assessment. Our discussion is illustrated on the basis of the exploitation of the multi-agent platform MAELIA dedicated to the simulation of social, economic and environmental impacts of low-water management in a context of climate and regulatory changes. We focus on three major decision-making processes occurring in the Adour-Garonne basin, France: (i) the participatory development of the Master Scheme for Water Planning and Management (SDAGE) under the auspices of the Water Agency; (ii) the publication of water use restrictions in situations of water scarcity; and (iii) the determination of the abstraction volumes for irrigation and their allocation. The MAELIA platform explicitly takes into account the mode of decision-making when it is framed by a procedure set beforehand, focusing on the actors' participation and on the nature and parameters of the measures to be implemented. It is observed that in some water organizations decision-making follows patterns that can be represented as rule-based actions triggered by thresholds of resource states. When decisions are resulting from individual choice, endowing virtual agents with bounded rationality allows us to reproduce (in silico) their behavior and decisions in a reliable way. However, the negotiation processes taking place during the period of time simulated by the models in arenas of collective choices are not all reproducible. Outcomes of some collective decisions are very little or

  6. Culture Matters in Successful Curriculum Change: An International Study of the Influence of National and Organizational Culture Tested With Multilevel Structural Equation Modeling.

    Science.gov (United States)

    Jippes, Mariëlle; Driessen, Erik W; Broers, Nick J; Majoor, Gerard D; Gijselaers, Wim H; van der Vleuten, Cees P M

    2015-07-01

    National culture has been shown to play a role in curriculum change in medical schools, and business literature has described a similar influence of organizational culture on change processes in organizations. This study investigated the impact of both national and organizational culture on successful curriculum change in medical schools internationally. The authors tested a literature-based conceptual model using multilevel structural equation modeling. For the operationalization of national and organizational culture, the authors used Hofstede's dimensions of culture and Quinn and Spreitzer's competing values framework, respectively. To operationalize successful curriculum change, the authors used two derivates: medical schools' organizational readiness for curriculum change developed by Jippes and colleagues, and change-related behavior developed by Herscovitch and Meyer. The authors administered a questionnaire in 2012 measuring the described operationalizations to medical schools in the process of changing their curriculum. Nine hundred ninety-one of 1,073 invited staff members from 131 of 345 medical schools in 56 of 80 countries completed the questionnaire. An initial poor fit of the model improved to a reasonable fit by two suggested modifications which seemed theoretically plausible. In sum, characteristics of national culture and organizational culture, such as a certain level of risk taking, flexible policies and procedures, and strong leadership, affected successful curriculum change. National and organizational culture influence readiness for change in medical schools. Therefore, medical schools considering curriculum reform should anticipate the potential impact of national and organizational culture.

  7. The Effects of Educational Diversity in a National Sample of Law Students: Fitting Multilevel Latent Variable Models in Data With Categorical Indicators.

    Science.gov (United States)

    Gottfredson, Nisha C; Panter, A T; Daye, Charles E; Allen, Walter F; Wightman, Linda F

    2009-01-01

    Controversy surrounding the use of race-conscious admissions can be partially resolved with improved empirical knowledge of the effects of racial diversity in educational settings. We use a national sample of law students nested in 64 law schools to test the complex and largely untested theory regarding the effects of educational diversity on student outcomes. Social scientists who study these outcomes frequently encounter both latent variables and nested data within a single analysis. Yet, until recently, an appropriate modeling technique has been computationally infeasible, and consequently few applied researchers have estimated appropriate models to test their theories, sometimes limiting the scope of their research question. Our results, based on disaggregated multilevel structural equation models, show that racial diversity is related to a reduction in prejudiced attitudes and increased perceived exposure to diverse ideas and that these effects are mediated by more frequent interpersonal contact with diverse peers. These findings provide support for the idea that administrative manipulation of educational diversity may lead to improved student outcomes. Admitting a racially/ethnically diverse student body provides an educational experience that encourages increased exposure to diverse ideas and belief systems.

  8. Multilevel eEmpirical Bayes modeling for improved estimation of toxicant formulations tosuppress parasitic sea lamprey in the Upper Great Lakes

    Science.gov (United States)

    Hatfield, Laura A.; Gutreuter, Steve; Boogaard, Michael A.; Carlin, Bradley P.

    2011-01-01

    Estimation of extreme quantal-response statistics, such as the concentration required to kill 99.9% of test subjects (LC99.9), remains a challenge in the presence of multiple covariates and complex study designs. Accurate and precise estimates of the LC99.9 for mixtures of toxicants are critical to ongoing control of a parasitic invasive species, the sea lamprey, in the Laurentian Great Lakes of North America. The toxicity of those chemicals is affected by local and temporal variations in water chemistry, which must be incorporated into the modeling. We develop multilevel empirical Bayes models for data from multiple laboratory studies. Our approach yields more accurate and precise estimation of the LC99.9 compared to alternative models considered. This study demonstrates that properly incorporating hierarchical structure in laboratory data yields better estimates of LC99.9 stream treatment values that are critical to larvae control in the field. In addition, out-of-sample prediction of the results of in situ tests reveals the presence of a latent seasonal effect not manifest in the laboratory studies, suggesting avenues for future study and illustrating the importance of dual consideration of both experimental and observational data.

  9. "Does anger regulation mediate the discrimination-mental health link among Mexican-origin adolescents? A longitudinal mediation analysis using multilevel modeling": Correction to Park et al. (2016).

    Science.gov (United States)

    2017-02-01

    Reports an error in "Does Anger Regulation Mediate the Discrimination-Mental Health Link Among Mexican-Origin Adolescents? A Longitudinal Mediation Analysis Using Multilevel Modeling" by Irene J. K. Park, Lijuan Wang, David R. Williams and Margarita Alegría ( Developmental Psychology , Advanced Online Publication, Nov 28, 2016, np). In the article, there were several typographical errors in the Recruitment and Procedures section. The percentage of mothers who responded to survey items should have been 99.3%. Additionally, the youths surveyed at T2 and T3 should have been n=246 . Accordingly, the percentage of youths surveyed in T2 and T3 should have been 91.4% and the percentage of mothers surveyed at T2 and T3 should have been 90.7%. Finally, the youths missing at T2 should have been n= 23, and therefore the attrition rate for youth participants should have been 8.6. All versions of this article have been corrected. (The following abstract of the original article appeared in record 2016-57671-001.) Although prior research has consistently documented the association between racial/ethnic discrimination and poor mental health outcomes, the mechanisms that underlie this link are still unclear. The present 3-wave longitudinal study tested the mediating role of anger regulation in the discrimination-mental health link among 269 Mexican-origin adolescents ( M age = 14.1 years, SD = 1.6; 57% girls), 12 to 17 years old. Three competing anger regulation variables were tested as potential mediators: outward anger expression, anger suppression, and anger control. Longitudinal mediation analyses were conducted using multilevel modeling that disaggregated within-person effects from between-person effects. Results indicated that outward anger expression was a significant mediator; anger suppression and anger control were not significant mediators. Within a given individual, greater racial/ethnic discrimination was associated with more frequent outward anger expression. In turn

  10. Multilevel model to estimate county-level untreated dental caries among US children aged 6-9years using the National Health and Nutrition Examination Survey.

    Science.gov (United States)

    Lin, Mei; Zhang, Xingyou; Holt, James B; Robison, Valerie; Li, Chien-Hsun; Griffin, Susan O

    2018-06-01

    Because conducting population-based oral health screening is resource intensive, oral health data at small-area levels (e.g., county-level) are not commonly available. We applied the multilevel logistic regression and poststratification method to estimate county-level prevalence of untreated dental caries among children aged 6-9years in the United States using data from the National Health and Nutrition Examination Survey (NHANES) 2005-2010 linked with various area-level data at census tract, county and state levels. We validated model-based national estimates against direct estimates from NHANES. We also compared model-based estimates with direct estimates from select State Oral Health Surveys (SOHS) at state and county levels. The model with individual-level covariates only and the model with individual-, census tract- and county-level covariates explained 7.2% and 96.3% respectively of overall county-level variation in untreated caries. Model-based county-level prevalence estimates ranged from 4.9% to 65.2% with median of 22.1%. The model-based national estimate (19.9%) matched the NHANES direct estimate (19.8%). We found significantly positive correlations between model-based estimates for 8-year-olds and direct estimates from the third-grade State Oral Health Surveys (SOHS) at state level for 34 states (Pearson coefficient: 0.54, P=0.001) and SOHS estimates at county level for 53 New York counties (Pearson coefficient: 0.38, P=0.006). This methodology could be a useful tool to characterize county-level disparities in untreated dental caries among children aged 6-9years and complement oral health surveillance to inform public health programs especially when local-level data are not available although the lack of external validation due to data unavailability should be acknowledged. Published by Elsevier Inc.

  11. Towards the development of multilevel-multiagent diagnostic aids

    International Nuclear Information System (INIS)

    Stratton, R.C.; Jarrell, D.B.

    1991-10-01

    Presented here is our methodology for developing automated aids for diagnosing faults in complex systems. We have designed these aids as multilevel-multiagent diagnostic aids based on principles that should be generally applicable to any complex system. In this methodology, ''multilevel'' refers to information models described at successful levels of abstraction that are tied together in such a way that reasoning is directed to the appropriate level as determined by the problem solving requirements. The concept of ''multiagent'' refers to the method of information processing within the multilevel model network; each model in the network is an independent information processor, i.e., an intelligent agent. 19 refs., 15 figs., 9 tabs

  12. Impact of high-performance work systems on individual- and branch-level performance: test of a multilevel model of intermediate linkages.

    Science.gov (United States)

    Aryee, Samuel; Walumbwa, Fred O; Seidu, Emmanuel Y M; Otaye, Lilian E

    2012-03-01

    We proposed and tested a multilevel model, underpinned by empowerment theory, that examines the processes linking high-performance work systems (HPWS) and performance outcomes at the individual and organizational levels of analyses. Data were obtained from 37 branches of 2 banking institutions in Ghana. Results of hierarchical regression analysis revealed that branch-level HPWS relates to empowerment climate. Additionally, results of hierarchical linear modeling that examined the hypothesized cross-level relationships revealed 3 salient findings. First, experienced HPWS and empowerment climate partially mediate the influence of branch-level HPWS on psychological empowerment. Second, psychological empowerment partially mediates the influence of empowerment climate and experienced HPWS on service performance. Third, service orientation moderates the psychological empowerment-service performance relationship such that the relationship is stronger for those high rather than low in service orientation. Last, ordinary least squares regression results revealed that branch-level HPWS influences branch-level market performance through cross-level and individual-level influences on service performance that emerges at the branch level as aggregated service performance.

  13. Multilevel particle filter

    KAUST Repository

    Law, Kody

    2016-01-06

    This talk will pertain to the filtering of partially observed diffusions, with discrete-time observations. It is assumed that only biased approximations of the diffusion can be obtained, for choice of an accuracy parameter indexed by l. A multilevel estimator is proposed, consisting of a telescopic sum of increment estimators associated to the successive levels. The work associated to O( 2) mean-square error between the multilevel estimator and average with respect to the filtering distribution is shown to scale optimally, for example as O( 2) for optimal rates of convergence of the underlying diffusion approximation. The method is illustrated on some toy examples as well as estimation of interest rate based on real S&P 500 stock price data.

  14. Hydrological response to dynamical downscaling of climate model outputs: A case study for western and eastern snowmelt-dominated Canada catchments

    OpenAIRE

    Magali Troin; Daniel Caya; Juan Alberto Velázquez; François Brissette

    2015-01-01

    Study region: An analysis of hydrological response to a dynamically downscaled multi-member multi-model global climate model (GCM) ensemble of simulations based on the Canadian Regional Climate Model (CRCM) is presented for three snowmelt-dominated basins in Canada. The basins are situated in the western mountainous (British Columbia) and eastern level (Quebec) regions in Canada, providing comprehensive experiments to validate the CRCM over various topographic features. Study focus: The ev...

  15. Multilevel ensemble Kalman filtering

    KAUST Repository

    Hoel, Haakon

    2016-01-08

    The ensemble Kalman filter (EnKF) is a sequential filtering method that uses an ensemble of particle paths to estimate the means and covariances required by the Kalman filter by the use of sample moments, i.e., the Monte Carlo method. EnKF is often both robust and efficient, but its performance may suffer in settings where the computational cost of accurate simulations of particles is high. The multilevel Monte Carlo method (MLMC) is an extension of classical Monte Carlo methods which by sampling stochastic realizations on a hierarchy of resolutions may reduce the computational cost of moment approximations by orders of magnitude. In this work we have combined the ideas of MLMC and EnKF to construct the multilevel ensemble Kalman filter (MLEnKF) for the setting of finite dimensional state and observation spaces. The main ideas of this method is to compute particle paths on a hierarchy of resolutions and to apply multilevel estimators on the ensemble hierarchy of particles to compute Kalman filter means and covariances. Theoretical results and a numerical study of the performance gains of MLEnKF over EnKF will be presented. Some ideas on the extension of MLEnKF to settings with infinite dimensional state spaces will also be presented.

  16. Multilevel ensemble Kalman filtering

    KAUST Repository

    Hoel, Haakon; Chernov, Alexey; Law, Kody; Nobile, Fabio; Tempone, Raul

    2016-01-01

    The ensemble Kalman filter (EnKF) is a sequential filtering method that uses an ensemble of particle paths to estimate the means and covariances required by the Kalman filter by the use of sample moments, i.e., the Monte Carlo method. EnKF is often both robust and efficient, but its performance may suffer in settings where the computational cost of accurate simulations of particles is high. The multilevel Monte Carlo method (MLMC) is an extension of classical Monte Carlo methods which by sampling stochastic realizations on a hierarchy of resolutions may reduce the computational cost of moment approximations by orders of magnitude. In this work we have combined the ideas of MLMC and EnKF to construct the multilevel ensemble Kalman filter (MLEnKF) for the setting of finite dimensional state and observation spaces. The main ideas of this method is to compute particle paths on a hierarchy of resolutions and to apply multilevel estimators on the ensemble hierarchy of particles to compute Kalman filter means and covariances. Theoretical results and a numerical study of the performance gains of MLEnKF over EnKF will be presented. Some ideas on the extension of MLEnKF to settings with infinite dimensional state spaces will also be presented.

  17. Socio-economic development and emotion-health connection revisited: a multilevel modeling analysis using data from 162 counties in China.

    Science.gov (United States)

    Yu, Zonghuo; Wang, Fei

    2016-03-12

    Substantial research has shown that emotions play a critical role in physical health. However, most of these studies were conducted in industrialized countries, and it is still an open question whether the emotion-health connection is a "first-world problem". In the current study, we examined socio-economic development's influence on emotion-health connection by performing multilevel-modeling analysis in a dataset of 33,600 individuals from 162 counties in China. Results showed that both positive emotions and negative emotions predicted level of physical health and regional Gross Domestic Product Per Capita (GDPPC) had some impact on the association between emotion and health through accessibility of medical resources and educational status. But these impacts were suppressed, and the total effects of GDPPC on emotion-health connections were not significant. These results support the universality of emotion-health connection across levels of GDPPC and provide new insight into how socio-economic development might affect these connections.

  18. High school and college biology: A multi-level model of the effects of high school biology courses on student academic performance in introductory college biology courses

    Science.gov (United States)

    Loehr, John Francis

    The issue of student preparation for college study in science has been an ongoing concern for both college-bound students and educators of various levels. This study uses a national sample of college students enrolled in introductory biology courses to address the relationship between high school biology preparation and subsequent introductory college biology performance. Multi-Level Modeling was used to investigate the relationship between students' high school science and mathematics experiences and college biology performance. This analysis controls for student demographic and educational background factors along with factors associated with the college or university attended. The results indicated that high school course-taking and science instructional experiences have the largest impact on student achievement in the first introductory college biology course. In particular, enrollment in courses, such as high school Calculus and Advanced Placement (AP) Biology, along with biology course content that focuses on developing a deep understanding of the topics is found to be positively associated with student achievement in introductory college biology. On the other hand, experiencing high numbers of laboratory activities, demonstrations, and independent projects along with higher levels of laboratory freedom are associated with negative achievement. These findings are relevant to high school biology teachers, college students, their parents, and educators looking beyond the goal of high school graduation.

  19. Longitudinal multilevel models of the big-fish-little-pond effect on academic self-concept: counterbalancing contrast and reflected-glory effects in Hong Kong schools.

    Science.gov (United States)

    Marsh, H W; Kong, C K; Hau, K T

    2000-02-01

    Longitudinal multilevel path models (7,997 students, 44 high schools, 4 years) evaluated effects of school-average achievement and perceived school status on academic self-concept in Hong Kong, which has a collectivist culture with a highly achievement-segregated high school system. Consistent with a priori predictions based on the big-fish-little-pond effect (BFLPE), higher school-average achievements led to lower academic self-concepts (contrast effect), whereas higher perceived school status had a counterbalancing positive effect on self-concept (reflected-glory, assimilation effect). The negative BFLPE is the net effect of counterbalancing influences, stronger negative contrast effects, and weaker positive assimilation effects so that controlling perceived school status led to purer--and even more negative--contrast effects. Attending a school where school-average achievement is high simultaneously resulted in a more demanding basis of comparison for one's own accomplishments (the stronger negative contrast effect) and a source of pride (the weaker positive assimilation effect).

  20. Theoretical basal Ca II fluxes for late-type stars: results from magnetic wave models with time-dependent ionization and multi-level radiation treatments

    Science.gov (United States)

    Fawzy, Diaa E.; Stȩpień, K.

    2018-03-01

    In the current study we present ab initio numerical computations of the generation and propagation of longitudinal waves in magnetic flux tubes embedded in the atmospheres of late-type stars. The interaction between convective turbulence and the magnetic structure is computed and the obtained longitudinal wave energy flux is used in a self-consistent manner to excite the small-scale magnetic flux tubes. In the current study we reduce the number of assumptions made in our previous studies by considering the full magnetic wave energy fluxes and spectra as well as time-dependent ionization (TDI) of hydrogen, employing multi-level Ca II atomic models, and taking into account departures from local thermodynamic equilibrium. Our models employ the recently confirmed value of the mixing-length parameter α=1.8. Regions with strong magnetic fields (magnetic filling factors of up to 50%) are also considered in the current study. The computed Ca II emission fluxes show a strong dependence on the magnetic filling factors, and the effect of time-dependent ionization (TDI) turns out to be very important in the atmospheres of late-type stars heated by acoustic and magnetic waves. The emitted Ca II fluxes with TDI included into the model are decreased by factors that range from 1.4 to 5.5 for G0V and M0V stars, respectively, compared to models that do not consider TDI. The results of our computations are compared with observations. Excellent agreement between the observed and predicted basal flux is obtained. The predicted trend of Ca II emission flux with magnetic filling factor and stellar surface temperature also agrees well with the observations but the calculated maximum fluxes for stars of different spectral types are about two times lower than observations. Though the longitudinal MHD waves considered here are important for chromosphere heating in high activity stars, additional heating mechanism(s) are apparently present.

  1. Bayesian Optimal Experimental Design Using Multilevel Monte Carlo

    KAUST Repository

    Ben Issaid, Chaouki

    2015-01-01

    informative data about the model parameters. One of the major difficulties in evaluating the expected information gain is that it naturally involves nested integration over a possibly high dimensional domain. We use the Multilevel Monte Carlo (MLMC) method

  2. The Relationship among School Safety, School Liking, and Students' Self-Esteem: Based on a Multilevel Mediation Model

    Science.gov (United States)

    Zhang, Xinghui; Xuan, Xin; Chen, Fumei; Zhang, Cai; Luo, Yuhan; Wang, Yun

    2016-01-01

    Background: Perceptions of school safety have an important effect on students' development. Based on the model of "context-process-outcomes," we examined school safety as a context variable to explore how school safety at the school level affected students' self-esteem. Methods: We used hierarchical linear modeling to examine the link…

  3. The Misspecification of the Covariance Structures in Multilevel Models for Single-Case Data: A Monte Carlo Simulation Study

    Science.gov (United States)

    Moeyaert, Mariola; Ugille, Maaike; Ferron, John M.; Beretvas, S. Natasha; Van den Noortgate, Wim

    2016-01-01

    The impact of misspecifying covariance matrices at the second and third levels of the three-level model is evaluated. Results indicate that ignoring existing covariance has no effect on the treatment effect estimate. In addition, the between-case variance estimates are unbiased when covariance is either modeled or ignored. If the research interest…

  4. Simulation-based evaluation of the performance of the F test in a linear multilevel model setting with sparseness at the level of the primary unit.

    Science.gov (United States)

    Bruyndonckx, Robin; Aerts, Marc; Hens, Niel

    2016-09-01

    In a linear multilevel model, significance of all fixed effects can be determined using F tests under maximum likelihood (ML) or restricted maximum likelihood (REML). In this paper, we demonstrate that in the presence of primary unit sparseness, the performance of the F test under both REML and ML is rather poor. Using simulations based on the structure of a data example on ceftriaxone consumption in hospitalized children, we studied variability, type I error rate and power in scenarios with a varying number of secondary units within the primary units. In general, the variability in the estimates for the effect of the primary unit decreased as the number of secondary units increased. In the presence of singletons (i.e., only one secondary unit within a primary unit), REML consistently outperformed ML, although even under REML the performance of the F test was found inadequate. When modeling the primary unit as a random effect, the power was lower while the type I error rate was unstable. The options of dropping, regrouping, or splitting the singletons could solve either the problem of a high type I error rate or a low power, while worsening the other. The permutation test appeared to be a valid alternative as it outperformed the F test, especially under REML. We conclude that in the presence of singletons, one should be careful in using the F test to determine the significance of the fixed effects, and propose the permutation test (under REML) as an alternative. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  5. Multilevel risk factors and developmental assets for internalizing symptoms and self-esteem in disadvantaged adolescents: modeling longitudinal trajectories from the Rural Adaptation Project.

    Science.gov (United States)

    Smokowski, Paul R; Guo, Shenyang; Rose, Roderick; Evans, Caroline B R; Cotter, Katie L; Bacallao, Martica

    2014-11-01

    The current study filled significant gaps in our knowledge of developmental psychopathology by examining the influence of multilevel risk factors and developmental assets on longitudinal trajectories of internalizing symptoms and self-esteem in an exceptionally culturally diverse sample of rural adolescents. Integrating ecological and social capital theories, we explored if positive microsystem transactions are associated with self-esteem while negative microsystem transactions increase the chances of internalizing problems. Data came from the Rural Adaptation Project, a 5-year longitudinal panel study of more than 4,000 middle school students from 28 public schools in two rural, disadvantaged counties in North Carolina. Three-level hierarchical linear modeling models were estimated to predict internalizing symptoms (e.g., depression, anxiety) and self-esteem. Relative to other students, risk for internalizing problems and low self-esteem was elevated for aggressive adolescents, students who were hassled or bullied at school, and those who were rejected by peers or in conflict with their parents. Internalizing problems were also more common among adolescents from socioeconomically disadvantaged families and neighborhoods, among those in schools with more suspensions, in students who reported being pressured by peers, and in youth who required more teacher support. It is likely that these experiences left adolescents disengaged from developing social capital from ecological microsystems (e.g., family, school, peers). On the positive side, support from parents and friends and optimism about the future were key assets associated with lower internalizing symptoms and higher self-esteem. Self-esteem was also positively related to religious orientation, school satisfaction, and future optimism. These variables show active engagement with ecological microsystems. The implications and limitations were discussed.

  6. Modelization of three-dimensional bone micro-architecture using Markov random fields with a multi-level clique system

    International Nuclear Information System (INIS)

    Lamotte, T.; Dinten, J.M.; Peyrin, F.

    2004-01-01

    Imaging trabecular bone micro-architecture in vivo non-invasively is still a challenging issue due to the complexity and small size of the structure. Thus, having a realistic 3D model of bone micro-architecture could be useful in image segmentation or image reconstruction. The goal of this work was to develop a 3D model of trabecular bone micro-architecture which can be seen as a problem of texture synthesis. We investigated a statistical model based on 3D Markov Random Fields (MRF's). Due to the Hammersley-Clifford theorem MRF's may equivalently be defined by an energy function on some set of cliques. In order to model 3D binary bone texture images (bone / background), we first used a particular well-known subclass of MRFs: the Ising model. The local energy function at some voxel depends on the closest neighbors of the voxels and on some parameters which control the shape and the proportion of bone. However, simulations yielded textures organized as connected clusters which even when varying the parameters did not approach the complexity of bone micro-architecture. Then, we introduced a second level of cliques taking into account neighbors located at some distance d from the site s and a new set of cliques allowing to control the plate thickness and spacing. The 3D bone texture images generated using the proposed model were analyzed using the usual bone-architecture quantification tools in order to relate the parameters of the MRF model to the characteristic parameters of bone micro-architecture (trabecular spacing, trabecular thickness, number of trabeculae...). (authors)

  7. Marginalized multilevel hurdle and zero-inflated models for overdispersed and correlated count data with excess zeros.

    Science.gov (United States)

    Kassahun, Wondwosen; Neyens, Thomas; Molenberghs, Geert; Faes, Christel; Verbeke, Geert

    2014-11-10

    Count data are collected repeatedly over time in many applications, such as biology, epidemiology, and public health. Such data are often characterized by the following three features. First, correlation due to the repeated measures is usually accounted for using subject-specific random effects, which are assumed to be normally distributed. Second, the sample variance may exceed the mean, and hence, the theoretical mean-variance relationship is violated, leading to overdispersion. This is usually allowed for based on a hierarchical approach, combining a Poisson model with gamma distributed random effects. Third, an excess of zeros beyond what standard count distributions can predict is often handled by either the hurdle or the zero-inflated model. A zero-inflated model assumes two processes as sources of zeros and combines a count distribution with a discrete point mass as a mixture, while the hurdle model separately handles zero observations and positive counts, where then a truncated-at-zero count distribution is used for the non-zero state. In practice, however, all these three features can appear simultaneously. Hence, a modeling framework that incorporates all three is necessary, and this presents challenges for the data analysis. Such models, when conditionally specified, will naturally have a subject-specific interpretation. However, adopting their purposefully modified marginalized versions leads to a direct marginal or population-averaged interpretation for parameter estimates of covariate effects, which is the primary interest in many applications. In this paper, we present a marginalized hurdle model and a marginalized zero-inflated model for correlated and overdispersed count data with excess zero observations and then illustrate these further with two case studies. The first dataset focuses on the Anopheles mosquito density around a hydroelectric dam, while adolescents' involvement in work, to earn money and support their families or themselves, is

  8. A GPU based high-resolution multilevel biomechanical head and neck model for validating deformable image registration

    International Nuclear Information System (INIS)

    Neylon, J.; Qi, X.; Sheng, K.; Low, D. A.; Kupelian, P.; Santhanam, A.; Staton, R.; Pukala, J.; Manon, R.

    2015-01-01

    Purpose: Validating the usage of deformable image registration (DIR) for daily patient positioning is critical for adaptive radiotherapy (RT) applications pertaining to head and neck (HN) radiotherapy. The authors present a methodology for generating biomechanically realistic ground-truth data for validating DIR algorithms for HN anatomy by (a) developing a high-resolution deformable biomechanical HN model from a planning CT, (b) simulating deformations for a range of interfraction posture changes and physiological regression, and (c) generating subsequent CT images representing the deformed anatomy. Methods: The biomechanical model was developed using HN kVCT datasets and the corresponding structure contours. The voxels inside a given 3D contour boundary were clustered using a graphics processing unit (GPU) based algorithm that accounted for inconsistencies and gaps in the boundary to form a volumetric structure. While the bony anatomy was modeled as rigid body, the muscle and soft tissue structures were modeled as mass–spring-damper models with elastic material properties that corresponded to the underlying contoured anatomies. Within a given muscle structure, the voxels were classified using a uniform grid and a normalized mass was assigned to each voxel based on its Hounsfield number. The soft tissue deformation for a given skeletal actuation was performed using an implicit Euler integration with each iteration split into two substeps: one for the muscle structures and the other for the remaining soft tissues. Posture changes were simulated by articulating the skeletal structure and enabling the soft structures to deform accordingly. Physiological changes representing tumor regression were simulated by reducing the target volume and enabling the surrounding soft structures to deform accordingly. Finally, the authors also discuss a new approach to generate kVCT images representing the deformed anatomy that accounts for gaps and antialiasing artifacts that may

  9. A GPU based high-resolution multilevel biomechanical head and neck model for validating deformable image registration

    Energy Technology Data Exchange (ETDEWEB)

    Neylon, J., E-mail: jneylon@mednet.ucla.edu; Qi, X.; Sheng, K.; Low, D. A.; Kupelian, P.; Santhanam, A. [Department of Radiation Oncology, University of California Los Angeles, 200 Medical Plaza, #B265, Los Angeles, California 90095 (United States); Staton, R.; Pukala, J.; Manon, R. [Department of Radiation Oncology, M.D. Anderson Cancer Center, Orlando, 1440 South Orange Avenue, Orlando, Florida 32808 (United States)

    2015-01-15

    Purpose: Validating the usage of deformable image registration (DIR) for daily patient positioning is critical for adaptive radiotherapy (RT) applications pertaining to head and neck (HN) radiotherapy. The authors present a methodology for generating biomechanically realistic ground-truth data for validating DIR algorithms for HN anatomy by (a) developing a high-resolution deformable biomechanical HN model from a planning CT, (b) simulating deformations for a range of interfraction posture changes and physiological regression, and (c) generating subsequent CT images representing the deformed anatomy. Methods: The biomechanical model was developed using HN kVCT datasets and the corresponding structure contours. The voxels inside a given 3D contour boundary were clustered using a graphics processing unit (GPU) based algorithm that accounted for inconsistencies and gaps in the boundary to form a volumetric structure. While the bony anatomy was modeled as rigid body, the muscle and soft tissue structures were modeled as mass–spring-damper models with elastic material properties that corresponded to the underlying contoured anatomies. Within a given muscle structure, the voxels were classified using a uniform grid and a normalized mass was assigned to each voxel based on its Hounsfield number. The soft tissue deformation for a given skeletal actuation was performed using an implicit Euler integration with each iteration split into two substeps: one for the muscle structures and the other for the remaining soft tissues. Posture changes were simulated by articulating the skeletal structure and enabling the soft structures to deform accordingly. Physiological changes representing tumor regression were simulated by reducing the target volume and enabling the surrounding soft structures to deform accordingly. Finally, the authors also discuss a new approach to generate kVCT images representing the deformed anatomy that accounts for gaps and antialiasing artifacts that may

  10. Simultaneous inference for multilevel linear mixed models - with an application to a large-scale school meal study

    DEFF Research Database (Denmark)

    Ritz, Christian; Laursen, Rikke Pilmann; Damsgaard, Camilla Trab

    2017-01-01

    of a school meal programme. We propose a novel and versatile framework for simultaneous inference on parameters estimated from linear mixed models that were fitted separately for several outcomes from the same study, but did not necessarily contain the same fixed or random effects. By combining asymptotic...... sizes of practical relevance we studied simultaneous coverage through simulation, which showed that the approach achieved acceptable coverage probabilities even for small sample sizes (10 clusters) and for 2–16 outcomes. The approach also compared favourably with a joint modelling approach. We also...

  11. An improved model for surround suppression by steerable filters and multilevel inhibition with application to contour detection

    NARCIS (Netherlands)

    Papari, Giuseppe; Petkov, Nicolai

    Psychophysical and neurophysiological evidence about the human visual system shows the existence of a mechanism, called surround suppression, which inhibits the response of an edge in the presence of other similar edges in the surroundings. A simple computational model of this phenomenon has been

  12. The use of multilevel models to evaluate sources of variation in reproductive performance in dairy cattle in Reunion Island

    DEFF Research Database (Denmark)

    Dohoo, I.R.; Tillard, E.; Stryhn, H.

    2001-01-01

    %, respectively) - but for the other two parameters (first-service-conception risk and first-service-to-conception interval), >90% of the variation resided at the lactation level. For the three continuous dependent variables, comparison of results between models based on log-transformed data and Box-Cox-transformed...

  13. Multilevel Deficiency of White Matter Connectivity Networks in Alzheimer's Disease: A Diffusion MRI Study with DTI and HARDI Models.

    Science.gov (United States)

    Wang, Tao; Shi, Feng; Jin, Yan; Yap, Pew-Thian; Wee, Chong-Yaw; Zhang, Jianye; Yang, Cece; Li, Xia; Xiao, Shifu; Shen, Dinggang

    2016-01-01

    Alzheimer's disease (AD) is the most common form of dementia in elderly people. It is an irreversible and progressive brain disease. In this paper, we utilized diffusion-weighted imaging (DWI) to detect abnormal topological organization of white matter (WM) structural networks. We compared the differences between WM connectivity characteristics at global, regional, and local levels in 26 patients with probable AD and 16 normal control (NC) elderly subjects, using connectivity networks constructed with the diffusion tensor imaging (DTI) model and the high angular resolution diffusion imaging (HARDI) model, respectively. At the global level, we found that the WM structural networks of both AD and NC groups had a small-world topology; however, the AD group showed a significant decrease in both global and local efficiency, but an increase in clustering coefficient and the average shortest path length. We further found that the AD patients had significantly decreased nodal efficiency at the regional level, as well as weaker connections in multiple local cortical and subcortical regions, such as precuneus, temporal lobe, hippocampus, and thalamus. The HARDI model was found to be more advantageous than the DTI model, as it was more sensitive to the deficiencies in AD at all of the three levels.

  14. The impact of individual and organisational factors on engagement of individuals with intellectual disability living in community group homes: a multilevel model.

    Science.gov (United States)

    Qian, X; Tichá, R; Larson, S A; Stancliffe, R J; Wuorio, A

    2015-06-01

    Being engaged in daily activities is a strong indicator of quality of life for individuals with intellectual disability (ID) who live in small community group homes. This study aimed to identify individual and organisational factors that predict high levels of engagement. Individuals with ID (n = 78), direct support professionals (DSPs; n = 174) and supervisors (n = 21) from 21 US group homes participated in the study. For each individual with ID, we conducted 80 min of observation at the person's residence. Information was also gathered regarding demographic characteristics, DSP competence, supervisor years of experience and management practices. Data were analysed using multilevel modelling. On average, individuals were engaged in social activities 12% of observed time and non-social activities 35% of the time. Individuals with greater adaptive skills who were supported by more competent staff showed significantly higher levels of social engagement. Individuals with less severe deficits in adaptive behaviours and less challenging behaviour showed higher levels of non-social engagement. Although none of the factors related to group homes were significant, 24% of the variance in non-social engagement existed among group homes. These results suggested that engagement is a dynamic construct. The extent to which an individual with ID is engaged in daily life is a result of interplay between the individual's characteristics and the group home environment. Future research is needed to investigate the influence of variables specific to the group home on the engagement level of individuals with disabilities. © 2014 MENCAP and International Association of the Scientific Study of Intellectual and Developmental Disabilities and John Wiley & Sons Ltd.

  15. A multilevel model of methicillin-resistant Staphylococcus aureus acquisition within the hierarchy of an Australian tertiary hospital.

    Science.gov (United States)

    Kong, Fiona; Paterson, David L; Coory, Michael; Clements, Archie C A

    2012-11-01

    Hospitals without universal single room accommodations typically contain multibed cubicles within wards. In this study, we examined whether the variation in a patient's risk for acquiring methicillin-resistant Staphylococcus aureus (MRSA) in a major tertiary hospital was greatest at the bed, cubicle, or ward level, and quantified the risk of MRSA acquisition associated with exposure to MRSA-colonized/infected patients within the same bed, cubicle, and ward at differently distributed lag times. Nested tri-level hierarchical logistic regression models with random effects were used for non-multiresistant MRSA (nmMRSA) and multiresistant MRSA (mMRSA). The models were internally validated. Receiver operating characteristic curves were used to compare the models' predictive capability The odds of new nmMRSA acquisition were 6.06-fold (95% credible intervals [CrI], 3.93- to 9.34-fold) greater in bed-weeks when a nmMRSA-colonized/infected patient was in the same cubicle 2 weeks earlier. The odds of mMRSA acquisition were 5.12-fold (95% CrI, 4.02- to 6.51-fold) greater in bed-weeks when a colonized/infected patient was in the same ward 2 weeks earlier. The between-cluster variance was highest at the ward level. Patients were at greater risk if there was a colonized/infected patient in the same cubicle or ward 2 weeks earlier. Our findings indicate that focusing on the relevant cubicles and wards during this high-risk period can help target infection control resources more efficiently. Copyright © 2012 Association for Professionals in Infection Control and Epidemiology, Inc. All rights reserved.

  16. Estimation of Indirect Effects in the Presence of Unmeasured Confounding for the Mediator-Outcome Relationship in a Multilevel 2-1-1 Mediation Model

    Science.gov (United States)

    Talloen, Wouter; Moerkerke, Beatrijs; Loeys, Tom; De Naeghel, Jessie; Van Keer, Hilde; Vansteelandt, Stijn

    2016-01-01

    To assess the direct and indirect effect of an intervention, multilevel 2-1-1 studies with intervention randomized at the upper (class) level and mediator and outcome measured at the lower (student) level are frequently used in educational research. In such studies, the mediation process may flow through the student-level mediator (the within…

  17. Thermomechanical Modeling of the Formation of a Multilevel, Crustal-Scale Magmatic System by the Yellowstone Plume

    Science.gov (United States)

    Colón, D. P.; Bindeman, I. N.; Gerya, T. V.

    2018-05-01

    Geophysical imaging of the Yellowstone supervolcano shows a broad zone of partial melt interrupted by an amagmatic gap at depths of 15-20 km. We reproduce this structure through a series of regional-scale magmatic-thermomechanical forward models which assume that magmatic dikes stall at rheologic discontinuities in the crust. We find that basaltic magmas accumulate at the Moho and at the brittle-ductile transition, which naturally forms at depths of 5-10 km. This leads to the development of a 10- to 15-km thick midcrustal sill complex with a top at a depth of approximately 10 km, consistent with geophysical observations of the pre-Yellowstone hot spot track. We show a linear relationship between melting rates in the mantle and rhyolite eruption rates along the hot spot track. Finally, melt production rates from our models suggest that the Yellowstone plume is 175°C hotter than the surrounding mantle and that the thickness of the overlying lithosphere is 80 km.

  18. Individual and culture-level components of survey response styles: A multi-level analysis using cultural models of selfhood.

    Science.gov (United States)

    Smith, Peter B; Vignoles, Vivian L; Becker, Maja; Owe, Ellinor; Easterbrook, Matthew J; Brown, Rupert; Bourguignon, David; Garðarsdóttir, Ragna B; Kreuzbauer, Robert; Cendales Ayala, Boris; Yuki, Masaki; Zhang, Jianxin; Lv, Shaobo; Chobthamkit, Phatthanakit; Jaafar, Jas Laile; Fischer, Ronald; Milfont, Taciano L; Gavreliuc, Alin; Baguma, Peter; Bond, Michael Harris; Martin, Mariana; Gausel, Nicolay; Schwartz, Seth J; Des Rosiers, Sabrina E; Tatarko, Alexander; González, Roberto; Didier, Nicolas; Carrasco, Diego; Lay, Siugmin; Nizharadze, George; Torres, Ana; Camino, Leoncio; Abuhamdeh, Sami; Macapagal, Ma Elizabeth J; Koller, Silvia H; Herman, Ginette; Courtois, Marie; Fritsche, Immo; Espinosa, Agustín; Villamar, Juan A; Regalia, Camillo; Manzi, Claudia; Brambilla, Maria; Zinkeng, Martina; Jalal, Baland; Kusdil, Ersin; Amponsah, Benjamin; Çağlar, Selinay; Mekonnen, Kassahun Habtamu; Möller, Bettina; Zhang, Xiao; Schweiger Gallo, Inge; Prieto Gil, Paula; Lorente Clemares, Raquel; Campara, Gabriella; Aldhafri, Said; Fülöp, Márta; Pyszczynski, Tom; Kesebir, Pelin; Harb, Charles

    2016-12-01

    Variations in acquiescence and extremity pose substantial threats to the validity of cross-cultural research that relies on survey methods. Individual and cultural correlates of response styles when using 2 contrasting types of response mode were investigated, drawing on data from 55 cultural groups across 33 nations. Using 7 dimensions of self-other relatedness that have often been confounded within the broader distinction between independence and interdependence, our analysis yields more specific understandings of both individual- and culture-level variations in response style. When using a Likert-scale response format, acquiescence is strongest among individuals seeing themselves as similar to others, and where cultural models of selfhood favour harmony, similarity with others and receptiveness to influence. However, when using Schwartz's (2007) portrait-comparison response procedure, acquiescence is strongest among individuals seeing themselves as self-reliant but also connected to others, and where cultural models of selfhood favour self-reliance and self-consistency. Extreme responding varies less between the two types of response modes, and is most prevalent among individuals seeing themselves as self-reliant, and in cultures favouring self-reliance. As both types of response mode elicit distinctive styles of response, it remains important to estimate and control for style effects to ensure valid comparisons. © 2016 International Union of Psychological Science.

  19. Integrating technology, curriculum, and online resources: A multilevel model study of impacts on science teachers and students

    Science.gov (United States)

    Ye, Lei

    This scale-up study investigated the impact of a teacher technology tool (Curriculum Customization Service, CCS), curriculum, and online resources on earth science teachers' attitudes, beliefs, and practices and on students' achievement and engagement with science learning. Participants included 73 teachers and over 2,000 ninth-grade students within five public school districts in the western U.S. To assess the impact on teachers, changes between pre- and postsurveys were examined. Results suggest that the CCS tool appeared to significantly increase both teachers' awareness of other earth science teachers' practices and teachers' frequency of using interactive resources in their lesson planning and classroom teaching. A standard multiple regression model was developed. In addition to "District," "Training condition" (whether or not teachers received CCS training) appeared to predict teachers' attitudes, beliefs, and practices. Teachers who received CCS training tended to have lower postsurvey scores than their peers who had no CCS training. Overall, usage of the CCS tool tended to be low, and there were differences among school districts. To assess the impact on students, changes were examined between pre- and postsurveys of (1) knowledge assessment and (2) students' engagement with science learning. Students showed pre- to postsurvey improvements in knowledge assessment, with small to medium effect sizes. A nesting effect (students clustered within teachers) in the Earth's Dynamic Geosphere (EDG) knowledge assessment was identified and addressed by fitting a two-level hierarchical linear model (HLM). In addition, significant school district differences existed for student post-knowledge assessment scores. On the student engagement questionnaire, students tended to be neutral or to slightly disagree that science learning was important in terms of using science in daily life, stimulating their thinking, discovering science concepts, and satisfying their own

  20. Accurate Mapping of Multilevel Rydberg Atoms on Interacting Spin-1 /2 Particles for the Quantum Simulation of Ising Models

    Science.gov (United States)

    de Léséleuc, Sylvain; Weber, Sebastian; Lienhard, Vincent; Barredo, Daniel; Büchler, Hans Peter; Lahaye, Thierry; Browaeys, Antoine

    2018-03-01

    We study a system of atoms that are laser driven to n D3 /2 Rydberg states and assess how accurately they can be mapped onto spin-1 /2 particles for the quantum simulation of anisotropic Ising magnets. Using nonperturbative calculations of the pair potentials between two atoms in the presence of electric and magnetic fields, we emphasize the importance of a careful selection of experimental parameters in order to maintain the Rydberg blockade and avoid excitation of unwanted Rydberg states. We benchmark these theoretical observations against experiments using two atoms. Finally, we show that in these conditions, the experimental dynamics observed after a quench is in good agreement with numerical simulations of spin-1 /2 Ising models in systems with up to 49 spins, for which numerical simulations become intractable.

  1. A Multilevel Association Model for IT Employees’ Life Stress and Job Satisfaction: An Information Technology (IT Industry Case Study

    Directory of Open Access Journals (Sweden)

    Mehmood Khalid

    2017-01-01

    Full Text Available The aim of this research was to investigate the association among IT employees’ life stress and job satisfaction in information technology (IT firms. Data on 250 IT employees’ in 30 working groups was obtained from 10 Information Technology (IT Chinese firms from Beijing, and analyzed using hierarchical linear modeling (HLM. Results found momentous association among life stress of IT employees’ and their job satisfaction at an individual-level and group-level in IT firms. Furthermore, life stress in Beijing at group-level moderates the association among job satisfaction and IT employees’ life stress at an individual-level. Finally, limitations and implications of the present study are also discussed.

  2. User's guide for SAMMY: a computer model for multilevel r-matrix fits to neutron data using Bayes' equations

    International Nuclear Information System (INIS)

    Larson, N.M.; Perey, F.G.

    1980-11-01

    A method is described for determining the parameters of a model from experimental data based upon the utilization of Bayes' theorem. This method has several advantages over the least-squares method as it is commonly used; one important advantage is that the assumptions under which the parameter values have been determined are more clearly evident than in many results based upon least squares. Bayes' method has been used to develop a computer code which can be utilized to analyze neutron cross-section data by means of the R-matrix theory. The required formulae from the R-matrix theory are presented, and the computer implementation of both Bayes' equations and R-matrix theory is described. Details about the computer code and compelte input/output information are given

  3. Optimal Multi-Level Lot Sizing for Requirements Planning Systems

    OpenAIRE

    Earle Steinberg; H. Albert Napier

    1980-01-01

    The wide spread use of advanced information systems such as Material Requirements Planning (MRP) has significantly altered the practice of dependent demand inventory management. Recent research has focused on development of multi-level lot sizing heuristics for such systems. In this paper, we develop an optimal procedure for the multi-period, multi-product, multi-level lot sizing problem by modeling the system as a constrained generalized network with fixed charge arcs and side constraints. T...

  4. Multi-level modelling of the response of the ultraminiature proportional counter: gas gain phenomena and pulse height spectra

    International Nuclear Information System (INIS)

    Olko, P.; Moutarde, C.; Segur, P.

    1995-01-01

    The ultraminiature proportional counters, UMC, unique radiation detectors for monitoring high intensity therapy fields, designed by Kliauga and operated at Columbia University (USA), have yielded a number of pulse height distributions for photons, neutrons and ions at simulated diameters of 5-50 nm. Monte Carlo calculations of the gas gain in such a counter questioned the possibility of achieving proportionally at such low simulated diameters. The response of the UMC has now been modelled taking into account both fluctuations of energy deposited in the counter volume and its calculated gas gain. Energy deposition was calculated using the MOCA-14, MOCA-8 and TRION codes, whereby distributions of ionisations d(j) after irradiations with 137 Cs, 15 MeV neutrons and 7 MeV.amu -1 deuterons were obtained. Monte Carlo calculations of electron avalanches in UMC show that the size of the single-electron avalanche P(n) reaching the anode depends strongly on the location of the primary ionisation within the counter volume. Distributions of the size of electron avalanches for higher numbers of primary ionisations, P *j (n), were obtained by successive convolutions of P(n). Finally, the counter response was obtained by weighting P *j (n) over d(j) distributions. On comparing the measured and calculated spectra it was concluded that the previously proposed single-electron peak calibration method might not be valid for the UMC due to the excessive width and overlap of electron avalanche distributions. Better agreement between the measured and calculated spectra is found if broader electron avalanche distributions than those used in the present calculations, are assumed. (author)

  5. Multilevel DC link inverter

    Science.gov (United States)

    Su, Gui-Jia

    2003-06-10

    A multilevel DC link inverter and method for improving torque response and current regulation in permanent magnet motors and switched reluctance motors having a low inductance includes a plurality of voltage controlled cells connected in series for applying a resulting dc voltage comprised of one or more incremental dc voltages. The cells are provided with switches for increasing the resulting applied dc voltage as speed and back EMF increase, while limiting the voltage that is applied to the commutation switches to perform PWM or dc voltage stepping functions, so as to limit current ripple in the stator windings below an acceptable level, typically 5%. Several embodiments are disclosed including inverters using IGBT's, inverters using thyristors. All of the inverters are operable in both motoring and regenerating modes.

  6. Totally parallel multilevel algorithms

    Science.gov (United States)

    Frederickson, Paul O.

    1988-01-01

    Four totally parallel algorithms for the solution of a sparse linear system have common characteristics which become quite apparent when they are implemented on a highly parallel hypercube such as the CM2. These four algorithms are Parallel Superconvergent Multigrid (PSMG) of Frederickson and McBryan, Robust Multigrid (RMG) of Hackbusch, the FFT based Spectral Algorithm, and Parallel Cyclic Reduction. In fact, all four can be formulated as particular cases of the same totally parallel multilevel algorithm, which are referred to as TPMA. In certain cases the spectral radius of TPMA is zero, and it is recognized to be a direct algorithm. In many other cases the spectral radius, although not zero, is small enough that a single iteration per timestep keeps the local error within the required tolerance.

  7. Monitoring well utility in a heterogeneous DNAPL source zone area: Insights from proximal multilevel sampler wells and sampling capture-zone modelling.

    Science.gov (United States)

    McMillan, Lindsay A; Rivett, Michael O; Wealthall, Gary P; Zeeb, Peter; Dumble, Peter

    2018-03-01

    Groundwater-quality assessment at contaminated sites often involves the use of short-screen (1.5 to 3 m) monitoring wells. However, even over these intervals considerable variation may occur in contaminant concentrations in groundwater adjacent to the well screen. This is especially true in heterogeneous dense non-aqueous phase liquid (DNAPL) source zones, where cm-scale contamination variability may call into question the effectiveness of monitoring wells to deliver representative data. The utility of monitoring wells in such settings is evaluated by reference to high-resolution multilevel sampler (MLS) wells located proximally to short-screen wells, together with sampling capture-zone modelling to explore controls upon well sample provenance and sensitivity to monitoring protocols. Field data are analysed from the highly instrumented SABRE research site that contained an old trichloroethene source zone within a shallow alluvial aquifer at a UK industrial facility. With increased purging, monitoring-well samples tend to a flow-weighted average concentration but may exhibit sensitivity to the implemented protocol and degree of purging. Formation heterogeneity adjacent to the well-screen particularly, alongside pump-intake position and water level, influence this sensitivity. Purging of low volumes is vulnerable to poor reproducibility arising from concentration variability predicted over the initial 1 to 2 screen volumes purged. Marked heterogeneity may also result in limited long-term sample concentration stabilization. Development of bespoke monitoring protocols, that consider screen volumes purged, alongside water-quality indicator parameter stabilization, is recommended to validate and reduce uncertainty when interpreting monitoring-well data within source zone areas. Generalised recommendations on monitoring well based protocols are also developed. A key monitoring well utility is their proportionately greater sample draw from permeable horizons constituting

  8. Violation of the Sphericity Assumption and Its Effect on Type-I Error Rates in Repeated Measures ANOVA and Multi-Level Linear Models (MLM).

    Science.gov (United States)

    Haverkamp, Nicolas; Beauducel, André

    2017-01-01

    We investigated the effects of violations of the sphericity assumption on Type I error rates for different methodical approaches of repeated measures analysis using a simulation approach. In contrast to previous simulation studies on this topic, up to nine measurement occasions were considered. Effects of the level of inter-correlations between measurement occasions on Type I error rates were considered for the first time. Two populations with non-violation of the sphericity assumption, one with uncorrelated measurement occasions and one with moderately correlated measurement occasions, were generated. One population with violation of the sphericity assumption combines uncorrelated with highly correlated measurement occasions. A second population with violation of the sphericity assumption combines moderately correlated and highly correlated measurement occasions. From these four populations without any between-group effect or within-subject effect 5,000 random samples were drawn. Finally, the mean Type I error rates for Multilevel linear models (MLM) with an unstructured covariance matrix (MLM-UN), MLM with compound-symmetry (MLM-CS) and for repeated measures analysis of variance (rANOVA) models (without correction, with Greenhouse-Geisser-correction, and Huynh-Feldt-correction) were computed. To examine the effect of both the sample size and the number of measurement occasions, sample sizes of n = 20, 40, 60, 80, and 100 were considered as well as measurement occasions of m = 3, 6, and 9. With respect to rANOVA, the results plead for a use of rANOVA with Huynh-Feldt-correction, especially when the sphericity assumption is violated, the sample size is rather small and the number of measurement occasions is large. For MLM-UN, the results illustrate a massive progressive bias for small sample sizes ( n = 20) and m = 6 or more measurement occasions. This effect could not be found in previous simulation studies with a smaller number of measurement occasions. The

  9. Does anger regulation mediate the discrimination-mental health link among Mexican-origin adolescents? A longitudinal mediation analysis using multilevel modeling.

    Science.gov (United States)

    Park, Irene J K; Wang, Lijuan; Williams, David R; Alegría, Margarita

    2017-02-01

    [Correction Notice: An Erratum for this article was reported in Vol 53(2) of Developmental Psychology (see record 2017-04475-001). In the article, there were several typographical errors in the Recruitment and Procedures section. The percentage of mothers who responded to survey items should have been 99.3%. Additionally, the youths surveyed at T2 and T3 should have been n 246. Accordingly, the percentage of youths surveyed in T2 and T3 should have been 91.4% and the percentage of mothers surveyed at T2 and T3 should have been 90.7%. Finally, the youths missing at T2 should have been n 23, and therefore the attrition rate for youth participants should have been 8.6. All versions of this article have been corrected.] Although prior research has consistently documented the association between racial/ethnic discrimination and poor mental health outcomes, the mechanisms that underlie this link are still unclear. The present 3-wave longitudinal study tested the mediating role of anger regulation in the discrimination-mental health link among 269 Mexican-origin adolescents ( M age = 14.1 years, SD = 1.6; 57% girls), 12 to 17 years old. Three competing anger regulation variables were tested as potential mediators: outward anger expression, anger suppression, and anger control. Longitudinal mediation analyses were conducted using multilevel modeling that disaggregated within-person effects from between-person effects. Results indicated that outward anger expression was a significant mediator; anger suppression and anger control were not significant mediators. Within a given individual, greater racial/ethnic discrimination was associated with more frequent outward anger expression. In turn, more frequent outward anger expression was associated with higher levels of anxiety and depression at a given time point. Gender, age, and nativity status were not significant moderators of the hypothesized mediation models. By identifying outward anger expression as an explanatory

  10. Monitoring well utility in a heterogeneous DNAPL source zone area: Insights from proximal multilevel sampler wells and sampling capture-zone modelling

    Science.gov (United States)

    McMillan, Lindsay A.; Rivett, Michael O.; Wealthall, Gary P.; Zeeb, Peter; Dumble, Peter

    2018-03-01

    Groundwater-quality assessment at contaminated sites often involves the use of short-screen (1.5 to 3 m) monitoring wells. However, even over these intervals considerable variation may occur in contaminant concentrations in groundwater adjacent to the well screen. This is especially true in heterogeneous dense non-aqueous phase liquid (DNAPL) source zones, where cm-scale contamination variability may call into question the effectiveness of monitoring wells to deliver representative data. The utility of monitoring wells in such settings is evaluated by reference to high-resolution multilevel sampler (MLS) wells located proximally to short-screen wells, together with sampling capture-zone modelling to explore controls upon well sample provenance and sensitivity to monitoring protocols. Field data are analysed from the highly instrumented SABRE research site that contained an old trichloroethene source zone within a shallow alluvial aquifer at a UK industrial facility. With increased purging, monitoring-well samples tend to a flow-weighted average concentration but may exhibit sensitivity to the implemented protocol and degree of purging. Formation heterogeneity adjacent to the well-screen particularly, alongside pump-intake position and water level, influence this sensitivity. Purging of low volumes is vulnerable to poor reproducibility arising from concentration variability predicted over the initial 1 to 2 screen volumes purged. Marked heterogeneity may also result in limited long-term sample concentration stabilization. Development of bespoke monitoring protocols, that consider screen volumes purged, alongside water-quality indicator parameter stabilization, is recommended to validate and reduce uncertainty when interpreting monitoring-well data within source zone areas. Generalised recommendations on monitoring well based protocols are also developed. A key monitoring well utility is their proportionately greater sample draw from permeable horizons constituting a

  11. Multi-Level Cultural Models

    Science.gov (United States)

    2014-11-05

    usable simulations. This procedure was to be tested using real-world data collected from open-source venues. The final system would support rapid...assess social change. Construct is an agent-based dynamic-network simulation system design to allow the user to assess the spread of information and...protest or violence. Technical Challenges Addressed  Re‐use:    Most agent-based simulation ( ABM ) in use today are one-off. In contrast, we

  12. The Master model on multi-actor and multilevel social responsibilities: A conceptual framework for policies and governance on stakeholders’ social responsibilities

    OpenAIRE

    Ashley, Patricia Almeida

    2011-01-01

    textabstractThis working paper contributes to a collective discussion in a workshop occurring in January 2011 at the International Institute of Social Studies, bringing scholars from Europe and Brazil and aiming inter-university research collaboration on linking policies on social responsibility to development and equity. The paper serves as an introductory discussion for reframing the concept of corporate social responsibility into a broader umbrella concept of multi-actor and multilevel soc...

  13. Intermediate and advanced topics in multilevel logistic regression analysis.

    Science.gov (United States)

    Austin, Peter C; Merlo, Juan

    2017-09-10

    Multilevel data occur frequently in health services, population and public health, and epidemiologic research. In such research, binary outcomes are common. Multilevel logistic regression models allow one to account for the clustering of subjects within clusters of higher-level units when estimating the effect of subject and cluster characteristics on subject outcomes. A search of the PubMed database demonstrated that the use of multilevel or hierarchical regression models is increasing rapidly. However, our impression is that many analysts simply use multilevel regression models to account for the nuisance of within-cluster homogeneity that is induced by clustering. In this article, we describe a suite of analyses that can complement the fitting of multilevel logistic regression models. These ancillary analyses permit analysts to estimate the marginal or population-average effect of covariates measured at the subject and cluster level, in contrast to the within-cluster or cluster-specific effects arising from the original multilevel logistic regression model. We describe the interval odds ratio and the proportion of opposed odds ratios, which are summary measures of effect for cluster-level covariates. We describe the variance partition coefficient and the median odds ratio which are measures of components of variance and heterogeneity in outcomes. These measures allow one to quantify the magnitude of the general contextual effect. We describe an R 2 measure that allows analysts to quantify the proportion of variation explained by different multilevel logistic regression models. We illustrate the application and interpretation of these measures by analyzing mortality in patients hospitalized with a diagnosis of acute myocardial infarction. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

  14. Mathematical learning instruction and teacher motivation factors affecting science technology engineering and math (STEM) major choices in 4-year colleges and universities: Multilevel structural equation modeling

    Science.gov (United States)

    Lee, Ahlam

    2011-12-01

    Using the Educational Longitudinal Study of 2002/06, this study examined the effects of the selected mathematical learning and teacher motivation factors on graduates' science, technology, engineering, and math (STEM) related major choices in 4-year colleges and universities, as mediated by math performance and math self-efficacy. Using multilevel structural equation modeling, I analyzed: (1) the association between mathematical learning instruction factors (i.e., computer, individual, and lecture-based learning activities in mathematics) and students' STEM major choices in 4-year colleges and universities as mediated by math performance and math self-efficacy and (2) the association between school factor, teacher motivation and students' STEM major choices in 4-year colleges and universities via mediators of math performance and math self-efficacy. The results revealed that among the selected learning experience factors, computer-based learning activities in math classrooms yielded the most positive effects on math self-efficacy, which significantly predicted the increase in the proportion of students' STEM major choice as mediated by math self-efficacy. Further, when controlling for base-year math Item Response Theory (IRT) scores, a positive relationship between individual-based learning activities in math classrooms and the first follow-up math IRT scores emerged, which related to the high proportion of students' STEM major choices. The results also indicated that individual and lecture-based learning activities in math yielded positive effects on math self-efficacy, which related to STEM major choice. Concerning between-school levels, teacher motivation yielded positive effects on the first follow up math IRT score, when controlling for base year IRT score. The results from this study inform educators, parents, and policy makers on how mathematics instruction can improve student math performance and encourage more students to prepare for STEM careers. Students

  15. Multi-level analysis in information systems research: the case of enterprise resource planning system usage in China

    Science.gov (United States)

    Sun, Yuan; Bhattacherjee, Anol

    2011-11-01

    Information technology (IT) usage within organisations is a multi-level phenomenon that is influenced by individual-level and organisational-level variables. Yet, current theories, such as the unified theory of acceptance and use of technology, describe IT usage as solely an individual-level phenomenon. This article postulates a model of organisational IT usage that integrates salient organisational-level variables such as user training, top management support and technical support within an individual-level model to postulate a multi-level model of IT usage. The multi-level model was then empirically validated using multi-level data collected from 128 end users and 26 managers in 26 firms in China regarding their use of enterprise resource planning systems and analysed using the multi-level structural equation modelling (MSEM) technique. We demonstrate the utility of MSEM analysis of multi-level data relative to the more common structural equation modelling analysis of single-level data and show how single-level data can be aggregated to approximate multi-level analysis when multi-level data collection is not possible. We hope that this article will motivate future scholars to employ multi-level data and multi-level analysis for understanding organisational phenomena that are truly multi-level in nature.

  16. Multi-level spondylolysis.

    Science.gov (United States)

    Hersh, David S; Kim, Yong H; Razi, Afshin

    2011-01-01

    The incidence of isthmic spondylolysis is approximately 3% to 6% in the general population. Spondylolytic defects involving multiple vertebral levels, on the other hand, are extremely rare. Only a handful of reports have examined the outcomes of surgical treatment of multi-level spondylolysis. Here, we present one case of bilateral pars defects at L3, L4, and L5. The patient, a 46-year-old female, presented with lower back pain radiating into the left lower extremity. Radiographs and CT scans of the lumbar spine revealed bilateral pars defects at L3-L5. The patient underwent lumbar discectomy and interbody fusion of L4-S1 as well as direct repair of the pars defect at L3. There were no postoperative complications, and by seven months the patient had improved clinically. While previous reports describe the use of either direct repair or fusion in the treatment of spondylolysis, we are unaware of reports describing the use of both techniques at adjacent levels.

  17. Resitting a high-stakes postgraduate medical examination on multiple occasions: nonlinear multilevel modelling of performance in the MRCP(UK examinations

    Directory of Open Access Journals (Sweden)

    McManus IC

    2012-06-01

    Full Text Available Abstract Background Failure rates in postgraduate examinations are often high and many candidates therefore retake examinations on several or even many times. Little, however, is known about how candidates perform across those multiple attempts. A key theoretical question to be resolved is whether candidates pass at a resit because they have got better, having acquired more knowledge or skills, or whether they have got lucky, chance helping them to get over the pass mark. In the UK, the issue of resits has become of particular interest since the General Medical Council issued a consultation and is considering limiting the number of attempts candidates may make at examinations. Methods Since 1999 the examination for Membership of the Royal Colleges of Physicians of the United Kingdom (MRCP(UK has imposed no limit on the number of attempts candidates can make at its Part 1, Part2 or PACES (Clinical examination. The present study examined the performance of candidates on the examinations from 2002/2003 to 2010, during which time the examination structure has been stable. Data were available for 70,856 attempts at Part 1 by 39,335 candidates, 37,654 attempts at Part 2 by 23,637 candidates and 40,303 attempts at PACES by 21,270 candidates, with the maximum number of attempts being 26, 21 and 14, respectively. The results were analyzed using multilevel modelling, fitting negative exponential growth curves to individual candidate performance. Results The number of candidates taking the assessment falls exponentially at each attempt. Performance improves across attempts, with evidence in the Part 1 examination that candidates are still improving up to the tenth attempt, with a similar improvement up to the fourth attempt in Part 2 and the sixth attempt at PACES. Random effects modelling shows that candidates begin at a starting level, with performance increasing by a smaller amount at each attempt, with evidence of a maximum, asymptotic level for

  18. Resitting a high-stakes postgraduate medical examination on multiple occasions: nonlinear multilevel modelling of performance in the MRCP(UK) examinations.

    Science.gov (United States)

    McManus, I C; Ludka, Katarzyna

    2012-06-14

    Failure rates in postgraduate examinations are often high and many candidates therefore retake examinations on several or even many times. Little, however, is known about how candidates perform across those multiple attempts. A key theoretical question to be resolved is whether candidates pass at a resit because they have got better, having acquired more knowledge or skills, or whether they have got lucky, chance helping them to get over the pass mark. In the UK, the issue of resits has become of particular interest since the General Medical Council issued a consultation and is considering limiting the number of attempts candidates may make at examinations. Since 1999 the examination for Membership of the Royal Colleges of Physicians of the United Kingdom (MRCP(UK)) has imposed no limit on the number of attempts candidates can make at its Part 1, Part 2 or PACES (Clinical) examination. The present study examined the performance of candidates on the examinations from 2002/2003 to 2010, during which time the examination structure has been stable. Data were available for 70,856 attempts at Part 1 by 39,335 candidates, 37,654 attempts at Part 2 by 23,637 candidates and 40,303 attempts at PACES by 21,270 candidates, with the maximum number of attempts being 26, 21 and 14, respectively. The results were analyzed using multilevel modelling, fitting negative exponential growth curves to individual candidate performance. The number of candidates taking the assessment falls exponentially at each attempt. Performance improves across attempts, with evidence in the Part 1 examination that candidates are still improving up to the tenth attempt, with a similar improvement up to the fourth attempt in Part 2 and the sixth attempt at PACES. Random effects modelling shows that candidates begin at a starting level, with performance increasing by a smaller amount at each attempt, with evidence of a maximum, asymptotic level for candidates, and candidates showing variation in starting

  19. Power and type I error of local fit statistics in multilevel latent class analysis

    NARCIS (Netherlands)

    Nagelkerke, E.; Oberski, D.L.; Vermunt, J.K.

    2017-01-01

    In the social and behavioral sciences, variables are often categorical and people are often nested in groups. Models for such data, such as multilevel logistic regression or the multilevel latent class model, should account for not only the categorical nature of the variables, but also the nested

  20. Multilevel Complex Networks and Systems

    Science.gov (United States)

    Caldarelli, Guido

    2014-03-01

    Network theory has been a powerful tool to model isolated complex systems. However, the classical approach does not take into account the interactions often present among different systems. Hence, the scientific community is nowadays concentrating the efforts on the foundations of new mathematical tools for understanding what happens when multiple networks interact. The case of economic and financial networks represents a paramount example of multilevel networks. In the case of trade, trade among countries the different levels can be described by the different granularity of the trading relations. Indeed, we have now data from the scale of consumers to that of the country level. In the case of financial institutions, we have a variety of levels at the same scale. For example one bank can appear in the interbank networks, ownership network and cds networks in which the same institution can take place. In both cases the systemically important vertices need to be determined by different procedures of centrality definition and community detection. In this talk I will present some specific cases of study related to these topics and present the regularities found. Acknowledged support from EU FET Project ``Multiplex'' 317532.

  1. A multi-level simulation platform of natural gas internal reforming solid oxide fuel cell-gas turbine hybrid generation system - Part II. Balancing units model library and system simulation

    Science.gov (United States)

    Bao, Cheng; Cai, Ningsheng; Croiset, Eric

    2011-10-01

    Following our integrated hierarchical modeling framework of natural gas internal reforming solid oxide fuel cell (IRSOFC), this paper firstly introduces the model libraries of main balancing units, including some state-of-the-art achievements and our specific work. Based on gPROMS programming code, flexible configuration and modular design are fully realized by specifying graphically all unit models in each level. Via comparison with the steady-state experimental data of Siemens-Westinghouse demonstration system, the in-house multi-level SOFC-gas turbine (GT) simulation platform is validated to be more accurate than the advanced power system analysis tool (APSAT). Moreover, some units of the demonstration system are designed reversely for analysis of a typically part-load transient process. The framework of distributed and dynamic modeling in most of units is significant for the development of control strategies in the future.

  2. Analysing the effect of area of residence over the life course in multilevel epidemiology.

    Science.gov (United States)

    Naess, Oyvind; Leyland, Alastair H

    2010-11-01

    In this paper we present multilevel models of individuals' residential history at multiple time points through the life course and their application and discuss some advantages and disadvantages for their use in epidemiological studies. Literature review of research using longitudinal multilevel models in studies of neighbourhood effects, statistical multilevel models that take individuals' residential history into account, and the application of these models in the Oslo mortality study. Measures of variance have been used to investigate the contextual impact of membership to collectives, such as area of residence, at several time points. The few longitudinal multilevel models that have been used suggest that early life area of residence may have an effect on mortality independently of residence later in life although the proportion of variation attributable to area level is small compared to individual level. The following multilevel models have been developed: simple multilevel models for each year separately, a multiple membership model, a cross-classified model, and finally a correlated cross-classified model. These models have different assumptions regarding the timing of influence through the life course. To fully recognise the origin of adult chronic diseases, factors at all stages of the life course at both individual and area level needs to be considered in order to avoid biased estimates. Important challenges in making life course residential data available for research and assessing how changing administrative coding over time reflect contextual impact need to be overcome before these models can be implemented as normal practice in multilevel epidemiology.

  3. Multilevel security for relational databases

    CERN Document Server

    Faragallah, Osama S; El-Samie, Fathi E Abd

    2014-01-01

    Concepts of Database Security Database Concepts Relational Database Security Concepts Access Control in Relational Databases      Discretionary Access Control      Mandatory Access Control      Role-Based Access Control Work Objectives Book Organization Basic Concept of Multilevel Database Security IntroductionMultilevel Database Relations Polyinstantiation      Invisible Polyinstantiation      Visible Polyinstantiation      Types of Polyinstantiation      Architectural Consideration

  4. On the Multilevel Nature of Meta-Analysis: A Tutorial, Comparison of Software Programs, and Discussion of Analytic Choices.

    Science.gov (United States)

    Pastor, Dena A; Lazowski, Rory A

    2018-01-01

    The term "multilevel meta-analysis" is encountered not only in applied research studies, but in multilevel resources comparing traditional meta-analysis to multilevel meta-analysis. In this tutorial, we argue that the term "multilevel meta-analysis" is redundant since all meta-analysis can be formulated as a special kind of multilevel model. To clarify the multilevel nature of meta-analysis the four standard meta-analytic models are presented using multilevel equations and fit to an example data set using four software programs: two specific to meta-analysis (metafor in R and SPSS macros) and two specific to multilevel modeling (PROC MIXED in SAS and HLM). The same parameter estimates are obtained across programs underscoring that all meta-analyses are multilevel in nature. Despite the equivalent results, not all software programs are alike and differences are noted in the output provided and estimators available. This tutorial also recasts distinctions made in the literature between traditional and multilevel meta-analysis as differences between meta-analytic choices, not between meta-analytic models, and provides guidance to inform choices in estimators, significance tests, moderator analyses, and modeling sequence. The extent to which the software programs allow flexibility with respect to these decisions is noted, with metafor emerging as the most favorable program reviewed.

  5. Multilevel Hybrid Chernoff Tau-Leap

    KAUST Repository

    Moraes, Alvaro

    2016-01-06

    Markovian pure jump processes can model many phenomena, e.g. chemical reactions at molecular level, protein transcription and translation, spread of epidemics diseases in small populations and in wireless communication networks, among many others. In this work [6] we present a novel multilevel algorithm for the Chernoff-based hybrid tauleap algorithm. This variance reduction technique allows us to: (a) control the global exit probability of any simulated trajectory, (b) obtain accurate and computable estimates for the expected value of any smooth observable of the process with minimal computational work.

  6. Multilevel Hybrid Chernoff Tau-Leap

    KAUST Repository

    Moraes, Alvaro

    2015-01-07

    Markovian pure jump processes can model many phenomena, e.g. chemical reactions at molecular level, protein transcription and translation, spread of epidemics diseases in small populations and in wireless communication networks, among many others. In this work [6] we present a novel multilevel algorithm for the Chernoff-based hybrid tauleap algorithm. This variance reduction technique allows us to: (a) control the global exit probability of any simulated trajectory, (b) obtain accurate and computable estimates for the expected value of any smooth observable of the process with minimal computational work.

  7. Multilevel Hybrid Chernoff Tau-Leap

    KAUST Repository

    Moraes, Alvaro

    2014-01-06

    Markovian pure jump processes can model many phenomena, e.g. chemical reactions at molecular level, protein transcription and translation, spread of epidemics diseases in small populations and in wireless communication networks, among many others. In this work [6] we present a novel multilevel algorithm for the Chernoff-based hybrid tauleap algorithm. This variance reduction technique allows us to: (a) control the global exit probability of any simulated trajectory, (b) obtain accurate and computable estimates for the expected value of any smooth observable of the process with minimal computational work.

  8. Modeling Fetal Weight for Gestational Age: A Comparison of a Flexible Multi-level Spline-based Model with Other Approaches

    Science.gov (United States)

    Villandré, Luc; Hutcheon, Jennifer A; Perez Trejo, Maria Esther; Abenhaim, Haim; Jacobsen, Geir; Platt, Robert W

    2011-01-01

    We present a model for longitudinal measures of fetal weight as a function of gestational age. We use a linear mixed model, with a Box-Cox transformation of fetal weight values, and restricted cubic splines, in order to flexibly but parsimoniously model median fetal weight. We systematically compare our model to other proposed approaches. All proposed methods are shown to yield similar median estimates, as evidenced by overlapping pointwise confidence bands, except after 40 completed weeks, where our method seems to produce estimates more consistent with observed data. Sex-based stratification affects the estimates of the random effects variance-covariance structure, without significantly changing sex-specific fitted median values. We illustrate the benefits of including sex-gestational age interaction terms in the model over stratification. The comparison leads to the conclusion that the selection of a model for fetal weight for gestational age can be based on the specific goals and configuration of a given study without affecting the precision or value of median estimates for most gestational ages of interest. PMID:21931571

  9. Explaining individual- and country-level variations in unregistered employment using a multi-level model: evidence from 35 Eurasian countries

    Directory of Open Access Journals (Sweden)

    Krasniqi Besnik A.

    2017-12-01

    Full Text Available The aim of this paper is to evaluate the individual- and country-level variations in unregistered employment. To analyse whether it is marginalised groups who are more likely to engage in unregistered employment and explain the country-level variations, a 2010 Life in Transition Survey (LiTS involving 38,864 interviews in 35 Eurasian countries is reported. Multilevel logistic regression analysis reveals that younger age groups, the divorced, and those with fewer years in education, are more likely to be unregistered employed. On a country-level, meanwhile, the prevalence of unregistered employment is strongly associated with tax morale; the greater the asymmetry between informal and formal institutions, the greater is the prevalence of unregistered employment. It is also higher when GDP per capita as well as social distribution and state intervention (subsidies and transfers, social contribution expenditure, health expenditure are lower. The paper concludes by discussing the theoretical and policy implications.

  10. Hybrid approach to structure modeling of the histamine H3 receptor: Multi-level assessment as a tool for model verification.

    Directory of Open Access Journals (Sweden)

    Jakub Jończyk

    Full Text Available The crucial role of G-protein coupled receptors and the significant achievements associated with a better understanding of the spatial structure of known receptors in this family encouraged us to undertake a study on the histamine H3 receptor, whose crystal structure is still unresolved. The latest literature data and availability of different software enabled us to build homology models of higher accuracy than previously published ones. The new models are expected to be closer to crystal structures; and therefore, they are much more helpful in the design of potential ligands. In this article, we describe the generation of homology models with the use of diverse tools and a hybrid assessment. Our study incorporates a hybrid assessment connecting knowledge-based scoring algorithms with a two-step ligand-based docking procedure. Knowledge-based scoring employs probability theory for global energy minimum determination based on information about native amino acid conformation from a dataset of experimentally determined protein structures. For a two-step docking procedure two programs were applied: GOLD was used in the first step and Glide in the second. Hybrid approaches offer advantages by combining various theoretical methods in one modeling algorithm. The biggest advantage of hybrid methods is their intrinsic ability to self-update and self-refine when additional structural data are acquired. Moreover, the diversity of computational methods and structural data used in hybrid approaches for structure prediction limit inaccuracies resulting from theoretical approximations or fuzziness of experimental data. The results of docking to the new H3 receptor model allowed us to analyze ligand-receptor interactions for reference compounds.

  11. Using Swiss Webster mice to model Fetal Alcohol Spectrum Disorders (FASD): An analysis of multilevel time-to-event data through mixed-effects Cox proportional hazards models.

    Science.gov (United States)

    Chi, Peter; Aras, Radha; Martin, Katie; Favero, Carlita

    2016-05-15

    Fetal Alcohol Spectrum Disorders (FASD) collectively describes the constellation of effects resulting from human alcohol consumption during pregnancy. Even with public awareness, the incidence of FASD is estimated to be upwards of 5% in the general population and is becoming a global health problem. The physical, cognitive, and behavioral impairments of FASD are recapitulated in animal models. Recently rodent models utilizing voluntary drinking paradigms have been developed that accurately reflect moderate consumption, which makes up the majority of FASD cases. The range in severity of FASD characteristics reflects the frequency, dose, developmental timing, and individual susceptibility to alcohol exposure. As most rodent models of FASD use C57BL/6 mice, there is a need to expand the stocks of mice studied in order to more fully understand the complex neurobiology of this disorder. To that end, we allowed pregnant Swiss Webster mice to voluntarily drink ethanol via the drinking in the dark (DID) paradigm throughout their gestation period. Ethanol exposure did not alter gestational outcomes as determined by no significant differences in maternal weight gain, maternal liquid consumption, litter size, or pup weight at birth or weaning. Despite seemingly normal gestation, ethanol-exposed offspring exhibit significantly altered timing to achieve developmental milestones (surface righting, cliff aversion, and open field traversal), as analyzed through mixed-effects Cox proportional hazards models. These results confirm Swiss Webster mice as a viable option to study the incidence and causes of ethanol-induced neurobehavioral alterations during development. Future studies in our laboratory will investigate the brain regions and molecules responsible for these behavioral changes. Copyright © 2016. Published by Elsevier B.V.

  12. A new configuration for multilevel converters with diode clamped topology

    DEFF Research Database (Denmark)

    Nami, A.; Zare, F.; Ledwich, G.

    2008-01-01

    Due to the increased use of renewable energy and power elctronic applications, more multilevel converters (MLC) are developed. A Neutral Point Clamped (NPC) inverter is one of the most used multilevel topologies for wind turbine (WT) and photovoltaic (PV) applications. One of the most crucial...... of load changes which can avoid neutral point balancing problem in such converters. In addition, the presented topology is suitable for renewable energy systems to boost the low rectified output-voltage. In order to verify the proposed topology, steady state analysis, modelling and simulations are carried...

  13. The Moderating Effect of Health-Improving Workplace Environment on Promoting Physical Activity in White-Collar Employees: A Multi-Site Longitudinal Study Using Multi-Level Structural Equation Modeling.

    Science.gov (United States)

    Watanabe, Kazuhiro; Otsuka, Yasumasa; Shimazu, Akihito; Kawakami, Norito

    2016-02-01

    This longitudinal study aimed to investigate the moderating effect of health-improving workplace environment on relationships between physical activity, self-efficacy, and psychological distress. Data were collected from 16 worksites and 129 employees at two time-points. Health-improving workplace environment was measured using the Japanese version of the Environmental Assessment Tool. Physical activity, self-efficacy, and psychological distress were also measured. Multi-level structural equation modeling was used to investigate the moderating effect of health-improving workplace environment on relationships between psychological distress, self-efficacy, and physical activity. Psychological distress was negatively associated with physical activity via low self-efficacy. Physical activity was negatively related to psychological distress. Physical activity/fitness facilities in the work environment exaggerated the positive relationship between self-efficacy and physical activity. Physical activity/fitness facilities in the workplace may promote employees' physical activity.

  14. Age, forgiveness, and meeting behavior: A multilevel study

    NARCIS (Netherlands)

    Schulte, E.-M.; Lehmann-Willenbrock, N.K.; Kauffeld, S.

    2013-01-01

    Purpose: This paper aims to examine the effects of age on counteractive team meeting behaviors (e.g. complaining). Forgiveness is included as a potential buffer against these behaviors. A multilevel model is developed to test individual and team level age effects. Design/methodology/approach: A

  15. Help Seeking in Online Collaborative Groupwork: A Multilevel Analysis

    Science.gov (United States)

    Du, Jianxia; Xu, Jianzhong; Fan, Xitao

    2015-01-01

    This study examined predictive models for students' help seeking in the context of online collaborative groupwork. Results from multilevel analysis revealed that most of the variance in help seeking was at the individual student level, and multiple variables at the individual level were predictive of help-seeking behaviour. Help seeking was…

  16. Determinants of firms' investment behaviour : a multilevel approach

    NARCIS (Netherlands)

    Farla, K.

    2013-01-01

    This paper investigates micro and macro determinants of firms' investment behaviour using firm data from 101 developing and emerging economies. A substantial number of firms in our sample does not invest in fixed capital or invests little relative to sales revenue. Using a multilevel probit model we

  17. Local posterior concentration rate for multilevel sparse sequences

    NARCIS (Netherlands)

    Belitser, E.N.; Nurushev, N.

    2017-01-01

    We consider empirical Bayesian inference in the many normal means model in the situation when the high-dimensional mean vector is multilevel sparse, that is,most of the entries of the parameter vector are some fixed values. For instance, the traditional sparse signal is a particular case (with one

  18. Daily Stressors in School-Age Children: A Multilevel Approach

    Science.gov (United States)

    Escobar, Milagros; Alarcón, Rafael; Blanca, María J.; Fernández-Baena, F. Javier; Rosel, Jesús F.; Trianes, María Victoria

    2013-01-01

    This study uses hierarchical or multilevel modeling to identify variables that contribute to daily stressors in a population of schoolchildren. Four hierarchical levels with several predictive variables were considered: student (age, sex, social adaptation of the student, number of life events and chronic stressors experienced, and educational…

  19. A Multilevel Evaluation of a Comprehensive Child Abuse Prevention Program

    Science.gov (United States)

    Lawson, Michael A.; Alameda-Lawson, Tania; Byrnes, Edward C.

    2012-01-01

    Objectives: The purpose of this study is to examine the extent to which participation in a county-wide prevention program leads to improvements in protective factors associated with child abuse prevention (CAP) and whether improvements in measured protective factors relate to decreased odds of child abuse. Method: Using multilevel growth modeling,…

  20. Multilevel techniques for Reservoir Simulation

    DEFF Research Database (Denmark)

    Christensen, Max la Cour

    The subject of this thesis is the development, application and study of novel multilevel methods for the acceleration and improvement of reservoir simulation techniques. The motivation for addressing this topic is a need for more accurate predictions of porous media flow and the ability to carry...... Full Approximation Scheme) • Variational (Galerkin) upscaling • Linear solvers and preconditioners First, a nonlinear multigrid scheme in the form of the Full Approximation Scheme (FAS) is implemented and studied for a 3D three-phase compressible rock/fluids immiscible reservoir simulator...... is extended to include a hybrid strategy, where FAS is combined with Newton’s method to construct a multilevel nonlinear preconditioner. This method demonstrates high efficiency and robustness. Second, an improved IMPES formulated reservoir simulator is implemented using a novel variational upscaling approach...

  1. Stability of Boolean multilevel networks.

    Science.gov (United States)

    Cozzo, Emanuele; Arenas, Alex; Moreno, Yamir

    2012-09-01

    The study of the interplay between the structure and dynamics of complex multilevel systems is a pressing challenge nowadays. In this paper, we use a semiannealed approximation to study the stability properties of random Boolean networks in multiplex (multilayered) graphs. Our main finding is that the multilevel structure provides a mechanism for the stabilization of the dynamics of the whole system even when individual layers work on the chaotic regime, therefore identifying new ways of feedback between the structure and the dynamics of these systems. Our results point out the need for a conceptual transition from the physics of single-layered networks to the physics of multiplex networks. Finally, the fact that the coupling modifies the phase diagram and the critical conditions of the isolated layers suggests that interdependency can be used as a control mechanism.

  2. A multilevel model of patient safety culture: cross-level relationship between organizational culture and patient safety behavior in Taiwan's hospitals.

    Science.gov (United States)

    Chen, I-Chi; Ng, Hui-Fuang; Li, Hung-Hui

    2012-01-01

    As health-care organizations endeavor to improve their quality of care, there is a growing recognition of the importance of establishing a culture of patient safety. The main objective of this study was to investigate the cross-level influences of organizational culture on patient safety behavior in Taiwan's hospitals. The authors measured organizational culture (bureaucratic, supportive and innovative culture), patient safety culture and behavior from 788 hospital workers among 42 hospitals in Taiwan. Multilevel analysis was applied to explore the relationship between organizational culture (group level) and patient safety behavior (individual level). Patient safety culture had positive impact on patient safety behavior in Taiwan's hospitals. The results also indicated that bureaucratic, innovative and supportive organizational cultures all had direct influence on patient safety behavior. However, only supportive culture demonstrated significant moderation effect on the relationship between patient safety culture and patient safety behavior. Furthermore, organizational culture strength was shown correlated negatively with patient safety culture variability. Overall, organizational culture plays an important role in patient safety activities. Safety behaviors of hospital staff are partly influenced by the prevailing cultural norms in their organizations and work groups. For management implications, constructed patient priority from management commitment to leadership is necessary. For academic implications, research on patient safety should consider leadership, group dynamics and organizational learning. These factors are important for understanding the barriers and the possibilities embedded in patient safety. Copyright © 2011 John Wiley & Sons, Ltd.

  3. Multi-Level Secure Local Area Network

    OpenAIRE

    Naval Postgraduate School (U.S.); Center for Information Systems Studies Security and Research (CISR)

    2011-01-01

    Multi-Level Secure Local Area Network is a cost effective, multi-level, easy to use office environment leveraging existing high assurance technology. The Department of Defense and U.S. Government have an identified need to securely share information classified at differing security levels. Because there exist no commercial solutions to this problem, NPS is developing a MLS LAN. The MLS LAN extends high assurance capabilities of an evaluated multi-level secure system to commercial personal com...

  4. Multilevel marketing společnosti Amway

    OpenAIRE

    Drozdková, Markéta

    2010-01-01

    This thesis analyses effectiveness and principles of multilevel marketing as a possible way of selling products and services. Theoretical part describes basis of marketing and direct selling, which is the basis of multilevel marketing. The thesis also states illegal forms of selling that misuse the advantages of multilevel marketing. Pracical part applies gained knowledge on Amway corporation and it atteds to operation of the company, which is evaluated by SWOT analysis.

  5. Multiple imputation by chained equations for systematically and sporadically missing multilevel data.

    Science.gov (United States)

    Resche-Rigon, Matthieu; White, Ian R

    2018-06-01

    In multilevel settings such as individual participant data meta-analysis, a variable is 'systematically missing' if it is wholly missing in some clusters and 'sporadically missing' if it is partly missing in some clusters. Previously proposed methods to impute incomplete multilevel data handle either systematically or sporadically missing data, but frequently both patterns are observed. We describe a new multiple imputation by chained equations (MICE) algorithm for multilevel data with arbitrary patterns of systematically and sporadically missing variables. The algorithm is described for multilevel normal data but can easily be extended for other variable types. We first propose two methods for imputing a single incomplete variable: an extension of an existing method and a new two-stage method which conveniently allows for heteroscedastic data. We then discuss the difficulties of imputing missing values in several variables in multilevel data using MICE, and show that even the simplest joint multilevel model implies conditional models which involve cluster means and heteroscedasticity. However, a simulation study finds that the proposed methods can be successfully combined in a multilevel MICE procedure, even when cluster means are not included in the imputation models.

  6. Explaining ethnic polarization over attitudes towards minority rights in Eastern Europe : a multilevel analysis

    NARCIS (Netherlands)

    Evans, Geoffrey; Need, Ariana

    2002-01-01

    This paper examines divisions between majority and minority ethnic groups over attitudes towards minority rights in 13 East European societies. Using national sample surveys and multilevel models, we test the effectiveness of competing explanations of ethnic polarization in attitudes towards

  7. space vector pulse width modulation of a multi-level diode clamped

    African Journals Online (AJOL)

    ES Obe

    step by step development of MATLAB /SIMULINK modeling of the space vector ..... Pulse Width Mod. of Multi-Level Diode Clamped Converter 119 powergui. Discrete, .... Load. Figure 22: Block diagram of the three level DCC design. 3 LEVEL ...

  8. Three-phase multilevel inverter configuration for open-winding high power application

    DEFF Research Database (Denmark)

    Sanjeevikumar, Padmanaban; Blaabjerg, Frede; Wheeler, Patrick William

    2015-01-01

    This paper work exploits a new dual open-winding three-phase multilevel inverter configuration suitable for high power medium-voltage applications. Modular structure comprised of standard three-phase voltage source inverter (VSI) along with one additional bi-directional semiconductor device (MOSFET...... for implementation purpose. Proposed dual-inverter configuration generates multilevel outputs with benefit includes reduced THD and dv/dt in comparison to other dual-inverter topologies. Complete model of the multilevel ac drive is developed with simple MSCFM modulation in Matlab/PLECs numerical software...

  9. The multilevel governance of migration and integration

    NARCIS (Netherlands)

    Scholten, P.; Penninx, R.; Garcés–Mascareñas, B.; Penninx, R.

    2016-01-01

    This chapter focuses on migration and integration as multilevel policy issues and explores the consequences in terms of multilevel governance. Immigration policymaking has been characterized by continued struggle between national governments and the EU about the amount of discretion states have in

  10. Teaching Multilevel Adult ESL Classes. ERIC Digest.

    Science.gov (United States)

    Shank, Cathy C.; Terrill, Lynda R.

    Teachers in multilevel adult English-as-a-Second-Language classes are challenged to use a variety of materials, activities, and techniques to engage the interest of the learners and assist them in their educational goals. This digest recommends ways to choose and organize content for multilevel classes, explains grouping strategies, discusses a…

  11. Multi-Level Formation of Complex Software Systems

    Directory of Open Access Journals (Sweden)

    Hui Li

    2016-05-01

    Full Text Available We present a multi-level formation model for complex software systems. The previous works extract the software systems to software networks for further studies, but usually investigate the software networks at the class level. In contrast to these works, our treatment of software systems as multi-level networks is more realistic. In particular, the software networks are organized by three levels of granularity, which represents the modularity and hierarchy in the formation process of real-world software systems. More importantly, simulations based on this model have generated more realistic structural properties of software networks, such as power-law, clustering and modularization. On the basis of this model, how the structure of software systems effects software design principles is then explored, and it could be helpful for understanding software evolution and software engineering practices.

  12. Income Inequality and Risk of Suicide in New York City Neighborhoods: A Multilevel Case-Control Study

    Science.gov (United States)

    Miller, Jeffrey R.; Piper, Tinka Markham; Ahern, Jennifer; Tracy, Melissa; Tardiff, Kenneth J.; Vlahov, David; Galea, Sandro

    2005-01-01

    Evidence on the relationship between income inequality and suicide is inconsistent. Data from the New York City Office of the Chief Medical Examiner for all fatal injuries was collected to conduct a multilevel case-control study. In multilevel models, suicide decedents (n = 374) were more likely than accident controls (n = 453) to reside in…

  13. National Profiles of Classroom Quality and Family Involvement: A Multilevel Examination of Proximal Influences on Head Start Children's School Readiness

    Science.gov (United States)

    Bulotsky-Shearer, Rebecca J.; Wen, Xiaoli; Faria, Ann-Marie; Hahs-Vaughn, Debbie L.; Korfmacher, Jon

    2012-01-01

    Guided by a developmental and ecological model, the study employed latent profile analysis to identify a multilevel typology of family involvement and Head Start classroom quality. Using the nationally representative Head Start Family and Child Experiences Survey (FACES 1997; N = 1870), six multilevel latent profiles were estimated, characterized…

  14. Multilevel Cross-Dependent Binary Longitudinal Data

    KAUST Repository

    Serban, Nicoleta

    2013-10-16

    We provide insights into new methodology for the analysis of multilevel binary data observed longitudinally, when the repeated longitudinal measurements are correlated. The proposed model is logistic functional regression conditioned on three latent processes describing the within- and between-variability, and describing the cross-dependence of the repeated longitudinal measurements. We estimate the model components without employing mixed-effects modeling but assuming an approximation to the logistic link function. The primary objectives of this article are to highlight the challenges in the estimation of the model components, to compare two approximations to the logistic regression function, linear and exponential, and to discuss their advantages and limitations. The linear approximation is computationally efficient whereas the exponential approximation applies for rare events functional data. Our methods are inspired by and applied to a scientific experiment on spectral backscatter from long range infrared light detection and ranging (LIDAR) data. The models are general and relevant to many new binary functional data sets, with or without dependence between repeated functional measurements.

  15. A multi-level modeling approach examining PTSD symptom reduction during prolonged exposure therapy: moderating effects of number of trauma types experienced, having an HIV-related index trauma, and years since HIV diagnosis among HIV-positive adults.

    Science.gov (United States)

    Junglen, Angela G; Smith, Brian C; Coleman, Jennifer A; Pacella, Maria L; Boarts, Jessica M; Jones, Tracy; Feeny, Norah C; Ciesla, Jeffrey A; Delahanty, Douglas L

    2017-11-01

    People living with HIV (PLWH) have extensive interpersonal trauma histories and higher rates of posttraumatic stress disorder (PTSD) than the general population. Prolonged exposure (PE) therapy is efficacious in reducing PTSD across a variety of trauma samples; however, research has not examined factors that influence how PTSD symptoms change during PE for PLWH. Using multi-level modeling, we examined the potential moderating effect of number of previous trauma types experienced, whether the index trauma was HIV-related or not, and years since HIV diagnosis on PTSD symptom reduction during a 10-session PE protocol in a sample of 51 PLWH. In general, PTSD symptoms decreased linearly throughout the PE sessions. Experiencing more previous types of traumatic events was associated with a slower rate of PTSD symptom change. In addition, LOCF analyses found that participants with a non-HIV-related versus HIV-related index trauma had a slower rate of change for PTSD symptoms over the course of PE. However, analyses of raw data decreased this finding to marginal. Years since HIV diagnosis did not impact PTSD symptom change. These results provide a better understanding of how to tailor PE to individual clients and aid clinicians in approximating the rate of symptom alleviation. Specifically, these findings underscore the importance of accounting for trauma history and index trauma type when implementing a treatment plan for PTSD in PLWH.

  16. Using multilevel models to evaluate the influence of contextual factors on HIV/AIDS, sexually transmitted infections, and risky sexual behavior in sub-Saharan Africa: a systematic review.

    Science.gov (United States)

    Ward-Peterson, Melissa; Fennie, Kristopher; Mauck, Daniel; Shakir, Maryam; Cosner, Chelsea; Bhoite, Prasad; Trepka, Mary Jo; Madhivanan, Purnima

    2018-02-01

    To describe the use of multilevel models (MLMs) in evaluating the influence of contextual factors on HIV/AIDS, sexually transmitted infections (STIs), and risky sexual behavior (RSB) in sub-Saharan Africa. Ten databases were searched through May 29, 2016. Two reviewers completed screening and full-text review. Studies examining the influence of contextual factors on HIV/AIDS, STIs, and RSB and using MLMs for analysis were included. The Quality Assessment Tool for Quantitative Studies was used to evaluate study quality. A total of 118 studies met inclusion criteria. Seventy-four studies focused on HIV/AIDS-related topics; 46 focused on RSB. No studies related to STIs other than HIV/AIDS met the eligibility criteria. Of five studies examining HIV serostatus and community socioeconomic factors, three found an association between poverty and measures of inequality and increased HIV prevalence. Among studies examining RSB, associations were found with numerous contextual factors, including poverty, education, and gender norms. Studies using MLMs indicate that several contextual factors, including community measures of socioeconomic status and educational attainment, are associated with a number of outcomes related to HIV/AIDS and RSB. Future studies using MLMs should focus on contextual-level interventions to strengthen the evidence base for causality. Copyright © 2017 Elsevier Inc. All rights reserved.

  17. Multilevel classification of security concerns in cloud computing

    Directory of Open Access Journals (Sweden)

    Syed Asad Hussain

    2017-01-01

    Full Text Available Threats jeopardize some basic security requirements in a cloud. These threats generally constitute privacy breach, data leakage and unauthorized data access at different cloud layers. This paper presents a novel multilevel classification model of different security attacks across different cloud services at each layer. It also identifies attack types and risk levels associated with different cloud services at these layers. The risks are ranked as low, medium and high. The intensity of these risk levels depends upon the position of cloud layers. The attacks get more severe for lower layers where infrastructure and platform are involved. The intensity of these risk levels is also associated with security requirements of data encryption, multi-tenancy, data privacy, authentication and authorization for different cloud services. The multilevel classification model leads to the provision of dynamic security contract for each cloud layer that dynamically decides about security requirements for cloud consumer and provider.

  18. Advanced Multilevel Monte Carlo Methods

    KAUST Repository

    Jasra, Ajay; Law, Kody; Suciu, Carina

    2017-01-01

    This article reviews the application of advanced Monte Carlo techniques in the context of Multilevel Monte Carlo (MLMC). MLMC is a strategy employed to compute expectations which can be biased in some sense, for instance, by using the discretization of a associated probability law. The MLMC approach works with a hierarchy of biased approximations which become progressively more accurate and more expensive. Using a telescoping representation of the most accurate approximation, the method is able to reduce the computational cost for a given level of error versus i.i.d. sampling from this latter approximation. All of these ideas originated for cases where exact sampling from couples in the hierarchy is possible. This article considers the case where such exact sampling is not currently possible. We consider Markov chain Monte Carlo and sequential Monte Carlo methods which have been introduced in the literature and we describe different strategies which facilitate the application of MLMC within these methods.

  19. Advanced Multilevel Monte Carlo Methods

    KAUST Repository

    Jasra, Ajay

    2017-04-24

    This article reviews the application of advanced Monte Carlo techniques in the context of Multilevel Monte Carlo (MLMC). MLMC is a strategy employed to compute expectations which can be biased in some sense, for instance, by using the discretization of a associated probability law. The MLMC approach works with a hierarchy of biased approximations which become progressively more accurate and more expensive. Using a telescoping representation of the most accurate approximation, the method is able to reduce the computational cost for a given level of error versus i.i.d. sampling from this latter approximation. All of these ideas originated for cases where exact sampling from couples in the hierarchy is possible. This article considers the case where such exact sampling is not currently possible. We consider Markov chain Monte Carlo and sequential Monte Carlo methods which have been introduced in the literature and we describe different strategies which facilitate the application of MLMC within these methods.

  20. Adaptive Multilevel Monte Carlo Simulation

    KAUST Repository

    Hoel, H

    2011-08-23

    This work generalizes a multilevel forward Euler Monte Carlo method introduced in Michael B. Giles. (Michael Giles. Oper. Res. 56(3):607–617, 2008.) for the approximation of expected values depending on the solution to an Itô stochastic differential equation. The work (Michael Giles. Oper. Res. 56(3):607– 617, 2008.) proposed and analyzed a forward Euler multilevelMonte Carlo method based on a hierarchy of uniform time discretizations and control variates to reduce the computational effort required by a standard, single level, Forward Euler Monte Carlo method. This work introduces an adaptive hierarchy of non uniform time discretizations, generated by an adaptive algorithmintroduced in (AnnaDzougoutov et al. Raùl Tempone. Adaptive Monte Carlo algorithms for stopped diffusion. In Multiscale methods in science and engineering, volume 44 of Lect. Notes Comput. Sci. Eng., pages 59–88. Springer, Berlin, 2005; Kyoung-Sook Moon et al. Stoch. Anal. Appl. 23(3):511–558, 2005; Kyoung-Sook Moon et al. An adaptive algorithm for ordinary, stochastic and partial differential equations. In Recent advances in adaptive computation, volume 383 of Contemp. Math., pages 325–343. Amer. Math. Soc., Providence, RI, 2005.). This form of the adaptive algorithm generates stochastic, path dependent, time steps and is based on a posteriori error expansions first developed in (Anders Szepessy et al. Comm. Pure Appl. Math. 54(10):1169– 1214, 2001). Our numerical results for a stopped diffusion problem, exhibit savings in the computational cost to achieve an accuracy of ϑ(TOL),from(TOL−3), from using a single level version of the adaptive algorithm to ϑ(((TOL−1)log(TOL))2).

  1. Discussão sobre algumas contribuições da modelagem multinível para a investigação de desempenho no trabalho Discussing some multilevel models contributions to investigate performance at work

    Directory of Open Access Journals (Sweden)

    Francisco Antonio Coelho Junior

    2011-08-01

    Full Text Available O investimento no capital intelectual tornou-se o pilar norteador das ações de gerenciamento de pessoas. A literatura em comportamento organizacional investigada enfatiza o efeito de variáveis de contexto no desempenho dos indivíduos. Faz-se mister compreender como se dá o impacto dessas variáveis segundo seus níveis de análise. O presente artigo discute contribuições potenciais da modelagem multinível na investigação de desempenho no trabalho. Discute, ainda, a aplicação dessa modelagem para compreensão de fenômenos comumente investigados em comportamento organizacional. Tais contribuições poderão favorecer a estruturação de modelos preditivos que poderão melhor capturar o significado da inclusão de variáveis típicas do contexto laboral.Investing on intellectual capital became the guiding pillar for personnel management actions. The organizational behavior literature highlights the effect of contextual variables on the performance of individuals. The impact of these variables, which belong to different levels of analysis, needs a better comprehension. This paper discusses the potential multilevel modeling contributions for investigating predictors of that performance. In addition, it also discusses the application of this modeling for understanding usually studied organizational behavior. These contributions may favor structuring predictive models which may better grasp the meaning of the inclusion of diverse and complex levels of variables from the labor context.

  2. Příležitosti a rizika fungování multilevel marketingu v ČR

    OpenAIRE

    Hašková, Lenka

    2017-01-01

    This paper presents the model of the business called Multilevel Marketing that is known as MLM. In the first part there is the characterization, the origin and historical development of Multilevel Marketing. The companies that became pioneers in this branch in The Czech Republic and became successful thanks to this model of the business are also mentioned in the first part of the paper. The differences between pyramid, non-ethical and illegal Multilevel Marketing are also contained in this pa...

  3. Multilevel Modulation formats for Optical Communication

    DEFF Research Database (Denmark)

    Jensen, Jesper Bevensee

    2008-01-01

    This thesis studies the use of multilevel modulation formats for optical communication systems. Multilevel modulation is an attractive method of increasing the spectral efficiency of optical communication systems. Various modulation formats employing phase modulation, amplitude modulation...... or a combination of the two have been studied. The use of polarization multiplexing (PolMux) to double the bit rate has also been investigated. The impact of transmission impairments such as chromatic dispersion, self phase modulation and cross phase modulation has been investigated. The feasibility of multilevel...... modulation for network oriented scenarios has been demonstrated....

  4. Advancing multilevel thinking and methods in HRM research

    NARCIS (Netherlands)

    Renkema, Maarten; Meijerink, Jeroen Gerard; Bondarouk, Tatiana

    2016-01-01

    Purpose Despite the growing belief that multilevel research is necessary to advance HRM understanding, there remains a lack of multilevel thinking – the application of principles for multilevel theory building. The purpose of this paper is to propose a systematic approach for multilevel HRM

  5. Nonresonant interaction of ultrashort electromagnetic pulses with multilevel quantum systems

    Science.gov (United States)

    Belenov, E.; Isakov, V.; Nazarkin, A.

    1994-01-01

    Some features of the excitation of multilevel quantum systems under the action of electromagnetic pulses which are shorter than the inverse frequency of interlevel transitions are considered. It is shown that the interaction is characterized by a specific type of selectivity which is not connected with the resonant absorption of radiation. The simplest three-level model displays the inverse population of upper levels. The effect of an ultrashort laser pulse on a multilevel molecule was regarded as an instant reception of the oscillation velocity by the oscillator and this approach showed an effective excitation and dissociation of the molecule. The estimations testify to the fact that these effects can be observed using modern femtosecond lasers.

  6. Multilevel and kin selection in a connected world

    DEFF Research Database (Denmark)

    Wade, Michael J; Wilson, David S; Goodnight, Charles

    2010-01-01

    in the opposition of two processes: within-group and among-group selection. This distinction is important in light of the current controversy among evolutionary biologists in which some continue to affirm that natural selection centres only and always at the level of the individual organism or gene, despite......Wild et al. argue that the evolution of reduced virulence can be understood from the perspective of inclusive fitness, obviating the need to evoke group selection as a contributing causal factor. Although they acknowledge the mathematical equivalence of the inclusive fitness and multilevel...... selection approaches, they conclude that reduced virulence can be viewed entirely as an individual-level adaptation by the parasite. Here we show that their model is a well-known special case of the more general theory of multilevel selection, and that the cause of reduced virulence resides...

  7. On the multi-level solution algorithm for Markov chains

    Energy Technology Data Exchange (ETDEWEB)

    Horton, G. [Univ. of Erlangen, Nuernberg (Germany)

    1996-12-31

    We discuss the recently introduced multi-level algorithm for the steady-state solution of Markov chains. The method is based on the aggregation principle, which is well established in the literature. Recursive application of the aggregation yields a multi-level method which has been shown experimentally to give results significantly faster than the methods currently in use. The algorithm can be reformulated as an algebraic multigrid scheme of Galerkin-full approximation type. The uniqueness of the scheme stems from its solution-dependent prolongation operator which permits significant computational savings in the evaluation of certain terms. This paper describes the modeling of computer systems to derive information on performance, measured typically as job throughput or component utilization, and availability, defined as the proportion of time a system is able to perform a certain function in the presence of component failures and possibly also repairs.

  8. Multi-level methods and approximating distribution functions

    International Nuclear Information System (INIS)

    Wilson, D.; Baker, R. E.

    2016-01-01

    Biochemical reaction networks are often modelled using discrete-state, continuous-time Markov chains. System statistics of these Markov chains usually cannot be calculated analytically and therefore estimates must be generated via simulation techniques. There is a well documented class of simulation techniques known as exact stochastic simulation algorithms, an example of which is Gillespie’s direct method. These algorithms often come with high computational costs, therefore approximate stochastic simulation algorithms such as the tau-leap method are used. However, in order to minimise the bias in the estimates generated using them, a relatively small value of tau is needed, rendering the computational costs comparable to Gillespie’s direct method. The multi-level Monte Carlo method (Anderson and Higham, Multiscale Model. Simul. 10:146–179, 2012) provides a reduction in computational costs whilst minimising or even eliminating the bias in the estimates of system statistics. This is achieved by first crudely approximating required statistics with many sample paths of low accuracy. Then correction terms are added until a required level of accuracy is reached. Recent literature has primarily focussed on implementing the multi-level method efficiently to estimate a single system statistic. However, it is clearly also of interest to be able to approximate entire probability distributions of species counts. We present two novel methods that combine known techniques for distribution reconstruction with the multi-level method. We demonstrate the potential of our methods using a number of examples.

  9. The Readability of Malaysian English Children Books: A Multilevel Analysis

    Directory of Open Access Journals (Sweden)

    Adlina Ismail

    2016-11-01

    Full Text Available These days, there are more English books for children published by local publishers in Malaysia. It is a positive development because the books will be more accessible to the children. However, the books have never been studied and evaluated in depth yet. One important factor in assessing reading materials is readability. Readability determines whether a text is easy or difficult to understand and a balanced mix of both can promote learning and language development. Various researchers mentioned a multilevel framework of discourse that any language assessment on a text should take into account. The levels that were proposed were word, syntax, textbase, situation model and genre and rhetorical structures. Traditional readability measures such as Flesh Reading Ease Formula, Gunning Readability Index, Fog Count, and Fry Grade Level are not able to address the multilevel because they are based on shallow variables. In contrast, Coh-metrix TERA provided five indices that are correlated to grade level and aligned to the multilevel framework. This study analyzed ten Malaysian English chapter books for children using this Coh-metrix TERA. The result revealed that the Malaysian English children books were easy in shallow level but there was a possible difficulty in textbase and situation model level because of the lack of cohesion. In conclusion, more attention should be given on deeper level of text rather than just word and syntax level.

  10. Multi-level methods and approximating distribution functions

    Energy Technology Data Exchange (ETDEWEB)

    Wilson, D., E-mail: daniel.wilson@dtc.ox.ac.uk; Baker, R. E. [Mathematical Institute, University of Oxford, Radcliffe Observatory Quarter, Woodstock Road, Oxford, OX2 6GG (United Kingdom)

    2016-07-15

    Biochemical reaction networks are often modelled using discrete-state, continuous-time Markov chains. System statistics of these Markov chains usually cannot be calculated analytically and therefore estimates must be generated via simulation techniques. There is a well documented class of simulation techniques known as exact stochastic simulation algorithms, an example of which is Gillespie’s direct method. These algorithms often come with high computational costs, therefore approximate stochastic simulation algorithms such as the tau-leap method are used. However, in order to minimise the bias in the estimates generated using them, a relatively small value of tau is needed, rendering the computational costs comparable to Gillespie’s direct method. The multi-level Monte Carlo method (Anderson and Higham, Multiscale Model. Simul. 10:146–179, 2012) provides a reduction in computational costs whilst minimising or even eliminating the bias in the estimates of system statistics. This is achieved by first crudely approximating required statistics with many sample paths of low accuracy. Then correction terms are added until a required level of accuracy is reached. Recent literature has primarily focussed on implementing the multi-level method efficiently to estimate a single system statistic. However, it is clearly also of interest to be able to approximate entire probability distributions of species counts. We present two novel methods that combine known techniques for distribution reconstruction with the multi-level method. We demonstrate the potential of our methods using a number of examples.

  11. A Multilevel Secure Workflow Management System

    National Research Council Canada - National Science Library

    Kang, Myong H; Froscher, Judith N; Sheth, Amit P; Kochut, Krys J; Miller, John A

    1999-01-01

    The Department of Defense (DoD) needs multilevel secure (MLS) workflow management systems to enable globally distributed users and applications to cooperate across classification levels to achieve mission critical goals...

  12. A multilevel analysis of the demands-control model: Is stress at work determined by factors at the group level or the individual level?

    NARCIS (Netherlands)

    Van Yperen, N.W.; Snijders, T.A.B.

    2000-01-01

    This study explored the extent to which negative health-related outcomes are associated with differences between work groups and with differences between individuals within work groups using R. A. Karasek's (1979) demands-control model. The sample consisted of 260 employees in 31 working groups of a

  13. A multilevel model to estimate the within- and the between-center components of the exposure/disease association in the EPIC study.

    Science.gov (United States)

    Sera, Francesco; Ferrari, Pietro

    2015-01-01

    In a multicenter study, the overall relationship between exposure and the risk of cancer can be broken down into a within-center component, which reflects the individual level association, and a between-center relationship, which captures the association at the aggregate level. A piecewise exponential proportional hazards model with random effects was used to evaluate the association between dietary fiber intake and colorectal cancer (CRC) risk in the EPIC study. During an average follow-up of 11.0 years, 4,517 CRC events occurred among study participants recruited in 28 centers from ten European countries. Models were adjusted by relevant confounding factors. Heterogeneity among centers was modelled with random effects. Linear regression calibration was used to account for errors in dietary questionnaire (DQ) measurements. Risk ratio estimates for a 10 g/day increment in dietary fiber were equal to 0.90 (95%CI: 0.85, 0.96) and 0.85 (0.64, 1.14), at the individual and aggregate levels, respectively, while calibrated estimates were 0.85 (0.76, 0.94), and 0.87 (0.65, 1.15), respectively. In multicenter studies, over a straightforward ecological analysis, random effects models allow information at the individual and ecologic levels to be captured, while controlling for confounding at both levels of evidence.

  14. A multilevel model to estimate the within- and the between-center components of the exposure/disease association in the EPIC study.

    Directory of Open Access Journals (Sweden)

    Francesco Sera

    Full Text Available In a multicenter study, the overall relationship between exposure and the risk of cancer can be broken down into a within-center component, which reflects the individual level association, and a between-center relationship, which captures the association at the aggregate level. A piecewise exponential proportional hazards model with random effects was used to evaluate the association between dietary fiber intake and colorectal cancer (CRC risk in the EPIC study. During an average follow-up of 11.0 years, 4,517 CRC events occurred among study participants recruited in 28 centers from ten European countries. Models were adjusted by relevant confounding factors. Heterogeneity among centers was modelled with random effects. Linear regression calibration was used to account for errors in dietary questionnaire (DQ measurements. Risk ratio estimates for a 10 g/day increment in dietary fiber were equal to 0.90 (95%CI: 0.85, 0.96 and 0.85 (0.64, 1.14, at the individual and aggregate levels, respectively, while calibrated estimates were 0.85 (0.76, 0.94, and 0.87 (0.65, 1.15, respectively. In multicenter studies, over a straightforward ecological analysis, random effects models allow information at the individual and ecologic levels to be captured, while controlling for confounding at both levels of evidence.

  15. Multilevel Deficiency of White Matter Connectivity Networks in Alzheimer’s Disease: A Diffusion MRI Study with DTI and HARDI Models

    Directory of Open Access Journals (Sweden)

    Tao Wang

    2016-01-01

    Full Text Available Alzheimer’s disease (AD is the most common form of dementia in elderly people. It is an irreversible and progressive brain disease. In this paper, we utilized diffusion-weighted imaging (DWI to detect abnormal topological organization of white matter (WM structural networks. We compared the differences between WM connectivity characteristics at global, regional, and local levels in 26 patients with probable AD and 16 normal control (NC elderly subjects, using connectivity networks constructed with the diffusion tensor imaging (DTI model and the high angular resolution diffusion imaging (HARDI model, respectively. At the global level, we found that the WM structural networks of both AD and NC groups had a small-world topology; however, the AD group showed a significant decrease in both global and local efficiency, but an increase in clustering coefficient and the average shortest path length. We further found that the AD patients had significantly decreased nodal efficiency at the regional level, as well as weaker connections in multiple local cortical and subcortical regions, such as precuneus, temporal lobe, hippocampus, and thalamus. The HARDI model was found to be more advantageous than the DTI model, as it was more sensitive to the deficiencies in AD at all of the three levels.

  16. Multi-level, Multi-stage and Stochastic Optimization Models for Energy Conservation in Buildings for Federal, State and Local Agencies

    Science.gov (United States)

    Champion, Billy Ray

    Energy Conservation Measure (ECM) project selection is made difficult given real-world constraints, limited resources to implement savings retrofits, various suppliers in the market and project financing alternatives. Many of these energy efficient retrofit projects should be viewed as a series of investments with annual returns for these traditionally risk-averse agencies. Given a list of ECMs available, federal, state and local agencies must determine how to implement projects at lowest costs. The most common methods of implementation planning are suboptimal relative to cost. Federal, state and local agencies can obtain greater returns on their energy conservation investment over traditional methods, regardless of the implementing organization. This dissertation outlines several approaches to improve the traditional energy conservations models. . Any public buildings in regions with similar energy conservation goals in the United States or internationally can also benefit greatly from this research. Additionally, many private owners of buildings are under mandates to conserve energy e.g., Local Law 85 of the New York City Energy Conservation Code requires any building, public or private, to meet the most current energy code for any alteration or renovation. Thus, both public and private stakeholders can benefit from this research. . The research in this dissertation advances and presents models that decision-makers can use to optimize the selection of ECM projects with respect to the total cost of implementation. A practical application of a two-level mathematical program with equilibrium constraints (MPEC) improves the current best practice for agencies concerned with making the most cost-effective selection leveraging energy services companies or utilities. The two-level model maximizes savings to the agency and profit to the energy services companies (Chapter 2). An additional model presented leverages a single congressional appropriation to implement ECM

  17. A Multilevel Model to Estimate the Within- and the Between-Center Components of the Exposure/Disease Association in the EPIC Study

    OpenAIRE

    Sera, Francesco; Ferrari, Pietro

    2015-01-01

    In a multicenter study, the overall relationship between exposure and the risk of cancer can be broken down into a within-center component, which reflects the individual level association, and a between-center relationship, which captures the association at the aggregate level. A piecewise exponential proportional hazards model with random effects was used to evaluate the association between dietary fiber intake and colorectal cancer (CRC) risk in the EPIC study. During an average follow-up o...

  18. The Preconception Stress and Resiliency Pathways Model: a multi-level framework on maternal, paternal, and child health disparities derived by community-based participatory research.

    Science.gov (United States)

    Ramey, Sharon Landesman; Schafer, Peter; DeClerque, Julia L; Lanzi, Robin G; Hobel, Calvin; Shalowitz, Madeleine; Chinchilli, Vern; Raju, Tonse N K

    2015-04-01

    Emerging evidence supports the theoretical and clinical importance of the preconception period in influencing pregnancy outcomes and child health. Collectively, this evidence affirms the need for a novel, integrative theoretical framework to design future investigations, integrate new findings, and identify promising, evidence-informed interventions to improve intergenerational health and reduce disparities. This article presents a transdisciplinary framework developed by the NIH Community Child Health Network (CCHN) through community-based participatory research processes. CCHN developed a Preconception Stress and Resiliency Pathways (PSRP) model by building local and multi-site community-academic participatory partnerships that established guidelines for research planning and decision-making; reviewed relevant findings diverse disciplinary and community perspectives; and identified the major themes of stress and resilience within the context of families and communities. The PSRP model focuses on inter-relating the multiple, complex, and dynamic biosocial influences theoretically linked to family health disparities. The PSRP model borrowed from and then added original constructs relating to developmental origins of lifelong health, epigenetics, and neighborhood and community influences on pregnancy outcome and family functioning (cf. MCHJ 2014). Novel elements include centrality of the preconception/inter-conception period, role of fathers and the parental relationship, maternal allostatic load (a composite biomarker index of cumulative wear-and-tear of stress), resilience resources of parents, and local neighborhood and community level influences (e.g., employment, housing, education, health care, and stability of basic necessities). CCHN's integrative framework embraces new ways of thinking about how to improve outcomes for future generations, by starting before conception, by including all family members, and by engaging the community vigorously at multiple

  19. One-day-ahead streamflow forecasting via super-ensembles of several neural network architectures based on the Multi-Level Diversity Model

    Science.gov (United States)

    Brochero, Darwin; Hajji, Islem; Pina, Jasson; Plana, Queralt; Sylvain, Jean-Daniel; Vergeynst, Jenna; Anctil, Francois

    2015-04-01

    Theories about generalization error with ensembles are mainly based on the diversity concept, which promotes resorting to many members of different properties to support mutually agreeable decisions. Kuncheva (2004) proposed the Multi Level Diversity Model (MLDM) to promote diversity in model ensembles, combining different data subsets, input subsets, models, parameters, and including a combiner level in order to optimize the final ensemble. This work tests the hypothesis about the minimisation of the generalization error with ensembles of Neural Network (NN) structures. We used the MLDM to evaluate two different scenarios: (i) ensembles from a same NN architecture, and (ii) a super-ensemble built by a combination of sub-ensembles of many NN architectures. The time series used correspond to the 12 basins of the MOdel Parameter Estimation eXperiment (MOPEX) project that were used by Duan et al. (2006) and Vos (2013) as benchmark. Six architectures are evaluated: FeedForward NN (FFNN) trained with the Levenberg Marquardt algorithm (Hagan et al., 1996), FFNN trained with SCE (Duan et al., 1993), Recurrent NN trained with a complex method (Weins et al., 2008), Dynamic NARX NN (Leontaritis and Billings, 1985), Echo State Network (ESN), and leak integrator neuron (L-ESN) (Lukosevicius and Jaeger, 2009). Each architecture performs separately an Input Variable Selection (IVS) according to a forward stepwise selection (Anctil et al., 2009) using mean square error as objective function. Post-processing by Predictor Stepwise Selection (PSS) of the super-ensemble has been done following the method proposed by Brochero et al. (2011). IVS results showed that the lagged stream flow, lagged precipitation, and Standardized Precipitation Index (SPI) (McKee et al., 1993) were the most relevant variables. They were respectively selected as one of the firsts three selected variables in 66, 45, and 28 of the 72 scenarios. A relationship between aridity index (Arora, 2002) and NN

  20. Multilevel sequential Monte Carlo samplers

    KAUST Repository

    Beskos, Alexandros; Jasra, Ajay; Law, Kody; Tempone, Raul; Zhou, Yan

    2016-01-01

    In this article we consider the approximation of expectations w.r.t. probability distributions associated to the solution of partial differential equations (PDEs); this scenario appears routinely in Bayesian inverse problems. In practice, one often has to solve the associated PDE numerically, using, for instance finite element methods which depend on the step-size level . hL. In addition, the expectation cannot be computed analytically and one often resorts to Monte Carlo methods. In the context of this problem, it is known that the introduction of the multilevel Monte Carlo (MLMC) method can reduce the amount of computational effort to estimate expectations, for a given level of error. This is achieved via a telescoping identity associated to a Monte Carlo approximation of a sequence of probability distributions with discretization levels . ∞>h0>h1⋯>hL. In many practical problems of interest, one cannot achieve an i.i.d. sampling of the associated sequence and a sequential Monte Carlo (SMC) version of the MLMC method is introduced to deal with this problem. It is shown that under appropriate assumptions, the attractive property of a reduction of the amount of computational effort to estimate expectations, for a given level of error, can be maintained within the SMC context. That is, relative to exact sampling and Monte Carlo for the distribution at the finest level . hL. The approach is numerically illustrated on a Bayesian inverse problem. © 2016 Elsevier B.V.

  1. Multilevel sequential Monte Carlo samplers

    KAUST Repository

    Beskos, Alexandros

    2016-08-29

    In this article we consider the approximation of expectations w.r.t. probability distributions associated to the solution of partial differential equations (PDEs); this scenario appears routinely in Bayesian inverse problems. In practice, one often has to solve the associated PDE numerically, using, for instance finite element methods which depend on the step-size level . hL. In addition, the expectation cannot be computed analytically and one often resorts to Monte Carlo methods. In the context of this problem, it is known that the introduction of the multilevel Monte Carlo (MLMC) method can reduce the amount of computational effort to estimate expectations, for a given level of error. This is achieved via a telescoping identity associated to a Monte Carlo approximation of a sequence of probability distributions with discretization levels . ∞>h0>h1⋯>hL. In many practical problems of interest, one cannot achieve an i.i.d. sampling of the associated sequence and a sequential Monte Carlo (SMC) version of the MLMC method is introduced to deal with this problem. It is shown that under appropriate assumptions, the attractive property of a reduction of the amount of computational effort to estimate expectations, for a given level of error, can be maintained within the SMC context. That is, relative to exact sampling and Monte Carlo for the distribution at the finest level . hL. The approach is numerically illustrated on a Bayesian inverse problem. © 2016 Elsevier B.V.

  2. How does a servant leader fuel the service fire? A multilevel model of servant leadership, individual self identity, group competition climate, and customer service performance.

    Science.gov (United States)

    Chen, Zhijun; Zhu, Jing; Zhou, Mingjian

    2015-03-01

    Building on a social identity framework, our cross-level process model explains how a manager's servant leadership affects frontline employees' service performance, measured as service quality, customer-focused citizenship behavior, and customer-oriented prosocial behavior. Among a sample of 238 hairstylists in 30 salons and 470 of their customers, we found that hair stylists' self-identity embedded in the group, namely, self-efficacy and group identification, partially mediated the positive effect of salon managers' servant leadership on stylists' service performance as rated by the customers, after taking into account the positive influence of transformational leadership. Moreover, group competition climate strengthened the positive relationship between self-efficacy and service performance. PsycINFO Database Record (c) 2015 APA, all rights reserved.

  3. Political participation of older adults in Scandinavia - the civic voluntarism model revisited? A multi-level analysis of three types of political participatio

    Directory of Open Access Journals (Sweden)

    Mikael Nygård

    2013-02-01

    Full Text Available This article examines political participation among older adults in Österbotten, Finland, and Västerbotten, Sweden. Two specific hypotheses are tested. First, we anticipate that older adults are loyal voters but less avid in engaging in politics between elections. Second, we expect individuallevel resources to explain why older people participate in politics. The article offers two contributions to the literature on political participation of older adults. First, it corroborates earlier findings by showing that older adults indeed have a higher inclination to vote than to engage in political activities between elections, but it also shows that the latter engagement is more diversified than one could expect. Second, although the findings largely support the resource model, they suggest that we need to consider also other factors such as the overall attitude towards older people.

  4. Conceptualising Multilevel Regulation in the EU: A Legal Translation of Multilevel Governance?

    NARCIS (Netherlands)

    Chowdhury, Nupur; Wessel, Ramses A.

    2012-01-01

    How should we conceive of regulation in the European context? This paper attempts to answer this by developing multilevel regulation as a theoretical concept. The basic aim of the paper is to explore the difference and convergence between regulation and governance and develop multilevel governance

  5. Traditional Dietary Pattern Increases Risk of Prostate Cancer in Argentina: Results of a Multilevel Modeling and Bias Analysis from a Case-Control Study

    International Nuclear Information System (INIS)

    Niclis, C.; Roman, M. D.; Eynard, A. R.; Diaz, M. D. P.

    2015-01-01

    There is increasing evidence that dietary habits play a role in prostate cancer (PC) occurrence. Argentinean cancer risk studies require additional attention because of the singular dietary pattern of this population. A case-control study (147 PC cases, 300 controls) was conducted in Cordoba (Argentina) throughout 2008-2013. A principal component factor analysis was performed to identify dietary patterns. A mixed logistic regression model was applied, taking into account family history of cancer. Possible bias was evaluated by probabilistic bias analysis. Four dietary patterns were identified: Traditional (fatty red meats, offal, processed meat, starchy vegetables, added sugars and sweets, candies, fats, and vegetable oils), Prudent (non starchy vegetables, whole grains), Carbohydrate (sodas/juices and bakery products), and Cheese (cheeses). High adherence to the Traditional (OR 2.82, 95 % CI: 1.569-5.099) and Carbohydrate Patterns (OR 2.14, 95 % CI: 1.470-3.128) showed a promoting effect for PC, whereas the Prudent and Cheese Patterns were independent factors. PC occurrence was also associated with family history of PC. Bias adjusted ORs indicate that the validity of the present study is acceptable. High adherence to characteristic Argentinean dietary patterns was associated with increased PC risk. Our results incorporate original contributions to knowledge about scenarios in South American dietary patterns and PC occurrence.

  6. Traditional Dietary Pattern Increases Risk of Prostate Cancer in Argentina: Results of a Multilevel Modeling and Bias Analysis from a Case-Control Study

    Directory of Open Access Journals (Sweden)

    Camila Niclis

    2015-01-01

    Full Text Available There is increasing evidence that dietary habits play a role in prostate cancer (PC occurrence. Argentinean cancer risk studies require additional attention because of the singular dietary pattern of this population. A case-control study (147 PC cases, 300 controls was conducted in Córdoba (Argentina throughout 2008–2013. A principal component factor analysis was performed to identify dietary patterns. A mixed logistic regression model was applied, taking into account family history of cancer. Possible bias was evaluated by probabilistic bias analysis. Four dietary patterns were identified: Traditional (fatty red meats, offal, processed meat, starchy vegetables, added sugars and sweets, candies, fats, and vegetable oils, Prudent (nonstarchy vegetables, whole grains, Carbohydrate (sodas/juices and bakery products, and Cheese (cheeses. High adherence to the Traditional (OR 2.82, 95%CI: 1.569–5.099 and Carbohydrate Patterns (OR 2.14, 95%CI: 1.470–3.128 showed a promoting effect for PC, whereas the Prudent and Cheese Patterns were independent factors. PC occurrence was also associated with family history of PC. Bias adjusted ORs indicate that the validity of the present study is acceptable. High adherence to characteristic Argentinean dietary patterns was associated with increased PC risk. Our results incorporate original contributions to knowledge about scenarios in South American dietary patterns and PC occurrence.

  7. A framework to promote collective action within the One Health community of practice: Using participatory modelling to enable interdisciplinary, cross-sectoral and multi-level integration

    Directory of Open Access Journals (Sweden)

    Aurelie Binot

    2015-12-01

    The implementation of a One Health (OH approach in this context calls for improved integration among disciplines and improved cross-sectoral collaboration, involving stakeholders at different levels. For sure, such integration is not achieved spontaneously, implies methodological guidelines and has transaction costs. We explore pathways for implementing such collaboration in SEA context, highlighting the main challenges to be faced by researchers and other target groups involved in OH actions. On this basis, we propose a conceptual framework of OH integration. Throughout 3 components (field-based data management, professional training workshops and higher education, we suggest to develop a new culture of networking involving actors from various disciplines, sectors and levels (from the municipality to the Ministries through a participatory modelling process, fostering synergies and cooperation. This framework could stimulate long-term dialogue process, based on the combination of case studies implementation and capacity building. It aims for implementing both institutional OH dynamics (multi-stakeholders and cross-sectoral and research approaches promoting systems thinking and involving social sciences to follow-up and strengthen collective action.

  8. A framework to promote collective action within the One Health community of practice: Using participatory modelling to enable interdisciplinary, cross-sectoral and multi-level integration.

    Science.gov (United States)

    Binot, Aurelie; Duboz, Raphaël; Promburom, Panomsak; Phimpraphai, Waraphon; Cappelle, Julien; Lajaunie, Claire; Goutard, Flavie Luce; Pinyopummintr, Tanu; Figuié, Muriel; Roger, François Louis

    2015-12-01

    As Southeast Asia (SEA) is characterized by high human and domestic animal densities, growing intensification of trade, drastic land use changes and biodiversity erosion, this region appears to be a hotspot to study complex dynamics of zoonoses emergence and health issues at the Animal-Human-Environment interface. Zoonotic diseases and environmental health issues can have devastating socioeconomic and wellbeing impacts. Assessing and managing the related risks implies to take into account ecological and social dynamics at play, in link with epidemiological patterns. The implementation of a One Health ( OH ) approach in this context calls for improved integration among disciplines and improved cross-sectoral collaboration, involving stakeholders at different levels. For sure, such integration is not achieved spontaneously, implies methodological guidelines and has transaction costs. We explore pathways for implementing such collaboration in SEA context, highlighting the main challenges to be faced by researchers and other target groups involved in OH actions. On this basis, we propose a conceptual framework of OH integration. Throughout 3 components (field-based data management, professional training workshops and higher education), we suggest to develop a new culture of networking involving actors from various disciplines, sectors and levels (from the municipality to the Ministries) through a participatory modelling process, fostering synergies and cooperation. This framework could stimulate long-term dialogue process, based on the combination of case studies implementation and capacity building. It aims for implementing both institutional OH dynamics (multi-stakeholders and cross-sectoral) and research approaches promoting systems thinking and involving social sciences to follow-up and strengthen collective action.

  9. On the Usefulness of a Multilevel Logistic Regression Approach to Person-Fit Analysis

    Science.gov (United States)

    Conijn, Judith M.; Emons, Wilco H. M.; van Assen, Marcel A. L. M.; Sijtsma, Klaas

    2011-01-01

    The logistic person response function (PRF) models the probability of a correct response as a function of the item locations. Reise (2000) proposed to use the slope parameter of the logistic PRF as a person-fit measure. He reformulated the logistic PRF model as a multilevel logistic regression model and estimated the PRF parameters from this…

  10. Managing the risks of proactivity: A multilevel study of initiative and performance in the middle management context

    NARCIS (Netherlands)

    Glaser, L.; Stam, W.; Takeuchi, R.

    2016-01-01

    Drawing on theories of behavioral decision making and situational strength, we developed and tested a multilevel model that explains how the performance outcomes of personal initiative tendency depend on the extent of alignment between organizational control mechanisms and proactive individuals'

  11. Theoretical calculation of saturated absorption for multilevel atoms

    International Nuclear Information System (INIS)

    O'Kane, T.J.; Scholten, R.E.; Farrell, P.M.

    1998-01-01

    We present the first theoretical saturated absorption spectra for general multi-level atoms, using a model based on extensions of the optical Bloch equations, and using Monte Carlo averaging of the absorption of individual atoms with random trajectories through a standing wave. We are for the first time able to accurately predict the merging of hyperfine and cross-over resonances due to intensity dependent phenomena such as power broadening. Results for 20-level sodium and 24-level rubidium models are presented and compared to experiment, demonstrating excellent agreement

  12. Multilevel sequential Monte-Carlo samplers

    KAUST Repository

    Jasra, Ajay

    2016-01-01

    Multilevel Monte-Carlo methods provide a powerful computational technique for reducing the computational cost of estimating expectations for a given computational effort. They are particularly relevant for computational problems when approximate distributions are determined via a resolution parameter h, with h=0 giving the theoretical exact distribution (e.g. SDEs or inverse problems with PDEs). The method provides a benefit by coupling samples from successive resolutions, and estimating differences of successive expectations. We develop a methodology that brings Sequential Monte-Carlo (SMC) algorithms within the framework of the Multilevel idea, as SMC provides a natural set-up for coupling samples over different resolutions. We prove that the new algorithm indeed preserves the benefits of the multilevel principle, even if samples at all resolutions are now correlated.

  13. Multilevel sequential Monte-Carlo samplers

    KAUST Repository

    Jasra, Ajay

    2016-01-05

    Multilevel Monte-Carlo methods provide a powerful computational technique for reducing the computational cost of estimating expectations for a given computational effort. They are particularly relevant for computational problems when approximate distributions are determined via a resolution parameter h, with h=0 giving the theoretical exact distribution (e.g. SDEs or inverse problems with PDEs). The method provides a benefit by coupling samples from successive resolutions, and estimating differences of successive expectations. We develop a methodology that brings Sequential Monte-Carlo (SMC) algorithms within the framework of the Multilevel idea, as SMC provides a natural set-up for coupling samples over different resolutions. We prove that the new algorithm indeed preserves the benefits of the multilevel principle, even if samples at all resolutions are now correlated.

  14. Agent Based Reasoning in Multilevel Flow Modeling

    DEFF Research Database (Denmark)

    Lind, Morten; Zhang, Xinxin

    2012-01-01

    to launch the MFM Workbench into an agent based environment, which can complement disadvantages of the original software. The agent-based MFM Workbench is centered on a concept called “Blackboard System” and use an event based mechanism to arrange the reasoning tasks. This design will support the new...

  15. Multilevel Flow Modeling of Domestic Heating Systems

    DEFF Research Database (Denmark)

    Hu, Junjie; Lind, Morten; You, Shi

    2012-01-01

    the operation on fault analysis and control. A significant improvement of the MFM methodology has been recently proposed, where the “role” concept was introduced to enable the representation of structural entities and the conveyance of important information for building up knowledge bases, with the purpose...... i.e. supplying and transferring thermal energy, it is off interest to use MFM to investigate similarities and differences between different implementations. In this paper, three typical domestic European heating systems, which differ from each other in the number of temperature sensors and auxiliary...

  16. Efficient modelling of a modular multilevel converter

    DEFF Research Database (Denmark)

    El-Khatib, Walid Ziad; Holbøll, Joachim; Rasmussen, Tonny Wederberg

    2013-01-01

    Looking at the near future, we see that offshore wind penetration into the electrical grid will continue increasing rapidly. Until very recently, the trend has been to place the offshore wind farms close to shore within the reach for transmission using HVAC cables but for larger distances HVDC...

  17. Synchronous Control of Modular Multilevel Converters

    DEFF Research Database (Denmark)

    Oleschuk, Valentin; Blaabjerg, Frede; Bose, Bimal K.

    2002-01-01

    A novel method of direct synchronous pulsewidth modulation (PWM) is applied for control of modular multilevel converters consisting from three standard triphase inverter modules along with an 0.33 p.u. output transformer. The proposed method provides synchronisation of the voltage waveforms...... for each module and the composed voltage at the output of the converter. Multilevel output voltage of the converter has quarter-wave symmetry during the whole range including the zone of overmodulation. Both continuous and discontinuous versions of synchronous PWM, based on vector approach...

  18. Multilevel radiative thermal memory realized by the hysteretic metal-insulator transition of vanadium dioxide

    International Nuclear Information System (INIS)

    Ito, Kota; Nishikawa, Kazutaka; Iizuka, Hideo

    2016-01-01

    Thermal information processing is attracting much interest as an analog of electronic computing. We experimentally demonstrated a radiative thermal memory utilizing a phase change material. The hysteretic metal-insulator transition of vanadium dioxide (VO 2 ) allows us to obtain a multilevel memory. We developed a Preisach model to explain the hysteretic radiative heat transfer between a VO 2 film and a fused quartz substrate. The transient response of our memory predicted by the Preisach model agrees well with the measured response. Our multilevel thermal memory paves the way for thermal information processing as well as contactless thermal management

  19. Multilevel radiative thermal memory realized by the hysteretic metal-insulator transition of vanadium dioxide

    Energy Technology Data Exchange (ETDEWEB)

    Ito, Kota, E-mail: kotaito@mosk.tytlabs.co.jp; Nishikawa, Kazutaka; Iizuka, Hideo [Toyota Central Research and Development Labs, Nagakute, Aichi 480-1192 (Japan)

    2016-02-01

    Thermal information processing is attracting much interest as an analog of electronic computing. We experimentally demonstrated a radiative thermal memory utilizing a phase change material. The hysteretic metal-insulator transition of vanadium dioxide (VO{sub 2}) allows us to obtain a multilevel memory. We developed a Preisach model to explain the hysteretic radiative heat transfer between a VO{sub 2} film and a fused quartz substrate. The transient response of our memory predicted by the Preisach model agrees well with the measured response. Our multilevel thermal memory paves the way for thermal information processing as well as contactless thermal management.

  20. Multi-Level Risk Assessment of a Power Plant Gas Turbine Applying ...

    African Journals Online (AJOL)

    Multi-Level Risk Assessment of a Power Plant Gas Turbine Applying the Criticality Index Model. ... Journal of the Nigerian Association of Mathematical Physics ... This study has carefully shown and expressed a step by step computation of the severity level of the Turbine component parts, using the Criticality Index model.

  1. Nonlinear Control Structure of Grid Connected Modular Multilevel Converters

    DEFF Research Database (Denmark)

    Hajizadeh, Amin; Norum, Lars; Ahadpour Shal, Alireza

    2017-01-01

    in the prediction step in order to preserve the stochastic characteristics of a nonlinear system. In order to design adaptive robust control strategy and nonlinear observer, mathematical model of MMC using rotating d-q theory has been used. Digital time-domain simulation studies are carried out in the Matlab......This paper implements nonlinear control structure based on Adaptive Fuzzy Sliding Mode (AFSM) Current Control and Unscented Kalman Filter (UKF) to estimate the capacitor voltages from the measurement of arm currents of Modular Multilevel Converter (MMC). UKF use nonlinear unscented transforms....../Simulink environment to verify the performance of the overall proposed control structure during different case studies....

  2. A multilevel method for conductive-radiative heat transfer

    Energy Technology Data Exchange (ETDEWEB)

    Banoczi, J.M.; Kelley, C.T. [North Carolina State Univ., Raleigh, NC (United States)

    1996-12-31

    We present a fast multilevel algorithm for the solution of a system of nonlinear integro-differential equations that model steady-state combined radiative-conductive heat transfer. The equations can be formulated as a compact fixed point problem with a fixed point map that requires both a solution of the linear transport equation and the linear heat equation for its evaluation. We use fast transport solvers developed by the second author, to construct an efficient evaluation of the fixed point map and then apply the Atkinson-Brakhage, method, with Newton-GMRES as the coarse mesh solver, to the full nonlinear system.

  3. Multilevel Hierarchy of Economic Space: Formation of Evolutionary Taxonomy

    Directory of Open Access Journals (Sweden)

    Daniil Petrovich Frolov

    2013-12-01

    Full Text Available The article considers methodological problems of hierarchical structuring of economic space. The evolution survey of multilevel analysis concepts reveals a dominant role of two-level (micro- macro neoclassical models because of the path dependence effect. In institutional and evolutionary theories the application of mesoanalysis and three-level models gradually becomes more active, but conventions in the field of taxonomy are extremely inert. The main methodological problems of a hierarchical taksonomization of economic space include the problem of taxonomical «rupture» of a subject and a method of Economics, the problem of an identification of the level (rank and scale of economic phenomena, the problem of an identification of subjects and business location, the problem of terminological unification. The author›s hierarchical model of economic space is developed in a context of the generalized evolutionary theory on the basis of multilevel population thinking. The model offers differentiation of industrial and territorial (spatial division and cooperation of labour and, more widely, economic activity. Branches and generation are treated as objects of the industrial analysis, population and ecocenosis – objects of the spatial analysis that allows reintegration of spatial formations in the system of economic analysis. The study of mesolevels and interlevel relations is particularly important. Institutionalism can be considered as metanarrative, i.e. one of universal languages of Economics. Scales and ranks of the functions assigned to subjects and objects of transactions define level differentiation of institutions’ forms in economic space

  4. Multilevel Dual Damascene copper interconnections

    Science.gov (United States)

    Lakshminarayanan, S.

    Copper has been acknowledged as the interconnect material for future generations of ICs to overcome the bottlenecks on speed and reliability present with the current Al based wiring. A new set of challenges brought to the forefront when copper replaces aluminum, have to be met and resolved to make it a viable option. Unit step processes related to copper technology have been under development for the last few years. In this work, the application of copper as the interconnect material in multilevel structures with SiO2 as the interlevel dielectric has been explored, with emphasis on integration issues and complete process realization. Interconnect definition was achieved by the Dual Damascene approach using chemical mechanical polishing of oxide and copper. The choice of materials used as adhesion promoter/diffusion barrier included Ti, Ta and CVD TiN. Two different polish chemistries (NH4OH or HNO3 based) were used to form the interconnects. The diffusion barrier was removed during polishing (in the case of TiN) or by a post CMP etch (as with Ti or Ta). Copper surface passivation was performed using boron implantation and PECVD nitride encapsulation. The interlevel dielectric way composed of a multilayer stack of PECVD SiO2 and SixNy. A baseline process sequence which ensured the mechanical and thermal compatibility of the different unit steps was first created. A comprehensive test vehicle was designed and test structures were fabricated using the process flow developed. Suitable modifications were subsequently introduced in the sequence as and when processing problems were encountered. Electrical characterization was performed on the fabricated devices, interconnects, contacts and vias. The structures were subjected to thermal stressing to assess their stability and performance. The measurement of interconnect sheet resistances revealed lower copper loss due to dishing on samples polished using HNO3 based slurry. Interconnect resistances remained stable upto 400o

  5. A multilevel evolutionary framework for sustainability analysis

    Directory of Open Access Journals (Sweden)

    Timothy M. Waring

    2015-06-01

    Full Text Available Sustainability theory can help achieve desirable social-ecological states by generalizing lessons across contexts and improving the design of sustainability interventions. To accomplish these goals, we argue that theory in sustainability science must (1 explain the emergence and persistence of social-ecological states, (2 account for endogenous cultural change, (3 incorporate cooperation dynamics, and (4 address the complexities of multilevel social-ecological interactions. We suggest that cultural evolutionary theory broadly, and cultural multilevel selection in particular, can improve on these fronts. We outline a multilevel evolutionary framework for describing social-ecological change and detail how multilevel cooperative dynamics can determine outcomes in environmental dilemmas. We show how this framework complements existing sustainability frameworks with a description of the emergence and persistence of sustainable institutions and behavior, a means to generalize causal patterns across social-ecological contexts, and a heuristic for designing and evaluating effective sustainability interventions. We support these assertions with case examples from developed and developing countries in which we track cooperative change at multiple levels of social organization as they impact social-ecological outcomes. Finally, we make suggestions for further theoretical development, empirical testing, and application.

  6. MULTILEVEL SYNCRETISM AND THE EVOLUTION OF ...

    African Journals Online (AJOL)

    MULTILEVEL SYNCRETISM AND THE EVOLUTION OF AFRIKAANS. PERIPHRASTIC POSSESSIVES WITH SE. Paul T. Roberge. University or North Carolina, Chapel ..... van hem ook een bees gestoole ben ook drie volk !lli!. spoor en ook ben daar bij Bester een velds waage uijt gespanne gewees heef zulle de man zijn ...

  7. Single-Level and Multilevel Mediation Analysis

    Science.gov (United States)

    Tofighi, Davood; Thoemmes, Felix

    2014-01-01

    Mediation analysis is a statistical approach used to examine how the effect of an independent variable on an outcome is transmitted through an intervening variable (mediator). In this article, we provide a gentle introduction to single-level and multilevel mediation analyses. Using single-level data, we demonstrate an application of structural…

  8. Robust Algebraic Multilevel Methods and Algorithms

    CERN Document Server

    Kraus, Johannes

    2009-01-01

    This book deals with algorithms for the solution of linear systems of algebraic equations with large-scale sparse matrices, with a focus on problems that are obtained after discretization of partial differential equations using finite element methods. Provides a systematic presentation of the recent advances in robust algebraic multilevel methods. Can be used for advanced courses on the topic.

  9. Multilevel interventions aimed at adult obesity prevention

    DEFF Research Database (Denmark)

    Benwell, Ann Fenger

    A growing body of literature emphasizes the importance of using both quantitative and qualitative methods to investigate the wide range of aspects which hinder or promote the success of health interventions. The pilot phase of this study highlights how mixed-method approaches can be strengthened ...... to investigate factors associated with multi-level obesity prevention....

  10. Engineering applications of heuristic multilevel optimization methods

    Science.gov (United States)

    Barthelemy, Jean-Francois M.

    1989-01-01

    Some engineering applications of heuristic multilevel optimization methods are presented and the discussion focuses on the dependency matrix that indicates the relationship between problem functions and variables. Coordination of the subproblem optimizations is shown to be typically achieved through the use of exact or approximate sensitivity analysis. Areas for further development are identified.

  11. Behavioral spillovers from freeriding in multilevel interactions.

    NARCIS (Netherlands)

    Thommes, K; Vyrastekova, J.; Akkerman, A.

    2015-01-01

    We study multilevel interactions using experimental methods. Does the efficiency of a production team suffer from the freeriding behavior of some team members at the firm level? Can we identify behavioral spillovers affecting teams? We isolate common tasks that teams must complete - coordination and

  12. Multidisciplinary design and analytic approaches to advance prospective research on the multilevel determinants of child health.

    Science.gov (United States)

    Johnson, Sara B; Little, Todd D; Masyn, Katherine; Mehta, Paras D; Ghazarian, Sharon R

    2017-06-01

    Characterizing the determinants of child health and development over time, and identifying the mechanisms by which these determinants operate, is a research priority. The growth of precision medicine has increased awareness and refinement of conceptual frameworks, data management systems, and analytic methods for multilevel data. This article reviews key methodological challenges in cohort studies designed to investigate multilevel influences on child health and strategies to address them. We review and summarize methodological challenges that could undermine prospective studies of the multilevel determinants of child health and ways to address them, borrowing approaches from the social and behavioral sciences. Nested data, variation in intervals of data collection and assessment, missing data, construct measurement across development and reporters, and unobserved population heterogeneity pose challenges in prospective multilevel cohort studies with children. We discuss innovations in missing data, innovations in person-oriented analyses, and innovations in multilevel modeling to address these challenges. Study design and analytic approaches that facilitate the integration across multiple levels, and that account for changes in people and the multiple, dynamic, nested systems in which they participate over time, are crucial to fully realize the promise of precision medicine for children and adolescents. Copyright © 2017 Elsevier Inc. All rights reserved.

  13. Design of shared unit-dose drug distribution network using multi-level particle swarm optimization.

    Science.gov (United States)

    Chen, Linjie; Monteiro, Thibaud; Wang, Tao; Marcon, Eric

    2018-03-01

    Unit-dose drug distribution systems provide optimal choices in terms of medication security and efficiency for organizing the drug-use process in large hospitals. As small hospitals have to share such automatic systems for economic reasons, the structure of their logistic organization becomes a very sensitive issue. In the research reported here, we develop a generalized multi-level optimization method - multi-level particle swarm optimization (MLPSO) - to design a shared unit-dose drug distribution network. Structurally, the problem studied can be considered as a type of capacitated location-routing problem (CLRP) with new constraints related to specific production planning. This kind of problem implies that a multi-level optimization should be performed in order to minimize logistic operating costs. Our results show that with the proposed algorithm, a more suitable modeling framework, as well as computational time savings and better optimization performance are obtained than that reported in the literature on this subject.

  14. Multilevel Weighted Support Vector Machine for Classification on Healthcare Data with Missing Values.

    Directory of Open Access Journals (Sweden)

    Talayeh Razzaghi

    Full Text Available This work is motivated by the needs of predictive analytics on healthcare data as represented by Electronic Medical Records. Such data is invariably problematic: noisy, with missing entries, with imbalance in classes of interests, leading to serious bias in predictive modeling. Since standard data mining methods often produce poor performance measures, we argue for development of specialized techniques of data-preprocessing and classification. In this paper, we propose a new method to simultaneously classify large datasets and reduce the effects of missing values. It is based on a multilevel framework of the cost-sensitive SVM and the expected maximization imputation method for missing values, which relies on iterated regression analyses. We compare classification results of multilevel SVM-based algorithms on public benchmark datasets with imbalanced classes and missing values as well as real data in health applications, and show that our multilevel SVM-based method produces fast, and more accurate and robust classification results.

  15. Tabu search approaches for the multi-level warehouse layout problem with adjacency constraints

    Science.gov (United States)

    Zhang, G. Q.; Lai, K. K.

    2010-08-01

    A new multi-level warehouse layout problem, the multi-level warehouse layout problem with adjacency constraints (MLWLPAC), is investigated. The same item type is required to be located in adjacent cells, and horizontal and vertical unit travel costs are product dependent. An integer programming model is proposed to formulate the problem, which is NP hard. Along with a cube-per-order index policy based heuristic, the standard tabu search (TS), greedy TS, and dynamic neighbourhood based TS are presented to solve the problem. The computational results show that the proposed approaches can reduce the transportation cost significantly.

  16. Simulation and Analysis of a Grid Connected Multi-level Converter Topologies and their Comparison

    Directory of Open Access Journals (Sweden)

    Mohammad Shadab Mirza

    2014-09-01

    Full Text Available This paper presents simulation and analysis of a grid connected multi-level converter topologies. In this paper, converter circuit works as an inverter by controlling the switching angle (α. This paper, presents a MATLAB/SIMULINK model of multi-level converter topologies (topology1 & topology2. Topology1 is without transformer while topology2 with transformer. Both the topologies are simulated and analyzed for three level converters in order to reduce the total harmonic distortion (THD. A comparative study of topology1 and topology2 is also presented in this paper for different switching angles (α and battery voltages. The results have been tabulated and discussed.

  17. A Container-based Trusted Multi-level Security Mechanism

    Directory of Open Access Journals (Sweden)

    Li Xiao-Yong

    2017-01-01

    Full Text Available Multi-level security mechanism has been widely applied in the military, government, defense and other domains in which information is required to be divided by security-level. Through this type of security mechanism, users at different security levels are provided with information at corresponding security levels. Traditional multi-level security mechanism which depends on the safety of operating system finally proved to be not practical. We propose a container-based trusted multi-level security mechanism in this paper to improve the applicability of the multi-level mechanism. It guarantees multi-level security of the system through a set of multi-level security policy rules and trusted techniques. The technical feasibility and application scenarios are also discussed. The ease of realization, strong practical significance and low cost of our method will largely expand the application of multi-level security mechanism in real life.

  18. Multi-level restricted maximum likelihood covariance estimation and kriging for large non-gridded spatial datasets

    KAUST Repository

    Castrillon, Julio

    2015-11-10

    We develop a multi-level restricted Gaussian maximum likelihood method for estimating the covariance function parameters and computing the best unbiased predictor. Our approach produces a new set of multi-level contrasts where the deterministic parameters of the model are filtered out thus enabling the estimation of the covariance parameters to be decoupled from the deterministic component. Moreover, the multi-level covariance matrix of the contrasts exhibit fast decay that is dependent on the smoothness of the covariance function. Due to the fast decay of the multi-level covariance matrix coefficients only a small set is computed with a level dependent criterion. We demonstrate our approach on problems of up to 512,000 observations with a Matérn covariance function and highly irregular placements of the observations. In addition, these problems are numerically unstable and hard to solve with traditional methods.

  19. Does the Organization Matter? A Multilevel Analysis of Organizational Effects in Homeless Service Innovations

    Science.gov (United States)

    Cronley, Courtney; Patterson, David A.

    2012-01-01

    This study examined the effects of organizational culture on staff members' use of management information systems ("N" = 142) within homeless service organizations ("N" = 24), using a multilevel model. The Organizational Social Context Questionnaire was used to measure organizational culture, defined by three sub-constructs: (1) proficiency, (2)…

  20. Multilevel Analyses of School and Children's Characteristics Associated with Physical Activity

    Science.gov (United States)

    Gomes, Thayse Natacha; dos Santos, Fernanda K.; Zhu, Weimo; Eisenmann, Joey; Maia, José A. R.

    2014-01-01

    Background: Children spend most of their awake time at school, and it is important to identify individual and school-level correlates of their physical activity (PA) levels. This study aimed to identify the between-school variability in Portuguese children PA and to investigate student and school PA correlates using multilevel modeling. Methods:…

  1. Fluid Intelligence as a Predictor of Learning: A Longitudinal Multilevel Approach Applied to Math

    Science.gov (United States)

    Primi, Ricardo; Ferrao, Maria Eugenia; Almeida, Leandro S.

    2010-01-01

    The association between fluid intelligence and inter-individual differences was investigated using multilevel growth curve modeling applied to data measuring intra-individual improvement on math achievement tests. A sample of 166 students (88 boys and 78 girls), ranging in age from 11 to 14 (M = 12.3, SD = 0.64), was tested. These individuals took…

  2. When Cannabis Is Available and Visible at School--A Multilevel Analysis of Students' Cannabis Use

    Science.gov (United States)

    Kuntsche, Emmanuel

    2010-01-01

    Aims: To investigate the links between the visibility of cannabis use in school (measured by teachers' reports of students being under the influence of cannabis on school premises), the proportion of cannabis users in the class, perceived availability of cannabis, as well as adolescent cannabis use. Methods: A multilevel regression model was…

  3. A Multilevel Network Study of the Effects of Delinquent Behavior on Friendship Evolution

    NARCIS (Netherlands)

    Snijders, T.A.B.; Baerveldt, Chris

    2003-01-01

    A multilevel approach is proposed to the study of the evolution of multiple networks. In this approach, the basic evolution process is assumed to be the same, while parameter values may differ between different networks. For the network evolution process, stochastic actor-oriented models are used,

  4. Multilevel Analysis of the Effects of Antidiscrimination Policies on Earnings by Sexual Orientation

    Science.gov (United States)

    Klawitter, Marieka

    2011-01-01

    This study uses the 2000 U.S. Census data to assess the impact of antidiscrimination policies for sexual orientation on earnings for gays and lesbians. Using a multilevel model allows estimation of the effects of state and local policies on earnings and of variation in the effects of sexual orientation across local labor markets. The results…

  5. Teamwork Satisfaction: Exploring the Multilevel Interaction of Teamwork Interest and Group Extraversion

    Science.gov (United States)

    French, Kimberly A.; Kottke, Janet L.

    2013-01-01

    Multilevel modeling is used to examine the impact of teamwork interest and group extraversion on group satisfaction. Participants included 206 undergraduates in 65 groups who were surveyed at the beginning and end of a requisite term-length group project for an upper-division university course. We hypothesized that teamwork interest and both…

  6. A Multilevel Analysis of Japanese Middle School Student and School Socioeconomic Status Influence on Mathematics Achievement

    Science.gov (United States)

    Takashiro, Naomi

    2017-01-01

    The author examined the simultaneous influence of Japanese middle school student and school socioeconomic status (SES) on student math achievement with two-level multilevel analysis models by utilizing the Trends in International Mathematics and Science Study (TIMSS) Japan data sets. The theoretical framework used in this study was…

  7. School Climate as a Predictor of Incivility and Bullying among Public School Employees: A Multilevel Analysis

    Science.gov (United States)

    Powell, Joshua E.; Powell, Anna L.; Petrosko, Joseph M.

    2015-01-01

    We surveyed public school educators on the workplace incivility and workplace bullying they experienced and obtained their ratings of the organizational climate of the school. We used multilevel modeling to determine the effects of individual-level and school-level predictors. Ratings of school climate were significantly related to incivility and…

  8. Pre- and Postnatal Women's Leisure Time Physical Activity Patterns: A Multilevel Longitudinal Analysis

    Science.gov (United States)

    Cramp, Anita G.; Bray, Steven R.

    2009-01-01

    The purpose of this study was to examine women's leisure time physical activity (LTPA) before pregnancy, during pregnancy, and through the first 7 months postnatal. Pre- and postnatal women (n = 309) completed the 12-month Modifiable Activity Questionnaire and demographic information. Multilevel modeling was used to estimate a growth curve…

  9. Parent Involvement and Science Achievement: A Cross-Classified Multilevel Latent Growth Curve Analysis

    Science.gov (United States)

    Johnson, Ursula Y.; Hull, Darrell M.

    2014-01-01

    The authors examined science achievement growth at Grades 3, 5, and 8 and parent school involvement at the same time points using the Early Childhood Longitudinal Study-Kindergarten Class of 1998-1999. Data were analyzed using cross-classified multilevel latent growth curve modeling with time invariant and varying covariates. School-based…

  10. Understanding the diversity of cooperation on innovation across countries: multilevel evidence from Europe

    Czech Academy of Sciences Publication Activity Database

    Srholec, Martin

    2015-01-01

    Roč. 24, 1-2 (2015), s. 159-182 ISSN 1043-8599 R&D Projects: GA ČR GAP402/10/2310 Institutional support: RVO:67985998 Keywords : innovation * cooperation * multilevel model Subject RIV: AH - Economics

  11. Predicting multi-level drug response with gene expression profile in multiple myeloma using hierarchical ordinal regression.

    Science.gov (United States)

    Zhang, Xinyan; Li, Bingzong; Han, Huiying; Song, Sha; Xu, Hongxia; Hong, Yating; Yi, Nengjun; Zhuang, Wenzhuo

    2018-05-10

    Multiple myeloma (MM), like other cancers, is caused by the accumulation of genetic abnormalities. Heterogeneity exists in the patients' response to treatments, for example, bortezomib. This urges efforts to identify biomarkers from numerous molecular features and build predictive models for identifying patients that can benefit from a certain treatment scheme. However, previous studies treated the multi-level ordinal drug response as a binary response where only responsive and non-responsive groups are considered. It is desirable to directly analyze the multi-level drug response, rather than combining the response to two groups. In this study, we present a novel method to identify significantly associated biomarkers and then develop ordinal genomic classifier using the hierarchical ordinal logistic model. The proposed hierarchical ordinal logistic model employs the heavy-tailed Cauchy prior on the coefficients and is fitted by an efficient quasi-Newton algorithm. We apply our hierarchical ordinal regression approach to analyze two publicly available datasets for MM with five-level drug response and numerous gene expression measures. Our results show that our method is able to identify genes associated with the multi-level drug response and to generate powerful predictive models for predicting the multi-level response. The proposed method allows us to jointly fit numerous correlated predictors and thus build efficient models for predicting the multi-level drug response. The predictive model for the multi-level drug response can be more informative than the previous approaches. Thus, the proposed approach provides a powerful tool for predicting multi-level drug response and has important impact on cancer studies.

  12. Domain decomposition and multilevel integration for fermions

    International Nuclear Information System (INIS)

    Ce, Marco; Giusti, Leonardo; Schaefer, Stefan

    2016-01-01

    The numerical computation of many hadronic correlation functions is exceedingly difficult due to the exponentially decreasing signal-to-noise ratio with the distance between source and sink. Multilevel integration methods, using independent updates of separate regions in space-time, are known to be able to solve such problems but have so far been available only for pure gauge theory. We present first steps into the direction of making such integration schemes amenable to theories with fermions, by factorizing a given observable via an approximated domain decomposition of the quark propagator. This allows for multilevel integration of the (large) factorized contribution to the observable, while its (small) correction can be computed in the standard way.

  13. Multilevel Monte Carlo in Approximate Bayesian Computation

    KAUST Repository

    Jasra, Ajay

    2017-02-13

    In the following article we consider approximate Bayesian computation (ABC) inference. We introduce a method for numerically approximating ABC posteriors using the multilevel Monte Carlo (MLMC). A sequential Monte Carlo version of the approach is developed and it is shown under some assumptions that for a given level of mean square error, this method for ABC has a lower cost than i.i.d. sampling from the most accurate ABC approximation. Several numerical examples are given.

  14. Multilevel resistive information storage and retrieval

    Science.gov (United States)

    Lohn, Andrew; Mickel, Patrick R.

    2016-08-09

    The present invention relates to resistive random-access memory (RRAM or ReRAM) systems, as well as methods of employing multiple state variables to form degenerate states in such memory systems. The methods herein allow for precise write and read steps to form multiple state variables, and these steps can be performed electrically. Such an approach allows for multilevel, high density memory systems with enhanced information storage capacity and simplified information retrieval.

  15. Multilevel predictors of adolescent physical activity: a longitudinal analysis

    Directory of Open Access Journals (Sweden)

    Hearst Mary O

    2012-02-01

    Full Text Available Abstract Background To examine how factors from a social ecologic model predict physical activity (PA among adolescents using a longitudinal analysis. Methods Participants in this longitudinal study were adolescents (ages 10-16 at baseline and one parent enrolled in the Transdisciplinary Research on Energetics and Cancer-Identifying Determinants of Eating and Activity (TREC-IDEA and the Etiology of Childhood Obesity (ECHO. Both studies were designed to assess a socio-ecologic model of adolescent obesity risk. PA was collected using ActiGraph activity monitors at two time points 24 months apart. Other measures included objective height and weight, adolescent and parent questionnaires on multilevel psychological, behavioral and social determinants of PA, and a home PA equipment inventory. Analysis was conducted using SAS, including descriptive characteristics, bivariate and stepped multivariate mixed models, using baseline adjustment. Models were stratified by gender. Results There were 578 adolescents with complete data. Results suggest few statistically significant longitudinal associations with physical activity measured as minutes of MVPA or total counts from accelerometers. For boys, greater self-efficacy (B = 0.75, p = 0.01 and baseline MVPA (B = 0.55, p p = 0.01 and barriers (B = -0.32, p = 0.05 significantly predicted MVPA at follow-up in the full model. The full multilevel model explained 30% of the variance in PA among boys and 24% among girls. Conclusions PA change in adolescents is a complex issue that is not easily understood. Our findings suggest early PA habits are the most important predictor of PA levels in adolescence. Intervention may be necessary prior to middle school to maintain PA through adolescence.

  16. Empowering leaders optimize working conditions for engagement: a multilevel study.

    Science.gov (United States)

    Tuckey, Michelle R; Bakker, Arnold B; Dollard, Maureen F

    2012-01-01

    Using a multilevel framework, this study examined the role of empowering leadership at the group level by fire brigade captains in facilitating the individual level motivational processes that underpin work engagement in volunteer firefighters. Anonymous mail surveys were completed by 540 volunteer firefighters from 68 fire brigades and, separately, by 68 brigade captains. As predicted on the basis of the Job Demands-Resources model, increased levels of cognitive demands and cognitive resources partially mediated the relationship between empowering leadership and work engagement. In a three-way Leadership × Demands × Resources interaction, empowering leadership also had the effect of optimizing working conditions for engagement by strengthening the positive effect of a work context in which both cognitive demands and cognitive resources were high. Our findings shed light on a process through which leaders can empower workers and enhance well-being: via their influence on and interaction with the work environment. They also underscore the need to examine work engagement from a multilevel theoretical perspective.

  17. Multilevel sparse functional principal component analysis.

    Science.gov (United States)

    Di, Chongzhi; Crainiceanu, Ciprian M; Jank, Wolfgang S

    2014-01-29

    We consider analysis of sparsely sampled multilevel functional data, where the basic observational unit is a function and data have a natural hierarchy of basic units. An example is when functions are recorded at multiple visits for each subject. Multilevel functional principal component analysis (MFPCA; Di et al. 2009) was proposed for such data when functions are densely recorded. Here we consider the case when functions are sparsely sampled and may contain only a few observations per function. We exploit the multilevel structure of covariance operators and achieve data reduction by principal component decompositions at both between and within subject levels. We address inherent methodological differences in the sparse sampling context to: 1) estimate the covariance operators; 2) estimate the functional principal component scores; 3) predict the underlying curves. Through simulations the proposed method is able to discover dominating modes of variations and reconstruct underlying curves well even in sparse settings. Our approach is illustrated by two applications, the Sleep Heart Health Study and eBay auctions.

  18. The Differences between Multilevel Marketing and the Financial Pyramids or “Pyramid Scheme”

    Directory of Open Access Journals (Sweden)

    Vanessa Braga Santos

    2017-06-01

    Full Text Available This research aims to analyze and understand the difference between the concept of Multilevel Marketing and the Financial Pyramids. The main objective of this work is to clarify the differences between these two business models that are growing worldwide and also present concepts that show the success of professionals in this kind of new business model. Multilevel Marketing shows a sustainable system, a direct selling business that includes recruiting distributors with a profit share and also by recruiting new members. In the Financial Pyramid concept, the problem is that business support is the network itself, and often there are no products to be commercialized, so this model is unsustainable and considered as an illegal business in several countries, including Brazil. Within this approach, a case study was conducted with one of the largest Multilevel Marketing companies in the world, Mary Kay. We conducted a direct interview with one of Mary Kay Independent Sales Directors from the city of Piracicaba, held in October 2016, and collected data surveys from the internet. The markets today are based on moving products, so we concluded that Multilevel Marketing is a great business opportunity to make an extra income by marketing services and products.

  19. Application of Hierarchical Linear Models/Linear Mixed-Effects Models in School Effectiveness Research

    Science.gov (United States)

    Ker, H. W.

    2014-01-01

    Multilevel data are very common in educational research. Hierarchical linear models/linear mixed-effects models (HLMs/LMEs) are often utilized to analyze multilevel data nowadays. This paper discusses the problems of utilizing ordinary regressions for modeling multilevel educational data, compare the data analytic results from three regression…

  20. Multi-level damage identification with response reconstruction

    Science.gov (United States)

    Zhang, Chao-Dong; Xu, You-Lin

    2017-10-01

    Damage identification through finite element (FE) model updating usually forms an inverse problem. Solving the inverse identification problem for complex civil structures is very challenging since the dimension of potential damage parameters in a complex civil structure is often very large. Aside from enormous computation efforts needed in iterative updating, the ill-condition and non-global identifiability features of the inverse problem probably hinder the realization of model updating based damage identification for large civil structures. Following a divide-and-conquer strategy, a multi-level damage identification method is proposed in this paper. The entire structure is decomposed into several manageable substructures and each substructure is further condensed as a macro element using the component mode synthesis (CMS) technique. The damage identification is performed at two levels: the first is at macro element level to locate the potentially damaged region and the second is over the suspicious substructures to further locate as well as quantify the damage severity. In each level's identification, the damage searching space over which model updating is performed is notably narrowed down, not only reducing the computation amount but also increasing the damage identifiability. Besides, the Kalman filter-based response reconstruction is performed at the second level to reconstruct the response of the suspicious substructure for exact damage quantification. Numerical studies and laboratory tests are both conducted on a simply supported overhanging steel beam for conceptual verification. The results demonstrate that the proposed multi-level damage identification via response reconstruction does improve the identification accuracy of damage localization and quantization considerably.