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Sample records for model structural equation

  1. Regularized Structural Equation Modeling.

    Science.gov (United States)

    Jacobucci, Ross; Grimm, Kevin J; McArdle, John J

    A new method is proposed that extends the use of regularization in both lasso and ridge regression to structural equation models. The method is termed regularized structural equation modeling (RegSEM). RegSEM penalizes specific parameters in structural equation models, with the goal of creating easier to understand and simpler models. Although regularization has gained wide adoption in regression, very little has transferred to models with latent variables. By adding penalties to specific parameters in a structural equation model, researchers have a high level of flexibility in reducing model complexity, overcoming poor fitting models, and the creation of models that are more likely to generalize to new samples. The proposed method was evaluated through a simulation study, two illustrative examples involving a measurement model, and one empirical example involving the structural part of the model to demonstrate RegSEM's utility.

  2. Structural Equation Model Trees

    Science.gov (United States)

    Brandmaier, Andreas M.; von Oertzen, Timo; McArdle, John J.; Lindenberger, Ulman

    2013-01-01

    In the behavioral and social sciences, structural equation models (SEMs) have become widely accepted as a modeling tool for the relation between latent and observed variables. SEMs can be seen as a unification of several multivariate analysis techniques. SEM Trees combine the strengths of SEMs and the decision tree paradigm by building tree…

  3. Handbook of structural equation modeling

    CERN Document Server

    Hoyle, Rick H

    2012-01-01

    The first comprehensive structural equation modeling (SEM) handbook, this accessible volume presents both the mechanics of SEM and specific SEM strategies and applications. The editor, contributors, and editorial advisory board are leading methodologists who have organized the book to move from simpler material to more statistically complex modeling approaches. Sections cover the foundations of SEM; statistical underpinnings, from assumptions to model modifications; steps in implementation, from data preparation through writing the SEM report; and basic and advanced applications, inclu

  4. Structural Equation Modeling of Travel Choice Dynamics

    OpenAIRE

    Golob, Thomas F.

    1988-01-01

    This research has two objectives. The first objective is to explore the use of the modeling tool called "latent structural equations" (structural equations with latent variables) in the general field of travel behavior analysis and the more specific field of dynamic analysis of travel behavior. The second objective is to apply a latent structural equation model in order to determine the causal relationships between income, car ownership, and mobility. Many transportation researchers ...

  5. Structural Equation Modeling of Multivariate Time Series

    Science.gov (United States)

    du Toit, Stephen H. C.; Browne, Michael W.

    2007-01-01

    The covariance structure of a vector autoregressive process with moving average residuals (VARMA) is derived. It differs from other available expressions for the covariance function of a stationary VARMA process and is compatible with current structural equation methodology. Structural equation modeling programs, such as LISREL, may therefore be…

  6. A first course in structural equation modeling

    CERN Document Server

    Raykov, Tenko

    2012-01-01

    In this book, authors Tenko Raykov and George A. Marcoulides introduce students to the basics of structural equation modeling (SEM) through a conceptual, nonmathematical approach. For ease of understanding, the few mathematical formulas presented are used in a conceptual or illustrative nature, rather than a computational one.Featuring examples from EQS, LISREL, and Mplus, A First Course in Structural Equation Modeling is an excellent beginner's guide to learning how to set up input files to fit the most commonly used types of structural equation models with these programs. The basic ideas and methods for conducting SEM are independent of any particular software.Highlights of the Second Edition include: Review of latent change (growth) analysis models at an introductory level Coverage of the popular Mplus program Updated examples of LISREL and EQS A CD that contains all of the text's LISREL, EQS, and Mplus examples.A First Course in Structural Equation Modeling is intended as an introductory book for students...

  7. Structural Equation Modeling in Special Education Research.

    Science.gov (United States)

    Moore, Alan D.

    1995-01-01

    This article suggests the use of structural equation modeling in special education research, to analyze multivariate data from both nonexperimental and experimental research. It combines a structural model linking latent variables and a measurement model linking observed variables with latent variables. (Author/DB)

  8. Linear causal modeling with structural equations

    CERN Document Server

    Mulaik, Stanley A

    2009-01-01

    Emphasizing causation as a functional relationship between variables that describe objects, Linear Causal Modeling with Structural Equations integrates a general philosophical theory of causation with structural equation modeling (SEM) that concerns the special case of linear causal relations. In addition to describing how the functional relation concept may be generalized to treat probabilistic causation, the book reviews historical treatments of causation and explores recent developments in experimental psychology on studies of the perception of causation. It looks at how to perceive causal

  9. Structural equation modeling methods and applications

    CERN Document Server

    Wang, Jichuan

    2012-01-01

    A reference guide for applications of SEM using Mplus Structural Equation Modeling: Applications Using Mplus is intended as both a teaching resource and a reference guide. Written in non-mathematical terms, this book focuses on the conceptual and practical aspects of Structural Equation Modeling (SEM). Basic concepts and examples of various SEM models are demonstrated along with recently developed advanced methods, such as mixture modeling and model-based power analysis and sample size estimate for SEM. The statistical modeling program, Mplus, is also featured and provides researchers with a

  10. Global identifiability of linear structural equation models

    CERN Document Server

    Drton, Mathias; Sullivant, Seth

    2010-01-01

    Structural equation models are multivariate statistical models that are defined by specifying noisy functional relationships among random variables. We consider the classical case of linear relationships and additive Gaussian noise terms. We give a necessary and sufficient condition for global identifiability of the model in terms of a mixed graph encoding the linear structural equations and the correlation structure of the error terms. Global identifiability is understood to mean injectivity of the parametrization of the model and is fundamental in particular for applicability of standard statistical methodology.

  11. Multiplicity Control in Structural Equation Modeling

    Science.gov (United States)

    Cribbie, Robert A.

    2007-01-01

    Researchers conducting structural equation modeling analyses rarely, if ever, control for the inflated probability of Type I errors when evaluating the statistical significance of multiple parameters in a model. In this study, the Type I error control, power and true model rates of famsilywise and false discovery rate controlling procedures were…

  12. Basics of Structural Equation Modeling

    CERN Document Server

    Maruyama, Dr Geoffrey M

    1997-01-01

    With the availability of software programs, such as LISREL, EQS, and AMOS, modeling (SEM) techniques have become a popular tool for formalized presentation of the hypothesized relationships underlying correlational research and test for the plausibility of hypothesizing for a particular data set. Through the use of careful narrative explanation, Maruyama's text describes the logic underlying SEM approaches, describes how SEM approaches relate to techniques like regression and factor analysis, analyzes the strengths and shortcomings of SEM as compared to alternative methodologies, and explores

  13. Advanced structural equation modeling issues and techniques

    CERN Document Server

    Marcoulides, George A

    2013-01-01

    By focusing primarily on the application of structural equation modeling (SEM) techniques in example cases and situations, this book provides an understanding and working knowledge of advanced SEM techniques with a minimum of mathematical derivations. The book was written for a broad audience crossing many disciplines, assumes an understanding of graduate level multivariate statistics, including an introduction to SEM.

  14. Structural Equation Modeling in Rehabilitation Counseling Research

    Science.gov (United States)

    Chan, Fong; Lee, Gloria K.; Lee, Eun-Jeong; Kubota, Coleen; Allen, Chase A.

    2007-01-01

    Structural equation modeling (SEM) has become increasingly popular in counseling, psychology, and rehabilitation research. The purpose of this article is to provide an overview of the basic concepts and applications of SEM in rehabilitation counseling research using the AMOS statistical software program.

  15. Principles and practice of structural equation modeling

    CERN Document Server

    Kline, Rex B

    2015-01-01

    Emphasizing concepts and rationale over mathematical minutiae, this is the most widely used, complete, and accessible structural equation modeling (SEM) text. Continuing the tradition of using real data examples from a variety of disciplines, the significantly revised fourth edition incorporates recent developments such as Pearl's graphing theory and the structural causal model (SCM), measurement invariance, and more. Readers gain a comprehensive understanding of all phases of SEM, from data collection and screening to the interpretation and reporting of the results. Learning is enhanced by ex

  16. Structural equation modeling for observational studies

    Science.gov (United States)

    Grace, J.B.

    2008-01-01

    Structural equation modeling (SEM) represents a framework for developing and evaluating complex hypotheses about systems. This method of data analysis differs from conventional univariate and multivariate approaches familiar to most biologists in several ways. First, SEMs are multiequational and capable of representing a wide array of complex hypotheses about how system components interrelate. Second, models are typically developed based on theoretical knowledge and designed to represent competing hypotheses about the processes responsible for data structure. Third, SEM is conceptually based on the analysis of covariance relations. Most commonly, solutions are obtained using maximum-likelihood solution procedures, although a variety of solution procedures are used, including Bayesian estimation. Numerous extensions give SEM a very high degree of flexibility in dealing with nonnormal data, categorical responses, latent variables, hierarchical structure, multigroup comparisons, nonlinearities, and other complicating factors. Structural equation modeling allows researchers to address a variety of questions about systems, such as how different processes work in concert, how the influences of perturbations cascade through systems, and about the relative importance of different influences. I present 2 example applications of SEM, one involving interactions among lynx (Lynx pardinus), mongooses (Herpestes ichneumon), and rabbits (Oryctolagus cuniculus), and the second involving anuran species richness. Many wildlife ecologists may find SEM useful for understanding how populations function within their environments. Along with the capability of the methodology comes a need for care in the proper application of SEM.

  17. Meta-analytic structural equation modelling

    CERN Document Server

    Jak, Suzanne

    2015-01-01

    This book explains how to employ MASEM, the combination of meta-analysis (MA) and structural equation modelling (SEM). It shows how by using MASEM, a single model can be tested to explain the relationships between a set of variables in several studies. This book gives an introduction to MASEM, with a focus on the state of the art approach: the two stage approach of Cheung and Cheung & Chan. Both, the fixed and the random approach to MASEM are illustrated with two applications to real data. All steps that have to be taken to perform the analyses are discussed extensively. All data and syntax files are available online, so that readers can imitate all analyses. By using SEM for meta-analysis, this book shows how to benefit from all available information from all available studies, even if few or none of the studies report about all relationships that feature in the full model of interest.

  18. Applying Meta-Analysis to Structural Equation Modeling

    Science.gov (United States)

    Hedges, Larry V.

    2016-01-01

    Structural equation models play an important role in the social sciences. Consequently, there is an increasing use of meta-analytic methods to combine evidence from studies that estimate the parameters of structural equation models. Two approaches are used to combine evidence from structural equation models: A direct approach that combines…

  19. Bayesian Data-Model Fit Assessment for Structural Equation Modeling

    Science.gov (United States)

    Levy, Roy

    2011-01-01

    Bayesian approaches to modeling are receiving an increasing amount of attention in the areas of model construction and estimation in factor analysis, structural equation modeling (SEM), and related latent variable models. However, model diagnostics and model criticism remain relatively understudied aspects of Bayesian SEM. This article describes…

  20. Structural equation models from paths to networks

    CERN Document Server

    Westland, J Christopher

    2015-01-01

    This compact reference surveys the full range of available structural equation modeling (SEM) methodologies.  It reviews applications in a broad range of disciplines, particularly in the social sciences where many key concepts are not directly observable.  This is the first book to present SEM’s development in its proper historical context–essential to understanding the application, strengths and weaknesses of each particular method.  This book also surveys the emerging path and network approaches that complement and enhance SEM, and that will grow in importance in the near future.  SEM’s ability to accommodate unobservable theory constructs through latent variables is of significant importance to social scientists.  Latent variable theory and application are comprehensively explained, and methods are presented for extending their power, including guidelines for data preparation, sample size calculation, and the special treatment of Likert scale data.  Tables of software, methodologies and fit st...

  1. Virtuous organization: A structural equation modeling approach

    Directory of Open Access Journals (Sweden)

    Majid Zamahani

    2013-02-01

    Full Text Available For years, the idea of virtue was unfavorable among researchers and virtues were traditionally considered as culture-specific, relativistic and they were supposed to be associated with social conservatism, religious or moral dogmatism, and scientific irrelevance. Virtue and virtuousness have been recently considered seriously among organizational researchers. The proposed study of this paper examines the relationships between leadership, organizational culture, human resource, structure and processes, care for community and virtuous organization. Structural equation modeling is employed to investigate the effects of each variable on other components. The data used in this study consists of questionnaire responses from employees in Payam e Noor University in Yazd province. A total of 250 questionnaires were sent out and a total of 211 valid responses were received. Our results have revealed that all the five variables have positive and significant impacts on virtuous organization. Among the five variables, organizational culture has the most direct impact (0.80 and human resource has the most total impact (0.844 on virtuous organization.

  2. On the Use of Structural Equation Models in Marketing Modeling

    NARCIS (Netherlands)

    Steenkamp, J.E.B.M.; Baumgartner, H.

    2000-01-01

    We reflect on the role of structural equation modeling (SEM) in marketing modeling and managerial decision making. We discuss some benefits provided by SEM and alert marketing modelers to several recent developments in SEM in three areas: measurement analysis, analysis of cross-sectional data, and a

  3. Fitting ARMA Time Series by Structural Equation Models.

    Science.gov (United States)

    van Buuren, Stef

    1997-01-01

    This paper outlines how the stationary ARMA (p,q) model (G. Box and G. Jenkins, 1976) can be specified as a structural equation model. Maximum likelihood estimates for the parameters in the ARMA model can be obtained by software for fitting structural equation models. The method is applied to three problem types. (SLD)

  4. The General Linear Model as Structural Equation Modeling

    Science.gov (United States)

    Graham, James M.

    2008-01-01

    Statistical procedures based on the general linear model (GLM) share much in common with one another, both conceptually and practically. The use of structural equation modeling path diagrams as tools for teaching the GLM as a body of connected statistical procedures is presented. A heuristic data set is used to demonstrate a variety of univariate…

  5. USING STRUCTURAL EQUATION MODELING TO INVESTIGATE RELATIONSHIPS AMONG ECOLOGICAL VARIABLES

    Science.gov (United States)

    This paper gives an introductory account of Structural Equation Modeling (SEM) and demonstrates its application using LISRELmodel utilizing environmental data. Using nine EMAP data variables, we analyzed their correlation matrix with an SEM model. The model characterized...

  6. A Structural Equation Modeling Analysis of Influences on Juvenile Delinquency

    Science.gov (United States)

    Barrett, David E.; Katsiyannis, Antonis; Zhang, Dalun; Zhang, Dake

    2014-01-01

    This study examined influences on delinquency and recidivism using structural equation modeling. The sample comprised 199,204 individuals: 99,602 youth whose cases had been processed by the South Carolina Department of Juvenile Justice and a matched control group of 99,602 youth without juvenile records. Structural equation modeling for the…

  7. Reporting Monte Carlo Studies in Structural Equation Modeling

    NARCIS (Netherlands)

    Boomsma, Anne

    2013-01-01

    In structural equation modeling, Monte Carlo simulations have been used increasingly over the last two decades, as an inventory from the journal Structural Equation Modeling illustrates. Reaching out to a broad audience, this article provides guidelines for reporting Monte Carlo studies in that fiel

  8. Meta-analysis a structural equation modeling approach

    CERN Document Server

    Cheung, Mike W-L

    2015-01-01

    Presents a novel approach to conducting meta-analysis using structural equation modeling. Structural equation modeling (SEM) and meta-analysis are two powerful statistical methods in the educational, social, behavioral, and medical sciences. They are often treated as two unrelated topics in the literature. This book presents a unified framework on analyzing meta-analytic data within the SEM framework, and illustrates how to conduct meta-analysis using the metaSEM package in the R statistical environment. Meta-Analysis: A Structural Equation Modeling Approach begins by introducing the impo

  9. Introduction to Structural Equation Modelling Using SPSS and Amos

    CERN Document Server

    Blunch, Niels J

    2008-01-01

    . Introduction to Structural Equation Modelling using SPSS and AMOS is a complete guide to carrying out your own structural equation modelling project. Assuming no previous experience of the subject, and a minimum of mathematical knowledge, this is the ideal guide for those new to structural equation modelling (SEM). Each chapter begins with learning objectives, and ends with a list of the new concepts introduced and questions to open up further discussion. Exercises for each chapter, incuding the necessary data, can be downloaded from the book's website. Helpful real life examples are include

  10. A Bayesian modeling approach for generalized semiparametric structural equation models.

    Science.gov (United States)

    Song, Xin-Yuan; Lu, Zhao-Hua; Cai, Jing-Heng; Ip, Edward Hak-Sing

    2013-10-01

    In behavioral, biomedical, and psychological studies, structural equation models (SEMs) have been widely used for assessing relationships between latent variables. Regression-type structural models based on parametric functions are often used for such purposes. In many applications, however, parametric SEMs are not adequate to capture subtle patterns in the functions over the entire range of the predictor variable. A different but equally important limitation of traditional parametric SEMs is that they are not designed to handle mixed data types-continuous, count, ordered, and unordered categorical. This paper develops a generalized semiparametric SEM that is able to handle mixed data types and to simultaneously model different functional relationships among latent variables. A structural equation of the proposed SEM is formulated using a series of unspecified smooth functions. The Bayesian P-splines approach and Markov chain Monte Carlo methods are developed to estimate the smooth functions and the unknown parameters. Moreover, we examine the relative benefits of semiparametric modeling over parametric modeling using a Bayesian model-comparison statistic, called the complete deviance information criterion (DIC). The performance of the developed methodology is evaluated using a simulation study. To illustrate the method, we used a data set derived from the National Longitudinal Survey of Youth.

  11. An Overview on R Packages for Structural Equation Modeling

    Directory of Open Access Journals (Sweden)

    Haibin Qiu

    2014-05-01

    Full Text Available The aim of this study is to present overview on R packages for structural equation modeling. Structural equation modeling, a statistical technique for testing and estimating causal relations using an amalgamation of statistical data and qualitative causal hypotheses, allow both confirmatory and exploratory modeling, meaning they are matched to both hypothesis testing and theory development. R project or R language, a free and popular programming language and computer software surroundings for statistical computing and graphics, is popularly used among statisticians for developing statistical computer software and data analysis. The major finding is that it is necessary to build excellent and enough structural equation modeling packages for R users to do research. Numerous packages for structural equation modeling of R project are introduced in this study and most of them are enclosed in the Comprehensive R Archive Network task view Psychometrics.

  12. A Framework for Structural Equation Models in General Pedigrees

    National Research Council Canada - National Science Library

    Morris, Nathan J; Elston, Robert C; Stein, Catherine M

    Background/Aims: Structural Equation Modeling (SEM) is an analysis approach that accounts for both the causal relationships between variables and the errors associated with the measurement of these variables...

  13. Evaluation of model fit in nonlinear multilevel structural equation modeling

    Directory of Open Access Journals (Sweden)

    Karin eSchermelleh-Engel

    2014-03-01

    Full Text Available Evaluating model fit in nonlinear multilevel structural equation models (MSEM presents a challenge as no adequate test statistic is available. Nevertheless, using a product indicator approach a likelihood ratio test for linear models is provided which may also be useful for nonlinear MSEM. The main problem with nonlinear models is that product variables are nonnormally distributed. Although robust test statistics have been developed for linear SEM to ensure valid results under the condition of nonnormality, they were not yet investigated for nonlinear MSEM. In a Monte Carlo study, the performance of the robust likelihood ratio test was investigated for models with single-level latent interaction effects using the unconstrained product indicator approach. As overall model fit evaluation has a potential limitation in detecting the lack of fit at a single level even for linear models, level-specific model fit evaluation was also investigated using partially saturated models. Four population models were considered: a model with interaction effects at both levels, an interaction effect at the within-group level, an interaction effect at the between-group level, and a model with no interaction effects at both levels. For these models the number of groups, predictor correlation, and model misspecification was varied. The results indicate that the robust test statistic performed sufficiently well. Advantages of level-specific model fit evaluation for the detection of model misfit are demonstrated.

  14. Evaluation of model fit in nonlinear multilevel structural equation modeling.

    Science.gov (United States)

    Schermelleh-Engel, Karin; Kerwer, Martin; Klein, Andreas G

    2014-01-01

    Evaluating model fit in nonlinear multilevel structural equation models (MSEM) presents a challenge as no adequate test statistic is available. Nevertheless, using a product indicator approach a likelihood ratio test for linear models is provided which may also be useful for nonlinear MSEM. The main problem with nonlinear models is that product variables are non-normally distributed. Although robust test statistics have been developed for linear SEM to ensure valid results under the condition of non-normality, they have not yet been investigated for nonlinear MSEM. In a Monte Carlo study, the performance of the robust likelihood ratio test was investigated for models with single-level latent interaction effects using the unconstrained product indicator approach. As overall model fit evaluation has a potential limitation in detecting the lack of fit at a single level even for linear models, level-specific model fit evaluation was also investigated using partially saturated models. Four population models were considered: a model with interaction effects at both levels, an interaction effect at the within-group level, an interaction effect at the between-group level, and a model with no interaction effects at both levels. For these models the number of groups, predictor correlation, and model misspecification was varied. The results indicate that the robust test statistic performed sufficiently well. Advantages of level-specific model fit evaluation for the detection of model misfit are demonstrated.

  15. Structural equation modeling: building and evaluating causal models: Chapter 8

    Science.gov (United States)

    Grace, James B.; Scheiner, Samuel M.; Schoolmaster, Donald R.

    2015-01-01

    Scientists frequently wish to study hypotheses about causal relationships, rather than just statistical associations. This chapter addresses the question of how scientists might approach this ambitious task. Here we describe structural equation modeling (SEM), a general modeling framework for the study of causal hypotheses. Our goals are to (a) concisely describe the methodology, (b) illustrate its utility for investigating ecological systems, and (c) provide guidance for its application. Throughout our presentation, we rely on a study of the effects of human activities on wetland ecosystems to make our description of methodology more tangible. We begin by presenting the fundamental principles of SEM, including both its distinguishing characteristics and the requirements for modeling hypotheses about causal networks. We then illustrate SEM procedures and offer guidelines for conducting SEM analyses. Our focus in this presentation is on basic modeling objectives and core techniques. Pointers to additional modeling options are also given.

  16. Applying meta-analysis to structural equation modeling.

    Science.gov (United States)

    Hedges, Larry V

    2016-06-01

    Structural equation models play an important role in the social sciences. Consequently, there is an increasing use of meta-analytic methods to combine evidence from studies that estimate the parameters of structural equation models. Two approaches are used to combine evidence from structural equation models: A direct approach that combines structural coefficients and an indirect approach that first combines correlation matrices and estimates structural coefficients from the combined correlation matrix. When there is no heterogeneity across studies, direct estimates of structural coefficients from several studies is an appealing approach. Heterogeneity of correlation matrices across studies presents both practical and conceptual problems. An alternative approach to heterogeneity is suggested as an example of how to better handle heterogeneity in this context. Copyright © 2016 John Wiley & Sons, Ltd.

  17. Partial Least Squares Structural Equation Modeling with R

    Science.gov (United States)

    Ravand, Hamdollah; Baghaei, Purya

    2016-01-01

    Structural equation modeling (SEM) has become widespread in educational and psychological research. Its flexibility in addressing complex theoretical models and the proper treatment of measurement error has made it the model of choice for many researchers in the social sciences. Nevertheless, the model imposes some daunting assumptions and…

  18. Finite Feedback Cycling in Structural Equation Models

    Science.gov (United States)

    Hayduk, Leslie A.

    2009-01-01

    In models containing reciprocal effects, or longer causal loops, the usual effect estimates assume that any effect touching a loop initiates an infinite cycling of effects around that loop. The real world, in contrast, might permit only finite feedback cycles. I use a simple hypothetical model to demonstrate that if the world permits only a few…

  19. Update to Core reporting practices in structural equation modeling.

    Science.gov (United States)

    Schreiber, James B

    2016-07-21

    This paper is a technical update to "Core Reporting Practices in Structural Equation Modeling."(1) As such, the content covered in this paper includes, sample size, missing data, specification and identification of models, estimation method choices, fit and residual concerns, nested, alternative, and equivalent models, and unique issues within the SEM family of techniques.

  20. Structural Equation Modeling Diagnostics Using R Package Semdiag and EQS

    Science.gov (United States)

    Yuan, Ke-Hai; Zhang, Zhiyong

    2012-01-01

    Yuan and Hayashi (2010) introduced 2 scatter plots for model and data diagnostics in structural equation modeling (SEM). However, the generation of the plots requires in-depth understanding of their underlying technical details. This article develops and introduces an R package semdiag for easily drawing the 2 plots. With a model specified in EQS…

  1. Hopes and Cautions in Implementing Bayesian Structural Equation Modeling

    Science.gov (United States)

    MacCallum, Robert C.; Edwards, Michael C.; Cai, Li

    2012-01-01

    Muthen and Asparouhov (2012) have proposed and demonstrated an approach to model specification and estimation in structural equation modeling (SEM) using Bayesian methods. Their contribution builds on previous work in this area by (a) focusing on the translation of conventional SEM models into a Bayesian framework wherein parameters fixed at zero…

  2. Advanced Applications of Structural Equation Modeling in Counseling Psychology Research

    Science.gov (United States)

    Martens, Matthew P.; Haase, Richard F.

    2006-01-01

    Structural equation modeling (SEM) is a data-analytic technique that allows researchers to test complex theoretical models. Most published applications of SEM involve analyses of cross-sectional recursive (i.e., unidirectional) models, but it is possible for researchers to test more complex designs that involve variables observed at multiple…

  3. A Structural Equation Approach to Models with Spatial Dependence

    NARCIS (Netherlands)

    Oud, J.H.L.; Folmer, H.

    2008-01-01

    We introduce the class of structural equation models (SEMs) and corresponding estimation procedures into a spatial dependence framework. SEM allows both latent and observed variables within one and the same (causal) model. Compared with models with observed variables only, this feature makes it poss

  4. A structural equation approach to models with spatial dependence

    NARCIS (Netherlands)

    Oud, J.H.L.; Folmer, H.

    2008-01-01

    We introduce the class of structural equation models (SEMs) and corresponding estimation procedures into a spatial dependence framework. SEM allows both latent and observed variables within one and the same (causal) model. Compared with models with observed variables only, this feature makes it poss

  5. Bayesian structural equation modeling method for hierarchical model validation

    Energy Technology Data Exchange (ETDEWEB)

    Jiang Xiaomo [Department of Civil and Environmental Engineering, Vanderbilt University, Box 1831-B, Nashville, TN 37235 (United States)], E-mail: xiaomo.jiang@vanderbilt.edu; Mahadevan, Sankaran [Department of Civil and Environmental Engineering, Vanderbilt University, Box 1831-B, Nashville, TN 37235 (United States)], E-mail: sankaran.mahadevan@vanderbilt.edu

    2009-04-15

    A building block approach to model validation may proceed through various levels, such as material to component to subsystem to system, comparing model predictions with experimental observations at each level. Usually, experimental data becomes scarce as one proceeds from lower to higher levels. This paper presents a structural equation modeling approach to make use of the lower-level data for higher-level model validation under uncertainty, integrating several components: lower-level data, higher-level data, computational model, and latent variables. The method proposed in this paper uses latent variables to model two sets of relationships, namely, the computational model to system-level data, and lower-level data to system-level data. A Bayesian network with Markov chain Monte Carlo simulation is applied to represent the two relationships and to estimate the influencing factors between them. Bayesian hypothesis testing is employed to quantify the confidence in the predictive model at the system level, and the role of lower-level data in the model validation assessment at the system level. The proposed methodology is implemented for hierarchical assessment of three validation problems, using discrete observations and time-series data.

  6. Maximum Likelihood Estimation in Meta-Analytic Structural Equation Modeling

    Science.gov (United States)

    Oort, Frans J.; Jak, Suzanne

    2016-01-01

    Meta-analytic structural equation modeling (MASEM) involves fitting models to a common population correlation matrix that is estimated on the basis of correlation coefficients that are reported by a number of independent studies. MASEM typically consist of two stages. The method that has been found to perform best in terms of statistical…

  7. Analyzing Mixed-Dyadic Data Using Structural Equation Models

    Science.gov (United States)

    Peugh, James L.; DiLillo, David; Panuzio, Jillian

    2013-01-01

    Mixed-dyadic data, collected from distinguishable (nonexchangeable) or indistinguishable (exchangeable) dyads, require statistical analysis techniques that model the variation within dyads and between dyads appropriately. The purpose of this article is to provide a tutorial for performing structural equation modeling analyses of cross-sectional…

  8. Multiplicity Control in Structural Equation Modeling: Incorporating Parameter Dependencies

    Science.gov (United States)

    Smith, Carrie E.; Cribbie, Robert A.

    2013-01-01

    When structural equation modeling (SEM) analyses are conducted, significance tests for all important model relationships (parameters including factor loadings, covariances, etc.) are typically conducted at a specified nominal Type I error rate ([alpha]). Despite the fact that many significance tests are often conducted in SEM, rarely is…

  9. A Note on Structural Equation Modeling Estimates of Reliability

    Science.gov (United States)

    Yang, Yanyun; Green, Samuel B.

    2010-01-01

    Reliability can be estimated using structural equation modeling (SEM). Two potential problems with this approach are that estimates may be unstable with small sample sizes and biased with misspecified models. A Monte Carlo study was conducted to investigate the quality of SEM estimates of reliability by themselves and relative to coefficient…

  10. A Structural Equation Model of Expertise in College Physics

    Science.gov (United States)

    Taasoobshirazi, Gita; Carr, Martha

    2009-01-01

    A model of expertise in physics was tested on a sample of 374 college students in 2 different level physics courses. Structural equation modeling was used to test hypothesized relationships among variables linked to expert performance in physics including strategy use, pictorial representation, categorization skills, and motivation, and these…

  11. A Structural Equation Model for Predicting Business Student Performance

    Science.gov (United States)

    Pomykalski, James J.; Dion, Paul; Brock, James L.

    2008-01-01

    In this study, the authors developed a structural equation model that accounted for 79% of the variability of a student's final grade point average by using a sample size of 147 students. The model is based on student grades in 4 foundational business courses: introduction to business, macroeconomics, statistics, and using databases. Educators and…

  12. A Bayesian Approach for Analyzing Longitudinal Structural Equation Models

    Science.gov (United States)

    Song, Xin-Yuan; Lu, Zhao-Hua; Hser, Yih-Ing; Lee, Sik-Yum

    2011-01-01

    This article considers a Bayesian approach for analyzing a longitudinal 2-level nonlinear structural equation model with covariates, and mixed continuous and ordered categorical variables. The first-level model is formulated for measures taken at each time point nested within individuals for investigating their characteristics that are dynamically…

  13. Play Context, Commitment, and Dating Violence: A Structural Equation Model

    Science.gov (United States)

    Gonzalez-Mendez, Rosaura; Hernandez-Cabrera, Juan Andres

    2009-01-01

    This study develops a structural equation model to describe the effect of two groups of factors (type of commitment and play context) on the violence experienced during intimate partner conflict. After contrasting the model in adolescents and university students, we have confirmed that aggressive play and the simulation of jealousy and anger…

  14. A Structural Equation Model of Conceptual Change in Physics

    Science.gov (United States)

    Taasoobshirazi, Gita; Sinatra, Gale M.

    2011-01-01

    A model of conceptual change in physics was tested on introductory-level, college physics students. Structural equation modeling was used to test hypothesized relationships among variables linked to conceptual change in physics including an approach goal orientation, need for cognition, motivation, and course grade. Conceptual change in physics…

  15. Gaussian Process Structural Equation Models with Latent Variables

    CERN Document Server

    Silva, Ricardo

    2010-01-01

    In a variety of disciplines such as social sciences, psychology, medicine and economics, the recorded data are considered to be noisy measurements of latent variables connected by some causal structure. This corresponds to a family of graphical models known as the structural equation model with latent variables. While linear non-Gaussian variants have been well-studied, inference in nonparametric structural equation models is still underdeveloped. We introduce a sparse Gaussian process parameterization that defines a non-linear structure connecting latent variables, unlike common formulations of Gaussian process latent variable models. An efficient Markov chain Monte Carlo procedure is described. We evaluate the stability of the sampling procedure and the predictive ability of the model compared against the current practice.

  16. Random-Effects Models for Meta-Analytic Structural Equation Modeling: Review, Issues, and Illustrations

    Science.gov (United States)

    Cheung, Mike W.-L.; Cheung, Shu Fai

    2016-01-01

    Meta-analytic structural equation modeling (MASEM) combines the techniques of meta-analysis and structural equation modeling for the purpose of synthesizing correlation or covariance matrices and fitting structural equation models on the pooled correlation or covariance matrix. Both fixed-effects and random-effects models can be defined in MASEM.…

  17. Application of structural equation models for evaluating epidemiological data and for calculation of the benchmark dose

    DEFF Research Database (Denmark)

    Budtz-Jørgensen, Esben; Keiding, Niels; Grandjean, P.

    2003-01-01

    observational epidemiology; measurement error; multiple endpoints structural equation models; safety standard......observational epidemiology; measurement error; multiple endpoints structural equation models; safety standard...

  18. Multiple Imputation Strategies for Multiple Group Structural Equation Models

    Science.gov (United States)

    Enders, Craig K.; Gottschall, Amanda C.

    2011-01-01

    Although structural equation modeling software packages use maximum likelihood estimation by default, there are situations where one might prefer to use multiple imputation to handle missing data rather than maximum likelihood estimation (e.g., when incorporating auxiliary variables). The selection of variables is one of the nuances associated…

  19. On the specification of structural equation models for ecological systems

    NARCIS (Netherlands)

    Grace, James B.; Anderson, T. Michael; Olff, Han; Scheiner, Samuel M.

    2010-01-01

    The use of structural equation modeling (SEM) is often motivated by its utility for investigating complex networks of relationships, but also because of its promise as a means of representing theoretical Concepts using latent variables. In this paper, we discuss characteristics of ecological theory

  20. Investigating Supervisory Relationships and Therapeutic Alliances Using Structural Equation Modeling

    Science.gov (United States)

    DePue, Mary Kristina; Lambie, Glenn W.; Liu, Ren; Gonzalez, Jessica

    2016-01-01

    The authors used structural equation modeling to examine the contribution of supervisees' supervisory relationship levels to therapeutic alliance (TA) scores with their clients in practicum. Results showed that supervisory relationship scores positively contributed to the TA. Client and counselor ratings of the TA also differed.

  1. Structural Equation Modeling Reporting Practices for Language Assessment

    Science.gov (United States)

    Ockey, Gary J.; Choi, Ikkyu

    2015-01-01

    Studies that use structural equation modeling (SEM) techniques are increasingly encountered in the language assessment literature. This popularity has created the need for a set of guidelines that can indicate what should be included in a research report and make it possible for research consumers to judge the appropriateness of the…

  2. Robust Structural Equation Modeling with Missing Data and Auxiliary Variables

    Science.gov (United States)

    Yuan, Ke-Hai; Zhang, Zhiyong

    2012-01-01

    The paper develops a two-stage robust procedure for structural equation modeling (SEM) and an R package "rsem" to facilitate the use of the procedure by applied researchers. In the first stage, M-estimates of the saturated mean vector and covariance matrix of all variables are obtained. Those corresponding to the substantive variables…

  3. Evaluating Interventions with Multimethod Data: A Structural Equation Modeling Approach

    Science.gov (United States)

    Crayen, Claudia; Geiser, Christian; Scheithauer, Herbert; Eid, Michael

    2011-01-01

    In many intervention and evaluation studies, outcome variables are assessed using a multimethod approach comparing multiple groups over time. In this article, we show how evaluation data obtained from a complex multitrait-multimethod-multioccasion-multigroup design can be analyzed with structural equation models. In particular, we show how the…

  4. Maximum Likelihood Estimation of Nonlinear Structural Equation Models.

    Science.gov (United States)

    Lee, Sik-Yum; Zhu, Hong-Tu

    2002-01-01

    Developed an EM type algorithm for maximum likelihood estimation of a general nonlinear structural equation model in which the E-step is completed by a Metropolis-Hastings algorithm. Illustrated the methodology with results from a simulation study and two real examples using data from previous studies. (SLD)

  5. Case-Deletion Diagnostics for Nonlinear Structural Equation Models

    Science.gov (United States)

    Lee, Sik-Yum; Lu, Bin

    2003-01-01

    In this article, a case-deletion procedure is proposed to detect influential observations in a nonlinear structural equation model. The key idea is to develop the diagnostic measures based on the conditional expectation of the complete-data log-likelihood function in the EM algorithm. An one-step pseudo approximation is proposed to reduce the…

  6. Local Influence Analysis of Nonlinear Structural Equation Models

    Science.gov (United States)

    Lee, Sik-Yum; Tang, Nian-Sheng

    2004-01-01

    By regarding the latent random vectors as hypothetical missing data and based on the conditional expectation of the complete-data log-likelihood function in the EM algorithm, we investigate assessment of local influence of various perturbation schemes in a nonlinear structural equation model. The basic building blocks of local influence analysis…

  7. Continuous Time Structural Equation Modeling with R Package ctsem

    Directory of Open Access Journals (Sweden)

    Charles C. Driver

    2017-04-01

    Full Text Available We introduce ctsem, an R package for continuous time structural equation modeling of panel (N > 1 and time series (N = 1 data, using full information maximum likelihood. Most dynamic models (e.g., cross-lagged panel models in the social and behavioural sciences are discrete time models. An assumption of discrete time models is that time intervals between measurements are equal, and that all subjects were assessed at the same intervals. Violations of this assumption are often ignored due to the difficulty of accounting for varying time intervals, therefore parameter estimates can be biased and the time course of effects becomes ambiguous. By using stochastic differential equations to estimate an underlying continuous process, continuous time models allow for any pattern of measurement occasions. By interfacing to OpenMx, ctsem combines the flexible specification of structural equation models with the enhanced data gathering opportunities and improved estimation of continuous time models. ctsem can estimate relationships over time for multiple latent processes, measured by multiple noisy indicators with varying time intervals between observations. Within and between effects are estimated simultaneously by modeling both observed covariates and unobserved heterogeneity. Exogenous shocks with different shapes, group differences, higher order diffusion effects and oscillating processes can all be simply modeled. We first introduce and define continuous time models, then show how to specify and estimate a range of continuous time models using ctsem.

  8. Structural Equation Modeling with Mplus Basic Concepts, Applications, and Programming

    CERN Document Server

    Byrne, Barbara M

    2011-01-01

    Modeled after Barbara Byrne's other best-selling structural equation modeling (SEM) books, this practical guide reviews the basic concepts and applications of SEM using Mplus Versions 5 & 6. The author reviews SEM applications based on actual data taken from her own research. Using non-mathematical language, it is written for the novice SEM user. With each application chapter, the author "walks" the reader through all steps involved in testing the SEM model including: an explanation of the issues addressed illustrated and annotated testing of the hypothesized and post hoc models expl

  9. Structural Equation Modeling with Lisrel: An Initial Vision

    Directory of Open Access Journals (Sweden)

    Naresh K Malhotra

    2014-05-01

    Full Text Available LISREL is considered one of the most robust software packages for Structural Equation Modeling with covariance matrices, while it is also considered complex and difficult to use. In this special issue of the Brazilian Journal of Marketing, we aim to present the main functions of LISREL, its features and, through a didactic example, reduce the perceived difficulty of using it. We also provide helpful guidelines to properly using this technique.

  10. Structural equation modeling in the context of clinical research

    Science.gov (United States)

    2017-01-01

    Structural equation modeling (SEM) has been widely used in economics, sociology and behavioral science. However, its use in clinical medicine is quite limited, probably due to technical difficulties. Because SEM is particularly suitable for analysis of complex relationships among observed variables, it must have potential applications to clinical medicine. The article introduces basic ideas of SEM in the context of clinical medicine. A simulated dataset is employed to show how to do model specification, model fit, visualization and assessment of goodness-of-fit. The first example fits a SEM with continuous outcome variable using sem() function, and the second explores the binary outcome variable using lavaan() function. PMID:28361067

  11. The Interface Between Theory and Data in Structural Equation Models

    Science.gov (United States)

    Grace, James B.; Bollen, Kenneth A.

    2006-01-01

    Structural equation modeling (SEM) holds the promise of providing natural scientists the capacity to evaluate complex multivariate hypotheses about ecological systems. Building on its predecessors, path analysis and factor analysis, SEM allows for the incorporation of both observed and unobserved (latent) variables into theoretically based probabilistic models. In this paper we discuss the interface between theory and data in SEM and the use of an additional variable type, the composite, for representing general concepts. In simple terms, composite variables specify the influences of collections of other variables and can be helpful in modeling general relationships of the sort commonly of interest to ecologists. While long recognized as a potentially important element of SEM, composite variables have received very limited use, in part because of a lack of theoretical consideration, but also because of difficulties that arise in parameter estimation when using conventional solution procedures. In this paper we present a framework for discussing composites and demonstrate how the use of partially reduced form models can help to overcome some of the parameter estimation and evaluation problems associated with models containing composites. Diagnostic procedures for evaluating the most appropriate and effective use of composites are illustrated with an example from the ecological literature. It is argued that an ability to incorporate composite variables into structural equation models may be particularly valuable in the study of natural systems, where concepts are frequently multifaceted and the influences of suites of variables are often of interest.

  12. Using of Structural Equation Modeling Techniques in Cognitive Levels Validation

    Directory of Open Access Journals (Sweden)

    Natalija Curkovic

    2012-10-01

    Full Text Available When constructing knowledge tests, cognitive level is usually one of the dimensions comprising the test specifications with each item assigned to measure a particular level. Recently used taxonomies of the cognitive levels most often represent some modification of the original Bloom’s taxonomy. There are many concerns in current literature about existence of predefined cognitive levels. The aim of this article is to investigate can structural equation modeling techniques confirm existence of different cognitive levels. For the purpose of the research, a Croatian final high-school Mathematics exam was used (N = 9626. Confirmatory factor analysis and structural regression modeling were used to test three different models. Structural equation modeling techniques did not support existence of different cognitive levels in this case. There is more than one possible explanation for that finding. Some other techniques that take into account nonlinear behaviour of the items as well as qualitative techniques might be more useful for the purpose of the cognitive levels validation. Furthermore, it seems that cognitive levels were not efficient descriptors of the items and so improvements are needed in describing the cognitive skills measured by items.

  13. Partial Least Squares Structural Equation Modeling with R

    Directory of Open Access Journals (Sweden)

    Hamdollah Ravand

    2016-09-01

    Full Text Available Structural equation modeling (SEM has become widespread in educational and psychological research. Its flexibility in addressing complex theoretical models and the proper treatment of measurement error has made it the model of choice for many researchers in the social sciences. Nevertheless, the model imposes some daunting assumptions and restrictions (e.g. normality and relatively large sample sizes that could discourage practitioners from applying the model. Partial least squares SEM (PLS-SEM is a nonparametric technique which makes no distributional assumptions and can be estimated with small sample sizes. In this paper a general introduction to PLS-SEM is given and is compared with conventional SEM. Next, step by step procedures, along with R functions, are presented to estimate the model. A data set is analyzed and the outputs are interpreted

  14. semPLS: Structural Equation Modeling Using Partial Least Squares

    Directory of Open Access Journals (Sweden)

    Armin Monecke

    2012-05-01

    Full Text Available Structural equation models (SEM are very popular in many disciplines. The partial least squares (PLS approach to SEM offers an alternative to covariance-based SEM, which is especially suited for situations when data is not normally distributed. PLS path modelling is referred to as soft-modeling-technique with minimum demands regarding mea- surement scales, sample sizes and residual distributions. The semPLS package provides the capability to estimate PLS path models within the R programming environment. Different setups for the estimation of factor scores can be used. Furthermore it contains modular methods for computation of bootstrap confidence intervals, model parameters and several quality indices. Various plot functions help to evaluate the model. The well known mobile phone dataset from marketing research is used to demonstrate the features of the package.

  15. Structural Equation Modeling: Theory and Applications in Forest Management

    Directory of Open Access Journals (Sweden)

    Tzeng Yih Lam

    2012-01-01

    Full Text Available Forest ecosystem dynamics are driven by a complex array of simultaneous cause-and-effect relationships. Understanding this complex web requires specialized analytical techniques such as Structural Equation Modeling (SEM. The SEM framework and implementation steps are outlined in this study, and we then demonstrate the technique by application to overstory-understory relationships in mature Douglas-fir forests in the northwestern USA. A SEM model was formulated with (1 a path model representing the effects of successively higher layers of vegetation on late-seral herbs through processes such as light attenuation and (2 a measurement model accounting for measurement errors. The fitted SEM model suggested a direct negative effect of light attenuation on late-seral herbs cover but a direct positive effect of northern aspect. Moreover, many processes have indirect effects mediated through midstory vegetation. SEM is recommended as a forest management tool for designing silvicultural treatments and systems for attaining complex arrays of management objectives.

  16. Structural equation models of VMT growth in US urbanised areas.

    Science.gov (United States)

    Ewing, Reid; Hamidi, Shima; Gallivan, Frank; Nelson, Arthur C.; Grace, James B.

    2014-01-01

    Vehicle miles travelled (VMT) is a primary performance indicator for land use and transportation, bringing with it both positive and negative externalities. This study updates and refines previous work on VMT in urbanised areas, using recent data, additional metrics and structural equation modelling (SEM). In a cross-sectional model for 2010, population, income and freeway capacity are positively related to VMT, while gasoline prices, development density and transit service levels are negatively related. Findings of the cross-sectional model are generally confirmed in a more tightly controlled longitudinal study of changes in VMT between 2000 and 2010, the first model of its kind. The cross-sectional and longitudinal models together, plus the transportation literature generally, give us a basis for generalising across studies to arrive at elasticity values of VMT with respect to different urban variables.

  17. Bayesian structural equation modeling in sport and exercise psychology.

    Science.gov (United States)

    Stenling, Andreas; Ivarsson, Andreas; Johnson, Urban; Lindwall, Magnus

    2015-08-01

    Bayesian statistics is on the rise in mainstream psychology, but applications in sport and exercise psychology research are scarce. In this article, the foundations of Bayesian analysis are introduced, and we will illustrate how to apply Bayesian structural equation modeling in a sport and exercise psychology setting. More specifically, we contrasted a confirmatory factor analysis on the Sport Motivation Scale II estimated with the most commonly used estimator, maximum likelihood, and a Bayesian approach with weakly informative priors for cross-loadings and correlated residuals. The results indicated that the model with Bayesian estimation and weakly informative priors provided a good fit to the data, whereas the model estimated with a maximum likelihood estimator did not produce a well-fitting model. The reasons for this discrepancy between maximum likelihood and Bayesian estimation are discussed as well as potential advantages and caveats with the Bayesian approach.

  18. FLEXIBILITY ANALYSIS IN AN INFORMATION ECONOMY: STRUCTURAL EQUATION MODELING

    Directory of Open Access Journals (Sweden)

    Ricardo da Silva

    2006-11-01

    Full Text Available This paper analyzes the new concept of flexibility in organizations – of relevance both at micro and macro level. Information Economy (IE modern function is specifically analyzed. The purpose of this paper is not limited to the study of information economy flexibility, but extends its focus to other areas of organization and economic studies, having as reference the proposed model. Although not covering all aspects regarding objectives and hypotheses, results obtained demonstrate that subsequent studies can lead to success experiences, since the models presented are: stability in relation to the deviations presented in the resulting equations; values that are very close to what is desirable for adjustment indexes, factorial loads, t-values, extracted variances and reliability; as well as other necessary aspects for the application of the technique. The approach focuses the analysis of information economy flexibility based on structural equations modeling to serve as reference for the development of adaptation phenomenon studies in relation to structures, strategies and organizational processes, against the environmental dynamics contemporary society is faced with.

  19. Structural Equation Modeling: Applications in ecological and evolutionary biology research

    Science.gov (United States)

    Pugesek, Bruce H.; von Eye, Alexander; Tomer, Adrian

    2003-01-01

    This book presents an introduction to the methodology of structural equation modeling, illustrates its use, and goes on to argue that it has revolutionary implications for the study of natural systems. A major theme of this book is that we have, up to this point, attempted to study systems primarily using methods (such as the univariate model) that were designed only for considering individual processes. Understanding systems requires the capacity to examine simultaneous influences and responses. Structural equation modeling (SEM) has such capabilities. It also possesses many other traits that add strength to its utility as a means of making scientific progress. In light of the capabilities of SEM, it can be argued that much of ecological theory is currently locked in an immature state that impairs its relevance. It is further argued that the principles of SEM are capable of leading to the development and evaluation of multivariate theories of the sort vitally needed for the conservation of natural systems. Supplementary information can be found at the authors website, http://www.jamesbgrace.com/. • Details why multivariate analyses should be used to study ecological systems • Exposes unappreciated weakness in many current popular analyses • Emphasizes the future methodological developments needed to advance our understanding of ecological systems.

  20. Applied structural equation modelling for researchers and practitioners using R and Stata for behavioural research

    CERN Document Server

    Ramlall, Indranarain

    2016-01-01

    This book explains in a rigorous, concise and practical manner all the vital components embedded in structural equation modelling. Focusing on R and stata to implement and perform various structural equation models.

  1. On the specification of structural equation models for ecological systems

    Science.gov (United States)

    Grace, J.B.; Michael, Anderson T.; Han, O.; Scheiner, S.M.

    2010-01-01

    The use of structural equation modeling (SEM) is often motivated by its utility for investigating complex networks of relationships, but also because of its promise as a means of representing theoretical concepts using latent variables. In this paper, we discuss characteristics of ecological theory and some of the challenges for proper specification of theoretical ideas in structural equation models (SE models). In our presentation, we describe some of the requirements for classical latent variable models in which observed variables (indicators) are interpreted as the effects of underlying causes. We also describe alternative model specifications in which indicators are interpreted as having causal influences on the theoretical concepts. We suggest that this latter nonclassical specification (which involves another variable type-the composite) will often be appropriate for ecological studies because of the multifaceted nature of our theoretical concepts. In this paper, we employ the use of meta-models to aid the translation of theory into SE models and also to facilitate our ability to relate results back to our theories. We demonstrate our approach by showing how a synthetic theory of grassland biodiversity can be evaluated using SEM and data from a coastal grassland. In this example, the theory focuses on the responses of species richness to abiotic stress and disturbance, both directly and through intervening effects on community biomass. Models examined include both those based on classical forms (where each concept is represented using a single latent variable) and also ones in which the concepts are recognized to be multifaceted and modeled as such. To address the challenge of matching SE models with the conceptual level of our theory, two approaches are illustrated, compositing and aggregation. Both approaches are shown to have merits, with the former being preferable for cases where the multiple facets of a concept have widely differing effects in the

  2. Analisis Loyalitas Pelanggan Industri Jasa Pengiriman Menggunakan Structural Equation Modeling

    Directory of Open Access Journals (Sweden)

    Sarika Zuhri

    2017-01-01

    Full Text Available Customer loyalty is important for both product and service industries. A loyal customer keeps using the company’s product and services. For a shipping service company, retaining existing customers in order to remain faithful will certainly be very crucial. This study was to determine relationship between variables affecting customer loyalty at PT. Pos Indonesia-Banda Aceh, a shipping service industry. The research used Structural Equation Modeling (SEM and with samples of 153 questionnaires obtained through a non-probability sampling technique. By using AMOS software, it can be concluded that the perceived quality does affect customer satisfaction, perceived value has influence on the customer satisfaction, the customer satisfaction is influential to trust and the trust itself has positive influence on customer loyalty.

  3. A performance measurement using balanced scorecard and structural equation modeling

    Directory of Open Access Journals (Sweden)

    Rosha Makvandi

    2014-02-01

    Full Text Available During the past few years, balanced scorecard (BSC has been widely used as a promising method for performance measurement. BSC studies organizations in terms of four perspectives including customer, internal processes, learning and growth and financial figures. This paper presents a hybrid of BSC and structural equation modeling (SEM to measure the performance of an Iranian university in province of Alborz, Iran. The proposed study of this paper uses this conceptual method, designs a questionnaire and distributes it among some university students and professors. Using SEM technique, the survey analyzes the data and the results indicate that the university did poorly in terms of all four perspectives. The survey extracts necessary target improvement by presenting necessary attributes for performance improvement.

  4. Structural Equation Modeling for Analyzing Erythrocyte Fatty Acids in Framingham

    Directory of Open Access Journals (Sweden)

    James V. Pottala

    2014-01-01

    Full Text Available Research has shown that several types of erythrocyte fatty acids (i.e., omega-3, omega-6, and trans are associated with risk for cardiovascular diseases. However, there are complex metabolic and dietary relations among fatty acids, which induce correlations that are typically ignored when using them as risk predictors. A latent variable approach could summarize these complex relations into a few latent variable scores for use in statistical models. Twenty-two red blood cell (RBC fatty acids were measured in Framingham (N = 3196. The correlation matrix of the fatty acids was modeled using structural equation modeling; the model was tested for goodness-of-fit and gender invariance. Thirteen fatty acids were summarized by three latent variables, and gender invariance was rejected so separate models were developed for men and women. A score was developed for the polyunsaturated fatty acid (PUFA latent variable, which explained about 30% of the variance in the data. The PUFA score included loadings in opposing directions among three omega-3 and three omega-6 fatty acids, and incorporated the biosynthetic and dietary relations among them. Whether the PUFA factor score can improve the performance of risk prediction in cardiovascular diseases remains to be tested.

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

    CERN Document Server

    Skrondal, Anders

    2004-01-01

    METHODOLOGY THE OMNI-PRESENCE OF LATENT VARIABLES Introduction 'True' variable measured with error Hypothetical constructs Unobserved heterogeneity Missing values and counterfactuals Latent responses Generating flexible distributions Combining information Summary MODELING DIFFERENT RESPONSE PROCESSES Introduction Generalized linear models Extensions of generalized linear models Latent response formulation Modeling durations or survival Summary and further reading CLASSICAL LATENT VARIABLE MODELS Introduction Multilevel regression models Factor models and item respons

  6. Using structural equation modeling for network meta-analysis.

    Science.gov (United States)

    Tu, Yu-Kang; Wu, Yun-Chun

    2017-07-14

    Network meta-analysis overcomes the limitations of traditional pair-wise meta-analysis by incorporating all available evidence into a general statistical framework for simultaneous comparisons of several treatments. Currently, network meta-analyses are undertaken either within the Bayesian hierarchical linear models or frequentist generalized linear mixed models. Structural equation modeling (SEM) is a statistical method originally developed for modeling causal relations among observed and latent variables. As random effect is explicitly modeled as a latent variable in SEM, it is very flexible for analysts to specify complex random effect structure and to make linear and nonlinear constraints on parameters. The aim of this article is to show how to undertake a network meta-analysis within the statistical framework of SEM. We used an example dataset to demonstrate the standard fixed and random effect network meta-analysis models can be easily implemented in SEM. It contains results of 26 studies that directly compared three treatment groups A, B and C for prevention of first bleeding in patients with liver cirrhosis. We also showed that a new approach to network meta-analysis based on the technique of unrestricted weighted least squares (UWLS) method can also be undertaken using SEM. For both the fixed and random effect network meta-analysis, SEM yielded similar coefficients and confidence intervals to those reported in the previous literature. The point estimates of two UWLS models were identical to those in the fixed effect model but the confidence intervals were greater. This is consistent with results from the traditional pairwise meta-analyses. Comparing to UWLS model with common variance adjusted factor, UWLS model with unique variance adjusted factor has greater confidence intervals when the heterogeneity was larger in the pairwise comparison. The UWLS model with unique variance adjusted factor reflects the difference in heterogeneity within each comparison

  7. Using structural equation modeling to investigate relationships among ecological variables

    Science.gov (United States)

    Malaeb, Z.A.; Kevin, Summers J.; Pugesek, B.H.

    2000-01-01

    Structural equation modeling is an advanced multivariate statistical process with which a researcher can construct theoretical concepts, test their measurement reliability, hypothesize and test a theory about their relationships, take into account measurement errors, and consider both direct and indirect effects of variables on one another. Latent variables are theoretical concepts that unite phenomena under a single term, e.g., ecosystem health, environmental condition, and pollution (Bollen, 1989). Latent variables are not measured directly but can be expressed in terms of one or more directly measurable variables called indicators. For some researchers, defining, constructing, and examining the validity of latent variables may be the end task of itself. For others, testing hypothesized relationships of latent variables may be of interest. We analyzed the correlation matrix of eleven environmental variables from the U.S. Environmental Protection Agency's (USEPA) Environmental Monitoring and Assessment Program for Estuaries (EMAP-E) using methods of structural equation modeling. We hypothesized and tested a conceptual model to characterize the interdependencies between four latent variables-sediment contamination, natural variability, biodiversity, and growth potential. In particular, we were interested in measuring the direct, indirect, and total effects of sediment contamination and natural variability on biodiversity and growth potential. The model fit the data well and accounted for 81% of the variability in biodiversity and 69% of the variability in growth potential. It revealed a positive total effect of natural variability on growth potential that otherwise would have been judged negative had we not considered indirect effects. That is, natural variability had a negative direct effect on growth potential of magnitude -0.3251 and a positive indirect effect mediated through biodiversity of magnitude 0.4509, yielding a net positive total effect of 0

  8. Occupants' satisfaction toward building environmental quality: structural equation modeling approach.

    Science.gov (United States)

    Kamaruzzaman, Syahrul Nizam; Egbu, C O; Zawawi, Emma Marinie Ahmad; Karim, Saipol Bari Abd; Woon, Chen Jia

    2015-05-01

    It is accepted that occupants who are more satisfied with their workplace's building internal environment are more productive. The main objective of the study was to measure the occupants' level of satisfaction and the perceived importance of the design or refurbishment on office conditions. The study also attempted to determine the factors affecting the occupants' satisfaction with their building or office conditions. Post-occupancy evaluations were conducted using a structured questionnaire developed by the Built Environment Research Group at the University of Manchester, UK. Our questionnaires incorporate 22 factors relating to the internal environment and rate these in terms of "user satisfaction" and "degree of importance." The questions were modified to reflect the specific setting of the study and take into consideration the local conditions and climate in Malaysia. The overall mean satisfaction of the occupants toward their office environment was 5.35. The results were measured by a single item of overall liking of office conditions in general. Occupants were more satisfied with their state of health in the workplace, but they were extremely dissatisfied with the distance away from a window. The factor analysis divided the variables into three groups, namely intrusion, air quality, and office appearance. Structural equation modeling (SEM) was then used to determine which factor had the most significant influence on occupants' satisfaction: appearance. The findings from the study suggest that continuous improvement in aspects of the building's appearance needs to be supported with effective and comprehensive maintenance to sustain the occupants' satisfaction.

  9. Fitting Data to Model: Structural Equation Modeling Diagnosis Using Two Scatter Plots

    Science.gov (United States)

    Yuan, Ke-Hai; Hayashi, Kentaro

    2010-01-01

    This article introduces two simple scatter plots for model diagnosis in structural equation modeling. One plot contrasts a residual-based M-distance of the structural model with the M-distance for the factor score. It contains information on outliers, good leverage observations, bad leverage observations, and normal cases. The other plot contrasts…

  10. Modeling Dynamic Functional Neuroimaging Data Using Structural Equation Modeling

    Science.gov (United States)

    Price, Larry R.; Laird, Angela R.; Fox, Peter T.; Ingham, Roger J.

    2009-01-01

    The aims of this study were to present a method for developing a path analytic network model using data acquired from positron emission tomography. Regions of interest within the human brain were identified through quantitative activation likelihood estimation meta-analysis. Using this information, a "true" or population path model was then…

  11. Revisiting the Leadership Scale for Sport: Examining Factor Structure Through Exploratory Structural Equation Modeling.

    Science.gov (United States)

    Chiu, Weisheng; Rodriguez, Fernando M; Won, Doyeon

    2016-10-01

    This study examines the factor structure of the shortened version of the Leadership Scale for Sport, through a survey of 201 collegiate swimmers at National Collegiate Athletic Association Division II and III institutions, using both exploratory structural equation modeling and confirmatory factor analysis. Both exploratory structural equation modeling and confirmatory factor analysis showed that a five-factor solution fit the data adequately. The sizes of factor loadings on target factors substantially differed between the confirmatory factor analysis and exploratory structural equation modeling solutions. In addition, the inter-correlations between factors of the Leadership Scale for Sport and the correlations with athletes' satisfaction were found to be inflated in the confirmatory factor analysis solution. Overall, the findings provide evidence of the factorial validity of the shortened Leadership Scale for Sport.

  12. A New Look at the Big Five Factor Structure through Exploratory Structural Equation Modeling

    Science.gov (United States)

    Marsh, Herbert W.; Ludtke, Oliver; Muthen, Bengt; Asparouhov, Tihomir; Morin, Alexandre J. S.; Trautwein, Ulrich; Nagengast, Benjamin

    2010-01-01

    NEO instruments are widely used to assess Big Five personality factors, but confirmatory factor analyses (CFAs) conducted at the item level do not support their a priori structure due, in part, to the overly restrictive CFA assumptions. We demonstrate that exploratory structural equation modeling (ESEM), an integration of CFA and exploratory…

  13. A Double-Structure Structural Equation Model for Three-Mode Data

    Science.gov (United States)

    Gonzalez, Jorge; De Boeck, Paul; Tuerlinckx, Francis

    2008-01-01

    Structural equation models are commonly used to analyze 2-mode data sets, in which a set of objects is measured on a set of variables. The underlying structure within the object mode is evaluated using latent variables, which are measured by indicators coming from the variable mode. Additionally, when the objects are measured under different…

  14. Reporting Multiple-Group Mean and Covariance Structure across Occasions with Structural Equation Modeling

    Science.gov (United States)

    Okech, David

    2012-01-01

    Objectives: Using baseline and second wave data, the study evaluated the measurement and structural properties of parenting stress, personal mastery, and economic strain with N = 381 lower income parents who decided to join and those who did not join in a child development savings account program. Methods: Structural equation modeling mean and…

  15. Comparing Entrepreneurship Intention: A Multigroup Structural Equation Modeling Approach

    Directory of Open Access Journals (Sweden)

    Sabrina O. Sihombing

    2012-04-01

    Full Text Available Unemployment is one of the main social and economic problems that many countries face nowadays. One strategic way to overcome this problem is by fostering entrepreneurship spirit especially for unem-ployment graduates. Entrepreneurship is becoming an alternative Job for students after they graduate. This is because entrepreneurship of fers major benefits, such as setting up one’s own business and the pos sibility of having significant financial rewards than working for others. Entrepreneurship is then offered by many universities. This research applies the theory of planned behavior (TPB by incorporating attitude toward success as an antecedent variable of the attitude to examine students’ intention to become an entrepreneur. The objective of this research is to compare entrepreneurship intention between business students and non-business students. A self-administered questionnaire was used to collect data for this study. Questionnaires were distributed to respondents by applying the drop-off/pick-up method. A number of 294 by questionnaires were used in the analysis. Data were analyzed by using structural equation modeling. Two out of four hypotheses were confirmed. These hypotheses are the relationship between the attitude toward becoming an entrepreneur and the intention to try becoming an entrepreneur, and the relationship perceived behavioral control and intention to try becoming an entrepreneur. This paper also provides a discussion and offers directions for future research.

  16. Comparing Entrepreneurship Intention: A Multigroup Structural Equation Modeling Approach

    Directory of Open Access Journals (Sweden)

    Sabrina O. Sihombing

    2012-04-01

    Full Text Available Unemployment is one of the main social and economic problems that many countries face nowadays. One strategic way to overcome this problem is by fostering entrepreneurship spirit especially for unem ployment graduates. Entrepreneurship is becoming an alternative Job for students after they graduate. This is because entrepreneurship of-fers major benefits, such as setting up one’s own business and the pos-sibility of having significant financial rewards than working for others. Entrepreneurship is then offered by many universities. This research applies the theory of planned behavior (TPB by incorporating attitude toward success as an antecedent variable of the attitude to examine students’ intention to become an entrepreneur. The objective of this research is to compare entrepreneurship intention between business students and non-business students. A self-administered questionnaire was used to collect data for this study. Questionnaires were distributed to respondents by applying the drop-off/pick-up method. A number of 294 by questionnaires were used in the analysis. Data were analyzed by using structural equation modeling. Two out of four hypotheses were confirmed. These hypotheses are the relationship between the attitude toward becoming an entrepreneur and the intention to try becoming an entrepreneur, and the relationship perceived behavioral control and intention to try becoming an entrepreneur. This paper also provides a discussion and offers directions for future research.

  17. Structural equation modeling of pesticide poisoning, depression, safety, and injury.

    Science.gov (United States)

    Beseler, Cheryl L; Stallones, Lorann

    2013-01-01

    The role of pesticide poisoning in risk of injuries may operate through a link between pesticide-induced depressive symptoms and reduced engagement in safety behaviors. The authors conducted structural equation modeling of cross-sectional data to examine the pattern of associations between pesticide poisoning, depressive symptoms, safety knowledge, safety behaviors, and injury. Interviews of 1637 Colorado farm operators and their spouses from 964 farms were conducted during 1993-1997. Pesticide poisoning was assessed based on a history of ever having been poisoned. The Center for Epidemiologic Studies-Depression scale was used to assess depressive symptoms. Safety knowledge and safety behaviors were assessed using ten items for each latent variable. Outcomes were safety behaviors and injuries. A total of 154 injuries occurred among 1604 individuals with complete data. Pesticide poisoning, financial problems, health, and age predicted negative affect/somatic depressive symptoms with similar effect sizes; sex did not. Depression was more strongly associated with safety behavior than was safety knowledge. Two safety behaviors were significantly associated with an increased risk of injury. This study emphasizes the importance of financial problems and health on depression, and provides further evidence for the link between neurological effects of past pesticide poisoning on risk-taking behaviors and injury.

  18. Identifiability of Gaussian Structural Equation Models with Same Error Variances

    CERN Document Server

    Peters, Jonas

    2012-01-01

    We consider structural equation models (SEMs) in which variables can be written as a function of their parents and noise terms (the latter are assumed to be jointly independent). Corresponding to each SEM, there is a directed acyclic graph (DAG) G_0 describing the relationships between the variables. In Gaussian SEMs with linear functions, the graph can be identified from the joint distribution only up to Markov equivalence classes (assuming faithfulness). It has been shown, however, that this constitutes an exceptional case. In the case of linear functions and non-Gaussian noise, the DAG becomes identifiable. Apart from few exceptions the same is true for non-linear functions and arbitrarily distributed additive noise. In this work, we prove identifiability for a third modification: if we require all noise variables to have the same variances, again, the DAG can be recovered from the joint Gaussian distribution. Our result can be applied to the problem of causal inference. If the data follow a Gaussian SEM w...

  19. Structural Identification and Validation in Stochastic Differential Equation based Models

    DEFF Research Database (Denmark)

    Møller, Jan Kloppenborg; Carstensen, Jacob; Madsen, Henrik

    2011-01-01

    Stochastic differential equations (SDEs) for ecosystem modelling have attracted increasing attention during recent years. The modelling has mostly been through simulation based experiments. Estimation of parameters in SDEs is, however, possible by combining Kalman filter and likelihood techniques...... as a function of the state variables and global radiation. Further improvements of both the drift and the diffusion term are achieved by comparing simulated densities and data....

  20. Habitat fragmentation and reproductive success: a structural equation modelling approach.

    Science.gov (United States)

    Le Tortorec, Eric; Helle, Samuli; Käyhkö, Niina; Suorsa, Petri; Huhta, Esa; Hakkarainen, Harri

    2013-09-01

    1. There is great interest on the effects of habitat fragmentation, whereby habitat is lost and the spatial configuration of remaining habitat patches is altered, on individual breeding performance. However, we still lack consensus of how this important process affects reproductive success, and whether its effects are mainly due to reduced fecundity or nestling survival. 2. The main reason for this may be the way that habitat fragmentation has been previously modelled. Studies have treated habitat loss and altered spatial configuration as two independent processes instead of as one hierarchical and interdependent process, and therefore have not been able to consider the relative direct and indirect effects of habitat loss and altered spatial configuration. 3. We investigated how habitat (i.e. old forest) fragmentation, caused by intense forest harvesting at the territory and landscape scales, is associated with the number of fledged offspring of an area-sensitive passerine, the Eurasian treecreeper (Certhia familiaris). We used structural equation modelling (SEM) to examine the complex hierarchical associations between habitat loss and altered spatial configuration on the number of fledged offspring, by controlling for individual condition and weather conditions during incubation. 4. Against generally held expectations, treecreeper reproductive success did not show a significant association with habitat fragmentation measured at the territory scale. Instead, our analyses suggested that an increasing amount of habitat at the landscape scale caused a significant increase in nest predation rates, leading to reduced reproductive success. This effect operated directly on nest predation rates, instead of acting indirectly through altered spatial configuration. 5. Because habitat amount and configuration are inherently strongly collinear, particularly when multiple scales are considered, our study demonstrates the usefulness of a SEM approach for hierarchical partitioning

  1. A Comparative Structural Equation Modeling Investigation of the Relationships among Teaching, Cognitive and Social Presence

    Science.gov (United States)

    Kozan, Kadir

    2016-01-01

    The present study investigated the relationships among teaching, cognitive, and social presence through several structural equation models to see which model would better fit the data. To this end, the present study employed and compared several different structural equation models because different models could fit the data equally well. Among…

  2. An Application of Latent Variable Structural Equation Modeling For Experimental Research in Educational Technology

    National Research Council Canada - National Science Library

    Hyeon Woo LEE

    2011-01-01

      AN APPLICATION OF LATENT VARIABL AN APPLICATION OF LATENT VARIABLE STRUCTURAL EQUATION MODELING FOR EXPERIMENTAL RESEARCH IN EDUCATIONAL TECHNOLOGY As the technology-enriched learning environments...

  3. Effects of Sample Size, Estimation Methods, and Model Specification on Structural Equation Modeling Fit Indexes.

    Science.gov (United States)

    Fan, Xitao; Wang, Lin; Thompson, Bruce

    1999-01-01

    A Monte Carlo simulation study investigated the effects on 10 structural equation modeling fit indexes of sample size, estimation method, and model specification. Some fit indexes did not appear to be comparable, and it was apparent that estimation method strongly influenced almost all fit indexes examined, especially for misspecified models. (SLD)

  4. A Maximum Likelihood Approach for Multisample Nonlinear Structural Equation Models with Missing Continuous and Dichotomous Data

    Science.gov (United States)

    Song, Xin-Yuan; Lee, Sik-Yum

    2006-01-01

    Structural equation models are widely appreciated in social-psychological research and other behavioral research to model relations between latent constructs and manifest variables and to control for measurement error. Most applications of SEMs are based on fully observed continuous normal data and models with a linear structural equation.…

  5. A Bayesian Approach for Analyzing Hierarchical Data with Missing Outcomes through Structural Equation Models

    Science.gov (United States)

    Song, Xin-Yuan; Lee, Sik-Yum

    2008-01-01

    Structural equation models are widely appreciated in behavioral, social, and psychological research to model relations between latent constructs and manifest variables, and to control for measurement errors. Most applications of structural equation models are based on fully observed data that are independently distributed. However, hierarchical…

  6. The issue of statistical power for overall model fit in evaluating structural equation models

    Directory of Open Access Journals (Sweden)

    Richard HERMIDA

    2015-06-01

    Full Text Available Statistical power is an important concept for psychological research. However, examining the power of a structural equation model (SEM is rare in practice. This article provides an accessible review of the concept of statistical power for the Root Mean Square Error of Approximation (RMSEA index of overall model fit in structural equation modeling. By way of example, we examine the current state of power in the literature by reviewing studies in top Industrial-Organizational (I/O Psychology journals using SEMs. Results indicate that in many studies, power is very low, which implies acceptance of invalid models. Additionally, we examined methodological situations which may have an influence on statistical power of SEMs. Results showed that power varies significantly as a function of model type and whether or not the model is the main model for the study. Finally, results indicated that power is significantly related to model fit statistics used in evaluating SEMs. The results from this quantitative review imply that researchers should be more vigilant with respect to power in structural equation modeling. We therefore conclude by offering methodological best practices to increase confidence in the interpretation of structural equation modeling results with respect to statistical power issues.

  7. Fixed- and random-effects meta-analytic structural equation modeling: examples and analyses in R.

    Science.gov (United States)

    Cheung, Mike W-L

    2014-03-01

    Meta-analytic structural equation modeling (MASEM) combines the ideas of meta-analysis and structural equation modeling for the purpose of synthesizing correlation or covariance matrices and fitting structural equation models on the pooled correlation or covariance matrix. Cheung and Chan (Psychological Methods 10:40-64, 2005b, Structural Equation Modeling 16:28-53, 2009) proposed a two-stage structural equation modeling (TSSEM) approach to conducting MASEM that was based on a fixed-effects model by assuming that all studies have the same population correlation or covariance matrices. The main objective of this article is to extend the TSSEM approach to a random-effects model by the inclusion of study-specific random effects. Another objective is to demonstrate the procedures with two examples using the metaSEM package implemented in the R statistical environment. Issues related to and future directions for MASEM are discussed.

  8. The Trauma Outcome Process Assessment Model: A Structural Equation Model Examination of Adjustment

    Science.gov (United States)

    Borja, Susan E.; Callahan, Jennifer L.

    2009-01-01

    This investigation sought to operationalize a comprehensive theoretical model, the Trauma Outcome Process Assessment, and test it empirically with structural equation modeling. The Trauma Outcome Process Assessment reflects a robust body of research and incorporates known ecological factors (e.g., family dynamics, social support) to explain…

  9. Equivalence and Differences between Structural Equation Modeling and State-Space Modeling Techniques

    Science.gov (United States)

    Chow, Sy-Miin; Ho, Moon-ho R.; Hamaker, Ellen L.; Dolan, Conor V.

    2010-01-01

    State-space modeling techniques have been compared to structural equation modeling (SEM) techniques in various contexts but their unique strengths have often been overshadowed by their similarities to SEM. In this article, we provide a comprehensive discussion of these 2 approaches' similarities and differences through analytic comparisons and…

  10. Equivalence and differences between structural equation modeling and state-space modeling techniques

    NARCIS (Netherlands)

    Chow, Sy-Miin; Ho, Moon-ho R.; Hamaker, E.L.; Dolan, C.V.

    2010-01-01

    State-space modeling techniques have been compared to structural equation modeling (SEM) techniques in various contexts but their unique strengths have often been overshadowed by their similarities to SEM. In this article, we provide a comprehensive discussion of these 2 approaches' similarities and

  11. Structural Equation Modeling of Multitrait-Multimethod Data: Different Models for Different Types of Methods

    Science.gov (United States)

    Eid, Michael; Nussbeck, Fridtjof W.; Geiser, Christian; Cole, David A.; Gollwitzer, Mario; Lischetzke, Tanja

    2008-01-01

    The question as to which structural equation model should be selected when multitrait-multimethod (MTMM) data are analyzed is of interest to many researchers. In the past, attempts to find a well-fitting model have often been data-driven and highly arbitrary. In the present article, the authors argue that the measurement design (type of methods…

  12. Strategic Competence as a Fourth-Order Factor Model: A Structural Equation Modeling Approach

    Science.gov (United States)

    Phakiti, Aek

    2008-01-01

    This article reports on an empirical study that tests a fourth-order factor model of strategic competence through the use of structural equation modeling (SEM). The study examines the hierarchical relationship of strategic competence to (a) strategic knowledge of cognitive and metacognitive strategy use in general (i.e., trait) and (b) strategic…

  13. Equivalence and Differences between Structural Equation Modeling and State-Space Modeling Techniques

    Science.gov (United States)

    Chow, Sy-Miin; Ho, Moon-ho R.; Hamaker, Ellen L.; Dolan, Conor V.

    2010-01-01

    State-space modeling techniques have been compared to structural equation modeling (SEM) techniques in various contexts but their unique strengths have often been overshadowed by their similarities to SEM. In this article, we provide a comprehensive discussion of these 2 approaches' similarities and differences through analytic comparisons and…

  14. Meta-Analytic Structural Equation Modeling (MASEM): Comparison of the Multivariate Methods

    Science.gov (United States)

    Zhang, Ying

    2011-01-01

    Meta-analytic Structural Equation Modeling (MASEM) has drawn interest from many researchers recently. In doing MASEM, researchers usually first synthesize correlation matrices across studies using meta-analysis techniques and then analyze the pooled correlation matrix using structural equation modeling techniques. Several multivariate methods of…

  15. Maximum Likelihood Analysis of Nonlinear Structural Equation Models with Dichotomous Variables

    Science.gov (United States)

    Song, Xin-Yuan; Lee, Sik-Yum

    2005-01-01

    In this article, a maximum likelihood approach is developed to analyze structural equation models with dichotomous variables that are common in behavioral, psychological and social research. To assess nonlinear causal effects among the latent variables, the structural equation in the model is defined by a nonlinear function. The basic idea of the…

  16. Quality of peas modelled by a structural equation system

    DEFF Research Database (Denmark)

    Bech, Anne C.; Juhl, Hans Jørn; Martens, Magni

    2000-01-01

    The quality of peas has been studied in a joint project between a pea producing company in Denmark and several research institutions. The study included quality from a consumer point of view based on market research and quality from more internal company points of view based on measurement...... in a PLS structural model with the Total Food Quality Model as starting point. The results show that texture and flavour do have approximately the same effect on consumers' perception of overall quality. Quality development goals for plant breeders would be to optimse perceived flavour directly...... by increasing the amount of sugars and more indirectly by improving the perception of colour through darker and less yellow peas. Perceived texture can be optimised by focusing on selected texture measurements. Udgivelsesdato: JUL...

  17. Quality of peas modelled by a structural equation system

    DEFF Research Database (Denmark)

    Bech, Anne C.; Juhl, Hans Jørn; Martens, Magni

    2000-01-01

    The quality of peas has been studied in a joint project between a pea producing company in Denmark and several research institutions. The study included quality from a consumer point of view based on market research and quality from more internal company points of view based on measurement...... expressed by consumers as a function of the objective measurements of quality, eg the physical/chemical variables? (3) Which of the measured objective variables are most important for further product development? In the paper we describe consumer evaluations as a function of physical/chemical variables...... in a PLS structural model with the Total Food Quality Model as starting point. The results show that texture and flavour do have approximately the same effect on consumers' perception of overall quality. Quality development goals for plant breeders would be to optimse perceived flavour directly...

  18. Bayesian structural equations model for multilevel data with missing responses and missing covariates

    CSIR Research Space (South Africa)

    Kim, S

    2008-03-01

    Full Text Available Motivated by a large multilevel survey conducted by the US Veterans Health Administration (VHA), we propose a structural equations model which involves a set of latent variables to capture dependence between different responses, a set of facility...

  19. Direct and Indirect Effects of Parental Influence upon Adolescent Alcohol Use: A Structural Equation Modeling Analysis

    Science.gov (United States)

    Kim, Young-Mi; Neff, James Alan

    2010-01-01

    A model incorporating the direct and indirect effects of parental monitoring on adolescent alcohol use was evaluated by applying structural equation modeling (SEM) techniques to data on 4,765 tenth-graders in the 2001 Monitoring the Future Study. Analyses indicated good fit of hypothesized measurement and structural models. Analyses supported both…

  20. The Structure of Preschoolers' Emotion Knowledge: Model Equivalence and Validity Using a Structural Equation Modeling Approach

    Science.gov (United States)

    Bassett, Hideko Hamada; Denham, Susanne; Mincic, Melissa; Graling, Kelly

    2012-01-01

    Research Findings: A theory-based 2-factor structure of preschoolers' emotion knowledge (i.e., recognition of emotional expression and understanding of emotion-eliciting situations) was tested using confirmatory factor analysis. Compared to 1- and 3-factor models, the 2-factor model showed a better fit to the data. The model was found to be…

  1. Further insights on the French WISC-IV factor structure through Bayesian structural equation modeling.

    Science.gov (United States)

    Golay, Philippe; Reverte, Isabelle; Rossier, Jérôme; Favez, Nicolas; Lecerf, Thierry

    2013-06-01

    The interpretation of the Wechsler Intelligence Scale for Children--Fourth Edition (WISC-IV) is based on a 4-factor model, which is only partially compatible with the mainstream Cattell-Horn-Carroll (CHC) model of intelligence measurement. The structure of cognitive batteries is frequently analyzed via exploratory factor analysis and/or confirmatory factor analysis. With classical confirmatory factor analysis, almost all cross-loadings between latent variables and measures are fixed to zero in order to allow the model to be identified. However, inappropriate zero cross-loadings can contribute to poor model fit, distorted factors, and biased factor correlations; most important, they do not necessarily faithfully reflect theory. To deal with these methodological and theoretical limitations, we used a new statistical approach, Bayesian structural equation modeling (BSEM), among a sample of 249 French-speaking Swiss children (8-12 years). With BSEM, zero-fixed cross-loadings between latent variables and measures are replaced by approximate zeros, based on informative, small-variance priors. Results indicated that a direct hierarchical CHC-based model with 5 factors plus a general intelligence factor better represented the structure of the WISC-IV than did the 4-factor structure and the higher order models. Because a direct hierarchical CHC model was more adequate, it was concluded that the general factor should be considered as a breadth rather than a superordinate factor. Because it was possible for us to estimate the influence of each of the latent variables on the 15 subtest scores, BSEM allowed improvement of the understanding of the structure of intelligence tests and the clinical interpretation of the subtest scores. PsycINFO Database Record (c) 2013 APA, all rights reserved.

  2. Testing strong factorial invariance using three-level structural equation modeling

    NARCIS (Netherlands)

    Jak, Suzanne

    2014-01-01

    Within structural equation modeling, the most prevalent model to investigate measurement bias is the multigroup model. Equal factor loadings and intercepts across groups in a multigroup model represent strong factorial invariance (absence of measurement bias) across groups. Although this approach is

  3. Testing strong factorial invariance using three-level structural equation modeling

    Directory of Open Access Journals (Sweden)

    Suzanne eJak

    2014-07-01

    Full Text Available Within structural equation modeling, the most prevalent model to investigate measurement bias is the multigroup model. Equal factor loadings and intercepts across groups in a multigroup model represent strong factorial invariance (absence of measurement bias across groups. Although this approach is possible in principle, it is hardly practical when the number of groups is large or when the group size is relatively small. Jak, Oort and Dolan (2013 showed how strong factorial invariance across large numbers of groups can be tested in a multilevel structural equation modeling framework, by treating group as a random instead of a fixed variable. In the present study, this model is extended for use with three-level data. The proposed method is illustrated with an investigation of strong factorial invariance across 156 school classes and 50 schools in a Dutch dyscalculia test, using three-level structural equation modeling.

  4. Testing strong factorial invariance using three-level structural equation modeling.

    Science.gov (United States)

    Jak, Suzanne

    2014-01-01

    Within structural equation modeling, the most prevalent model to investigate measurement bias is the multigroup model. Equal factor loadings and intercepts across groups in a multigroup model represent strong factorial invariance (absence of measurement bias) across groups. Although this approach is possible in principle, it is hardly practical when the number of groups is large or when the group size is relatively small. Jak et al. (2013) showed how strong factorial invariance across large numbers of groups can be tested in a multilevel structural equation modeling framework, by treating group as a random instead of a fixed variable. In the present study, this model is extended for use with three-level data. The proposed method is illustrated with an investigation of strong factorial invariance across 156 school classes and 50 schools in a Dutch dyscalculia test, using three-level structural equation modeling.

  5. A Component-Based Debugging Approach for Detecting Structural Inconsistencies in Declarative Equation Based Models

    Institute of Scientific and Technical Information of China (English)

    Jian-Wan Ding; Li-Ping Chen; Fan-Li Zhou

    2006-01-01

    Object-oriented modeling with declarative equation based languages often unconsciously leads to structural inconsistencies. Component-based debugging is a new structural analysis approach that addresses this problem by analyzing the structure of each component in a model to separately locate faulty components. The analysis procedure is performed recursively based on the depth-first rule. It first generates fictitious equations for a component to establish a debugging environment, and then detects structural defects by using graph theoretical approaches to analyzing the structure of the system of equations resulting from the component. The proposed method can automatically locate components that cause the structural inconsistencies, and show the user detailed error messages. This information can be a great help in finding and localizing structural inconsistencies, and in some cases pinpoints them immediately.

  6. Maximum Likelihood Analysis of a Two-Level Nonlinear Structural Equation Model with Fixed Covariates

    Science.gov (United States)

    Lee, Sik-Yum; Song, Xin-Yuan

    2005-01-01

    In this article, a maximum likelihood (ML) approach for analyzing a rather general two-level structural equation model is developed for hierarchically structured data that are very common in educational and/or behavioral research. The proposed two-level model can accommodate nonlinear causal relations among latent variables as well as effects…

  7. Analyzing Dyadic Data With Multilevel Modeling Versus Structural Equation Modeling: A Tale of Two Methods.

    Science.gov (United States)

    Ledermann, Thomas; Kenny, David A

    2017-02-06

    Multilevel modeling (MLM) and structural equation modeling (SEM) are the dominant methods for the analysis of dyadic data. Both methods are extensively reviewed for the widely used actor-partner interdependence model and the dyadic growth curve model, as well as other less frequently adopted models, including the common fate model and the mutual influence model. For each method, we discuss the analysis of distinguishable and indistinguishable members, the treatment of missing data, the standardization of effects, and tests of mediation. Even though there has been some blending of the 2 methods, each method has its own advantages and disadvantages, thus both should be in the toolbox of dyadic researchers. (PsycINFO Database Record

  8. IT vendor selection model by using structural equation model & analytical hierarchy process

    Science.gov (United States)

    Maitra, Sarit; Dominic, P. D. D.

    2012-11-01

    Selecting and evaluating the right vendors is imperative for an organization's global marketplace competitiveness. Improper selection and evaluation of potential vendors can dwarf an organization's supply chain performance. Numerous studies have demonstrated that firms consider multiple criteria when selecting key vendors. This research intends to develop a new hybrid model for vendor selection process with better decision making. The new proposed model provides a suitable tool for assisting decision makers and managers to make the right decisions and select the most suitable vendor. This paper proposes a Hybrid model based on Structural Equation Model (SEM) and Analytical Hierarchy Process (AHP) for long-term strategic vendor selection problems. The five steps framework of the model has been designed after the thorough literature study. The proposed hybrid model will be applied using a real life case study to assess its effectiveness. In addition, What-if analysis technique will be used for model validation purpose.

  9. Half-trek criterion for generic identifiability of linear structural equation models

    CERN Document Server

    Foygel, Rina; Drton, Mathias

    2011-01-01

    A linear structural equation model relates random variables of interest and corresponding Gaussian noise terms via a linear equation system. Each such model can be represented by a mixed graph in which directed edges encode the linear equations, and bidirected edges indicate possible correlations among noise terms. We study parameter identifiability in these models, that is, we ask for conditions that ensure that the edge coefficients and correlations appearing in a linear structural equation model can be uniquely recovered from the covariance matrix of the associated normal distribution. We treat the case of generic identifiability, where unique recovery is possible for almost every choice of parameters. We give a new graphical criterion that is sufficient for generic identifiability. It improves criteria from prior work and does not require the directed part of the graph to be acyclic. We also develop a related necessary condition and examine the "gap" between sufficient and necessary conditions through sim...

  10. Structural Equation Models of Latent Interactions: An Appropriate Standardized Solution and Its Scale-Free Properties

    Science.gov (United States)

    Wen, Zhonglin; Marsh, Herbert W.; Hau, Kit-Tai

    2010-01-01

    Standardized parameter estimates are routinely used to summarize the results of multiple regression models of manifest variables and structural equation models of latent variables, because they facilitate interpretation. Although the typical standardization of interaction terms is not appropriate for multiple regression models, straightforward…

  11. Women's Path into Science and Engineering Majors: A Structural Equation Model

    Science.gov (United States)

    Camp, Amanda G.; Gilleland, Diane; Pearson, Carolyn; Vander Putten, Jim

    2009-01-01

    The intent of this study was to investigate the adequacy of Weidman's (1985, 1989) theoretical undergraduate socialization model as an empirical-based causal model pertaining to women's career path choice into a science or engineering (SE) major via structural equation modeling. Data were obtained from the Beginning Postsecondary Students…

  12. A Structural Equation Model for ICT Usage in Higher Education

    Science.gov (United States)

    Usluel, Yasemin Kocak; Askar, Petek; Bas, Turgay

    2008-01-01

    This study focuses on Information and Communication Technologies (ICT) usage, which is the indicator of diffusion. A model composed of the variables which can explain ICT usage in Turkish higher education is established and tested within the study. The two dimensions of ICT usage are considered: instructional and managerial. The data collected…

  13. Professional identity acquisition process model in interprofessional education using structural equation modelling: 10-year initiative survey.

    Science.gov (United States)

    Kururi, Nana; Tozato, Fusae; Lee, Bumsuk; Kazama, Hiroko; Katsuyama, Shiori; Takahashi, Maiko; Abe, Yumiko; Matsui, Hiroki; Tokita, Yoshiharu; Saitoh, Takayuki; Kanaizumi, Shiomi; Makino, Takatoshi; Shinozaki, Hiromitsu; Yamaji, Takehiko; Watanabe, Hideomi

    2016-01-01

    The mandatory interprofessional education (IPE) programme at Gunma University, Japan, was initiated in 1999. A questionnaire of 10 items to assess the students' understanding of the IPE training programme has been distributed since then, and the factor analysis of the responses revealed that it was categorised into four subscales, i.e. "professional identity", "structure and function of training facilities", "teamwork and collaboration", and "role and responsibilities", and suggested that these may take into account the development of IPE programme with clinical training. The purpose of this study was to examine the professional identity acquisition process (PIAP) model in IPE using structural equation modelling (SEM). Overall, 1,581 respondents of a possible 1,809 students from the departments of nursing, laboratory sciences, physical therapy, and occupational therapy completed the questionnaire. The SEM technique was utilised to construct a PIAP model on the relationships among four factors. The original PIAP model showed that "professional identity" was predicted by two factors, namely "role and responsibilities" and "teamwork and collaboration". These two factors were predicted by the factor "structure and function of training facilities". The same structure was observed in nursing and physical therapy students' PIAP models, but it was not completely the same in laboratory sciences and occupational therapy students' PIAP models. A parallel but not isolated curriculum on expertise unique to the profession, which may help to understand their professional identity in combination with learning the collaboration, may be necessary.

  14. The Effect of Perceived Instructional Effectiveness on Student Loyalty: A Multilevel Structural Equation Model

    Science.gov (United States)

    Simsek, Gulhayat Golbasi; Noyan, Fatma

    2009-01-01

    Social sciences research often entails the analysis of data with a multilevel structure. An example of multilevel data is containing measurement on university students nested within instructors. This paper concentrates on multilevel analysis of structural equation modeling with educational data. Data used in this study were gathered from 17647…

  15. OpenMx: An Open Source Extended Structural Equation Modeling Framework

    Science.gov (United States)

    Boker, Steven; Neale, Michael; Maes, Hermine; Wilde, Michael; Spiegel, Michael; Brick, Timothy; Spies, Jeffrey; Estabrook, Ryne; Kenny, Sarah; Bates, Timothy; Mehta, Paras; Fox, John

    2011-01-01

    OpenMx is free, full-featured, open source, structural equation modeling (SEM) software. OpenMx runs within the "R" statistical programming environment on Windows, Mac OS-X, and Linux computers. The rationale for developing OpenMx is discussed along with the philosophy behind the user interface. The OpenMx data structures are…

  16. OpenMx: An Open Source Extended Structural Equation Modeling Framework

    Science.gov (United States)

    Boker, Steven; Neale, Michael; Maes, Hermine; Wilde, Michael; Spiegel, Michael; Brick, Timothy; Spies, Jeffrey; Estabrook, Ryne; Kenny, Sarah; Bates, Timothy; Mehta, Paras; Fox, John

    2011-01-01

    OpenMx is free, full-featured, open source, structural equation modeling (SEM) software. OpenMx runs within the "R" statistical programming environment on Windows, Mac OS-X, and Linux computers. The rationale for developing OpenMx is discussed along with the philosophy behind the user interface. The OpenMx data structures are…

  17. Application of Exploratory Structural Equation Modeling to Evaluate the Academic Motivation Scale

    Science.gov (United States)

    Guay, Frédéric; Morin, Alexandre J. S.; Litalien, David; Valois, Pierre; Vallerand, Robert J.

    2015-01-01

    In this research, the authors examined the construct validity of scores of the Academic Motivation Scale using exploratory structural equation modeling. Study 1 and Study 2 involved 1,416 college students and 4,498 high school students, respectively. First, results of both studies indicated that the factor structure tested with exploratory…

  18. Application of partial differential equation modeling of the control/structural dynamics of flexible spacecraft

    Science.gov (United States)

    Taylor, Lawrence W., Jr.; Rajiyah, H.

    1991-01-01

    Partial differential equations for modeling the structural dynamics and control systems of flexible spacecraft are applied here in order to facilitate systems analysis and optimization of these spacecraft. Example applications are given, including the structural dynamics of SCOLE, the Solar Array Flight Experiment, the Mini-MAST truss, and the LACE satellite. The development of related software is briefly addressed.

  19. Application of partial differential equation modeling of the control/structural dynamics of flexible spacecraft

    Science.gov (United States)

    Taylor, Lawrence W., Jr.; Rajiyah, H.

    Partial differential equations for modeling the structural dynamics and control systems of flexible spacecraft are applied here in order to facilitate systems analysis and optimization of these spacecraft. Example applications are given, including the structural dynamics of SCOLE, the Solar Array Flight Experiment, the Mini-MAST truss, and the LACE satellite. The development of related software is briefly addressed.

  20. Analysis of Structural Equation Model with Ignorable Missing Continuous and Polytomous Data.

    Science.gov (United States)

    Song, Xin-Yuan; Lee, Sik-Yum

    2002-01-01

    Developed a Bayesian approach for structural equation models with ignorable missing continuous and polytomous data that obtains joint Bayesian estimates of thresholds, structural parameters, and latent factor scores simultaneously. Illustrated the approach through analysis of a real data set of 20 patterns of condom use in the Philippines. (SLD)

  1. Causal Analysis of Religious Violence, a Structural Equation Modeling Approach

    Directory of Open Access Journals (Sweden)

    M Munajat

    2015-12-01

    [Penelitian ini berusaha mengkaji sebab kekerasan keagamaan dengan menggunakan pendekatan Model Persamaan Struktur (SEM. Penelitian kuantitatif terdahulu dalam bidang gerakan sosial dan kekerasan politik menunjukkan bahwa setidaknya ada tiga faktor yang diduga kuat menjadi penyebab kekerasan kolektif, seperti kekerasan agama, yaitu: 1 semakin fundamentalis seseorang, maka ia akan semakin cenderung menyetujui pernggunaan cara kekerasan, 2 semakin rendah kepercayaan seseorang terhadap pemerintah, maka ia akan semakin menyetujui penggunaan kekerasan, 3 berbeda dengan pendapat ke-dua, hanya orang yang rendah kepercayaanya kepada pemerintah, namun mempunyai semangat politik tinggi, yang akan menyetujui penggunaan cara-cara kekerasan. Berdasarkan pada data yang diambil dari 343 responden dari para aktivis, Front Pembela Islam, Muhammadiyah dan Nahdlatul Ulama, penelitian ini mengkonfirmasi bahwa semakin fundamentalis seseorang, maka ia akan semakin cenderung menyetujui kekerasan, terlepas dari afiliasi organisasi mereka. Namun demikian, penelitian ini tidak mendukung hubungan antara kepercayaan terhadap pemerintah dan kekerasan. Demikian juga, hubungan antara kekerasan dan interaksi antara kepercayaan pemerintah dan semangat politik tidak dapat dibuktikan dari data dalam penelitian ini. Oleh karena itu, penelitian ini menyimpulkan bahwa fundamentalisme, sebagai salah satu bentuk keagamaan, merupakan faktor yang sangat penting dalam menjelaskan kekerasan keagamaan.

  2. Prescriptive Statements and Educational Practice: What Can Structural Equation Modeling (SEM) Offer?

    Science.gov (United States)

    Martin, Andrew J.

    2011-01-01

    Longitudinal structural equation modeling (SEM) can be a basis for making prescriptive statements on educational practice and offers yields over "traditional" statistical techniques under the general linear model. The extent to which prescriptive statements can be made will rely on the appropriate accommodation of key elements of research design,…

  3. A Two-Stage Approach to Synthesizing Covariance Matrices in Meta-Analytic Structural Equation Modeling

    Science.gov (United States)

    Cheung, Mike W. L.; Chan, Wai

    2009-01-01

    Structural equation modeling (SEM) is widely used as a statistical framework to test complex models in behavioral and social sciences. When the number of publications increases, there is a need to systematically synthesize them. Methodology of synthesizing findings in the context of SEM is known as meta-analytic SEM (MASEM). Although correlation…

  4. Linear indices in nonlinear structural equation models : best fitting proper indices and other composites

    NARCIS (Netherlands)

    Dijkstra, T.K.; Henseler, J.

    2011-01-01

    The recent advent of nonlinear structural equation models with indices poses a new challenge to the measurement of scientific constructs. We discuss, exemplify and add to a family of statistical methods aimed at creating linear indices, and compare their suitability in a complex path model with line

  5. Reliability of Summed Item Scores Using Structural Equation Modeling: An Alternative to Coefficient Alpha

    Science.gov (United States)

    Green, Samuel B.; Yang, Yanyun

    2009-01-01

    A method is presented for estimating reliability using structural equation modeling (SEM) that allows for nonlinearity between factors and item scores. Assuming the focus is on consistency of summed item scores, this method for estimating reliability is preferred to those based on linear SEM models and to the most commonly reported estimate of…

  6. Some Cautionary Notes on the Specification and Interpretation of LISREL-type Structural Equation Models.

    Science.gov (United States)

    Baldwin, Beatrice

    LISREL-type structural equation modeling is a powerful statistical technique that seems appropriate for social science variables which are complex and difficult to measure. The literature on the specification, estimation, and testing of such models is voluminous. The greatest proportion of this literature, however, focuses on the technical aspects…

  7. A Demonstration of a Systematic Item-Reduction Approach Using Structural Equation Modeling

    Science.gov (United States)

    Larwin, Karen; Harvey, Milton

    2012-01-01

    Establishing model parsimony is an important component of structural equation modeling (SEM). Unfortunately, little attention has been given to developing systematic procedures to accomplish this goal. To this end, the current study introduces an innovative application of the jackknife approach first presented in Rensvold and Cheung (1999). Unlike…

  8. Exploring Mediating Effect of Metacognitive Awareness on Comprehension of Science Texts through Structural Equation Modeling Analysis

    Science.gov (United States)

    Wang, Jing-Ru; Chen, Shin-Feng

    2014-01-01

    This study used a Chinese-language version of the Index of Science Reading Awareness (ISRA) to investigate metacognitive awareness and the Reading Comprehension of Science Test (RCST) to explore comprehension of science text by Taiwanese students. Structural equation modeling (SEM) results confirmed the validity of the underlying models of…

  9. Standards-Based Evaluation and Teacher Career Satisfaction: A Structural Equation Modeling Analysis

    Science.gov (United States)

    Conley, Sharon; Muncey, Donna E.; You, Sukkyung

    2005-01-01

    Structural equation modeling was used to assess the plausibility of a conceptual model specifying hypothesized linkages among perceptions of characteristics of standards-based evaluation, work environment mediators, and career satisfaction and other outcomes. Four comprehensive high schools located in two neighboring counties in southern…

  10. A Two-Stage Approach to Synthesizing Covariance Matrices in Meta-Analytic Structural Equation Modeling

    Science.gov (United States)

    Cheung, Mike W. L.; Chan, Wai

    2009-01-01

    Structural equation modeling (SEM) is widely used as a statistical framework to test complex models in behavioral and social sciences. When the number of publications increases, there is a need to systematically synthesize them. Methodology of synthesizing findings in the context of SEM is known as meta-analytic SEM (MASEM). Although correlation…

  11. Bayesian Analysis of Nonlinear Structural Equation Models with Nonignorable Missing Data

    Science.gov (United States)

    Lee, Sik-Yum

    2006-01-01

    A Bayesian approach is developed for analyzing nonlinear structural equation models with nonignorable missing data. The nonignorable missingness mechanism is specified by a logistic regression model. A hybrid algorithm that combines the Gibbs sampler and the Metropolis-Hastings algorithm is used to produce the joint Bayesian estimates of…

  12. Organizational Cynicism, School Culture, and Academic Achievement: The Study of Structural Equation Modeling

    Science.gov (United States)

    Karadag, Engin; Kilicoglu, Gökhan; Yilmaz, Derya

    2014-01-01

    The purpose of this study is to explain constructed theoretical models that organizational cynicism perceptions of primary school teachers affect school culture and academic achievement, by using structural equation modeling. With the assumption that there is a cause-effect relationship between three main variables, the study was constructed with…

  13. Structural equation modeling versus marginal structural modeling for assessing mediation in the presence of posttreatment confounding.

    Science.gov (United States)

    Moerkerke, Beatrijs; Loeys, Tom; Vansteelandt, Stijn

    2015-06-01

    Inverse probability weighting for marginal structural models has been suggested as a strategy to estimate the direct effect of a treatment or exposure on an outcome in studies where the effect of mediator on outcome is subject to posttreatment confounding. This type of confounding, whereby confounders of the effect of mediator on outcome are themselves affected by the exposure, complicates mediation analyses and necessitates apt analysis strategies. In this article, we contrast the inverse probability weighting approach with the traditional path analysis approach to mediation analysis. We show that in a particular class of linear models, adjustment for posttreatment confounding can be realized via a fairly standard modification of the traditional path analysis approach. The resulting approach is simpler; by avoiding inverse probability weighting, it moreover results in direct effect estimators with smaller finite sample bias and greater precision. We further show that a particular variant of the G-estimation approach from the causal inference literature is equivalent with the path analysis approach in simple linear settings but is more generally applicable in settings with interactions and/or noncontinuous mediators and confounders. We conclude that the use of inverse probability weighting for marginal structural models to adjust for posttreatment confounding in mediation analysis is primarily indicated in nonlinear models for the outcome.

  14. Structural equation models for meta-analysis in environmental risk assessment

    DEFF Research Database (Denmark)

    Budtz-Jørgensen, Esben; Debes, Frodi; Weihe, Pal;

    2010-01-01

    The potential of structural equation models for combining information from different studies in environmental epidemiology is explored. For illustration we synthesize data from two birth cohorts assessing the effects of prenatal exposure to methylmercury on childhood cognitive performance. One...... cohort was the largest by far, but a smaller cohort included superior assessment of the PCB exposure which has been considered an important confounder when estimating the mercury effect. The data were analyzed by specification of a structural equation model for each cohort. Information was then pooled...

  15. Basic and Advanced Bayesian Structural Equation Modeling With Applications in the Medical and Behavioral Sciences

    CERN Document Server

    Lee, Sik-Yum

    2012-01-01

    This book provides clear instructions to researchers on how to apply Structural Equation Models (SEMs) for analyzing the inter relationships between observed and latent variables. Basic and Advanced Bayesian Structural Equation Modeling introduces basic and advanced SEMs for analyzing various kinds of complex data, such as ordered and unordered categorical data, multilevel data, mixture data, longitudinal data, highly non-normal data, as well as some of their combinations. In addition, Bayesian semiparametric SEMs to capture the true distribution of explanatory latent variables are introduce

  16. Maternal, Infant Characteristics, Breastfeeding Techniques, and Initiation: Structural Equation Modeling Approaches

    OpenAIRE

    2015-01-01

    Objectives The aim of this study was to examine the relationships among maternal and infant characteristics, breastfeeding techniques, and exclusive breastfeeding initiation in different modes of birth using structural equation modeling approaches. Methods We examined a hypothetical model based on integrating concepts of a breastfeeding decision-making model, a breastfeeding initiation model, and a social cognitive theory among 952 mother-infant dyads. The LATCH breastfeeding assessment tool ...

  17. An Overview of Path Analysis: Mediation Analysis Concept in Structural Equation Modeling

    OpenAIRE

    Jenatabadi, Hashem Salarzadeh

    2015-01-01

    This paper provides a tutorial discussion on path analysis structure with concept of structural equation modelling (SEM). The paper delivers an introduction to path analysis technique and explain to how to deal with analyzing the data with this kind of statistical methodology especially with a mediator in the research model. The intended audience is statisticians, mathematicians, or methodologists who either know about SEM or simple basic statistics especially in regression and linear/nonline...

  18. Exploring Factor Model Parameters across Continuous Variables with Local Structural Equation Models.

    Science.gov (United States)

    Hildebrandt, Andrea; Lüdtke, Oliver; Robitzsch, Alexander; Sommer, Christopher; Wilhelm, Oliver

    2016-01-01

    Using an empirical data set, we investigated variation in factor model parameters across a continuous moderator variable and demonstrated three modeling approaches: multiple-group mean and covariance structure (MGMCS) analyses, local structural equation modeling (LSEM), and moderated factor analysis (MFA). We focused on how to study variation in factor model parameters as a function of continuous variables such as age, socioeconomic status, ability levels, acculturation, and so forth. Specifically, we formalized the LSEM approach in detail as compared with previous work and investigated its statistical properties with an analytical derivation and a simulation study. We also provide code for the easy implementation of LSEM. The illustration of methods was based on cross-sectional cognitive ability data from individuals ranging in age from 4 to 23 years. Variations in factor loadings across age were examined with regard to the age differentiation hypothesis. LSEM and MFA converged with respect to the conclusions. When there was a broad age range within groups and varying relations between the indicator variables and the common factor across age, MGMCS produced distorted parameter estimates. We discuss the pros of LSEM compared with MFA and recommend using the two tools as complementary approaches for investigating moderation in factor model parameters.

  19. Modelling pathways to Rubisco degradation: a structural equation network modelling approach.

    Directory of Open Access Journals (Sweden)

    Catherine Tétard-Jones

    Full Text Available 'Omics analysis (transcriptomics, proteomics quantifies changes in gene/protein expression, providing a snapshot of changes in biochemical pathways over time. Although tools such as modelling that are needed to investigate the relationships between genes/proteins already exist, they are rarely utilised. We consider the potential for using Structural Equation Modelling to investigate protein-protein interactions in a proposed Rubisco protein degradation pathway using previously published data from 2D electrophoresis and mass spectrometry proteome analysis. These informed the development of a prior model that hypothesised a pathway of Rubisco Large Subunit and Small Subunit degradation, producing both primary and secondary degradation products. While some of the putative pathways were confirmed by the modelling approach, the model also demonstrated features that had not been originally hypothesised. We used Bayesian analysis based on Markov Chain Monte Carlo simulation to generate output statistics suggesting that the model had replicated the variation in the observed data due to protein-protein interactions. This study represents an early step in the development of approaches that seek to enable the full utilisation of information regarding the dynamics of biochemical pathways contained within proteomics data. As these approaches gain attention, they will guide the design and conduct of experiments that enable 'Omics modelling to become a common place practice within molecular biology.

  20. Sample Size Considerations in Prevention Research Applications of Multilevel Modeling and Structural Equation Modeling.

    Science.gov (United States)

    Hoyle, Rick H; Gottfredson, Nisha C

    2015-10-01

    When the goal of prevention research is to capture in statistical models some measure of the dynamic complexity in structures and processes implicated in problem behavior and its prevention, approaches such as multilevel modeling (MLM) and structural equation modeling (SEM) are indicated. Yet the assumptions that must be satisfied if these approaches are to be used responsibly raise concerns regarding their use in prevention research involving smaller samples. In this article, we discuss in nontechnical terms the role of sample size in MLM and SEM and present findings from the latest simulation work on the performance of each approach at sample sizes typical of prevention research. For each statistical approach, we draw from extant simulation studies to establish lower bounds for sample size (e.g., MLM can be applied with as few as ten groups comprising ten members with normally distributed data, restricted maximum likelihood estimation, and a focus on fixed effects; sample sizes as small as N = 50 can produce reliable SEM results with normally distributed data and at least three reliable indicators per factor) and suggest strategies for making the best use of the modeling approach when N is near the lower bound.

  1. From Ordinary Differential Equations to Structural Causal Models: the deterministic case

    NARCIS (Netherlands)

    Mooij, J.M.; Janzing, D.; Schölkopf, B.; Nicholson, A.; Smyth, P.

    2013-01-01

    We show how, and under which conditions, the equilibrium states of a first-order Ordinary Differential Equation (ODE) system can be described with a deterministic Structural Causal Model (SCM). Our exposition sheds more light on the concept of causality as expressed within the framework of Structura

  2. Factors Affecting Higher Order Thinking Skills of Students: A Meta-Analytic Structural Equation Modeling Study

    Science.gov (United States)

    Budsankom, Prayoonsri; Sawangboon, Tatsirin; Damrongpanit, Suntorapot; Chuensirimongkol, Jariya

    2015-01-01

    The purpose of the research is to develop and identify the validity of factors affecting higher order thinking skills (HOTS) of students. The thinking skills can be divided into three types: analytical, critical, and creative thinking. This analysis is done by applying the meta-analytic structural equation modeling (MASEM) based on a database of…

  3. An Application of Structural Equation Modeling for Developing Good Teaching Characteristics Ontology

    Science.gov (United States)

    Phiakoksong, Somjin; Niwattanakul, Suphakit; Angskun, Thara

    2013-01-01

    Ontology is a knowledge representation technique which aims to make knowledge explicit by defining the core concepts and their relationships. The Structural Equation Modeling (SEM) is a statistical technique which aims to explore the core factors from empirical data and estimates the relationship between these factors. This article presents an…

  4. Testing Mediation Using Multiple Regression and Structural Equation Modeling Analyses in Secondary Data

    Science.gov (United States)

    Li, Spencer D.

    2011-01-01

    Mediation analysis in child and adolescent development research is possible using large secondary data sets. This article provides an overview of two statistical methods commonly used to test mediated effects in secondary analysis: multiple regression and structural equation modeling (SEM). Two empirical studies are presented to illustrate the…

  5. A Structural Equation Modelling of the Academic Self-Concept Scale

    Science.gov (United States)

    Matovu, Musa

    2014-01-01

    The study aimed at validating the academic self-concept scale by Liu and Wang (2005) in measuring academic self-concept among university students. Structural equation modelling was used to validate the scale which was composed of two subscales; academic confidence and academic effort. The study was conducted on university students; males and…

  6. Using a Structural Equation Model to Describe the Infusion of Civic Engagement in the Campus Culture

    Science.gov (United States)

    Billings, Meredith S.; Terkla, Dawn Geronimo

    2011-01-01

    This study assesses whether Tufts University's campus culture was successful at infusing civic-mindedness in all undergraduates. A structural equation model was developed, and findings revealed that the campus environment had a significant positive impact on civic values and beliefs and a positive indirect effect on civic engagement activities.…

  7. Self-Conscious Emotions in Response to Perceived Failure: A Structural Equation Model

    Science.gov (United States)

    Bidjerano, Temi

    2010-01-01

    This study explored the occurrence of self-conscious emotions in response to perceived academic failure among 4th-grade students from the United States and Bulgaria, and the author investigated potential contributors to such negative emotional experiences. Results from structural equation modeling indicated that regardless of country, negative…

  8. Spiritual Leadership and Organizational Culture: A Study of Structural Equation Modeling

    Science.gov (United States)

    Karadag, Engin

    2009-01-01

    The aim of this study is to test the spiritual leadership behaviors of school principles in a structural equation model. The study is designed to test causality with the assumption that causality exists between the two variables. In this study, spiritual leadership behavior of managers is treated as the independent variable whereas the…

  9. Using Structural Equation Modeling to Assess Functional Connectivity in the Brain: Power and Sample Size Considerations

    Science.gov (United States)

    Sideridis, Georgios; Simos, Panagiotis; Papanicolaou, Andrew; Fletcher, Jack

    2014-01-01

    The present study assessed the impact of sample size on the power and fit of structural equation modeling applied to functional brain connectivity hypotheses. The data consisted of time-constrained minimum norm estimates of regional brain activity during performance of a reading task obtained with magnetoencephalography. Power analysis was first…

  10. Structural Equation Modeling towards Online Learning Readiness, Academic Motivations, and Perceived Learning

    Science.gov (United States)

    Horzum, Mehmet Baris; Kaymak, Zeliha Demir; Gungoren, Ozlem Canan

    2015-01-01

    The relationship between online learning readiness, academic motivations, and perceived learning was investigated via structural equation modeling in the research. The population of the research consisted of 750 students who studied using the online learning programs of Sakarya University. 420 of the students who volunteered for the research and…

  11. Understanding the Impact of Trauma Exposure on Posttraumatic Stress Symptomatology: A Structural Equation Modeling Approach

    Science.gov (United States)

    Chen, Wei; Wang, Long; Zhang, Xing-Li; Shi, Jian-Nong

    2012-01-01

    The objective of this study was to investigate the impact of trauma exposure on the posttraumatic stress symptomatology (PTSS) of children who resided near the epicenter of the 2008 Wenchuan earthquake. The mechanisms of this impact were explored via structural equation models with self-esteem and coping strategies included as mediators. The…

  12. Vocabulary and Grammar Knowledge in Second Language Reading Comprehension: A Structural Equation Modeling Study

    Science.gov (United States)

    Zhang, Dongbo

    2012-01-01

    Using structural equation modeling analysis, this study examined the contribution of vocabulary and grammatical knowledge to second language reading comprehension among 190 advanced Chinese English as a foreign language learners. Vocabulary knowledge was measured in both breadth (Vocabulary Levels Test) and depth (Word Associates Test);…

  13. Cultural, Social, and Economic Capital Constructs in International Assessments: An Evaluation Using Exploratory Structural Equation Modeling

    Science.gov (United States)

    Caro, Daniel H.; Sandoval-Hernández, Andrés; Lüdtke, Oliver

    2014-01-01

    The article employs exploratory structural equation modeling (ESEM) to evaluate constructs of economic, cultural, and social capital in international large-scale assessment (LSA) data from the Progress in International Reading Literacy Study (PIRLS) 2006 and the Programme for International Student Assessment (PISA) 2009. ESEM integrates the…

  14. Bayesian Structural Equation Modeling: A More Flexible Representation of Substantive Theory

    Science.gov (United States)

    Muthen, Bengt; Asparouhov, Tihomir

    2012-01-01

    This article proposes a new approach to factor analysis and structural equation modeling using Bayesian analysis. The new approach replaces parameter specifications of exact zeros with approximate zeros based on informative, small-variance priors. It is argued that this produces an analysis that better reflects substantive theories. The proposed…

  15. A Structural Equation Modelling Approach for Massive Blended Synchronous Teacher Training

    Science.gov (United States)

    Kannan, Kalpana; Narayanan, Krishnan

    2015-01-01

    This paper presents a structural equation modelling (SEM) approach for blended synchronous teacher training workshop. It examines the relationship among various factors that influence the Satisfaction (SAT) of participating teachers. Data were collected with the help of a questionnaire from about 500 engineering college teachers. These teachers…

  16. Bayesian Methods for Analyzing Structural Equation Models with Covariates, Interaction, and Quadratic Latent Variables

    Science.gov (United States)

    Lee, Sik-Yum; Song, Xin-Yuan; Tang, Nian-Sheng

    2007-01-01

    The analysis of interaction among latent variables has received much attention. This article introduces a Bayesian approach to analyze a general structural equation model that accommodates the general nonlinear terms of latent variables and covariates. This approach produces a Bayesian estimate that has the same statistical optimal properties as a…

  17. A Bayesian Approach for Nonlinear Structural Equation Models with Dichotomous Variables Using Logit and Probit Links

    Science.gov (United States)

    Lee, Sik-Yum; Song, Xin-Yuan; Cai, Jing-Heng

    2010-01-01

    Analysis of ordered binary and unordered binary data has received considerable attention in social and psychological research. This article introduces a Bayesian approach, which has several nice features in practical applications, for analyzing nonlinear structural equation models with dichotomous data. We demonstrate how to use the software…

  18. Quasi-Maximum Likelihood Estimation of Structural Equation Models with Multiple Interaction and Quadratic Effects

    Science.gov (United States)

    Klein, Andreas G.; Muthen, Bengt O.

    2007-01-01

    In this article, a nonlinear structural equation model is introduced and a quasi-maximum likelihood method for simultaneous estimation and testing of multiple nonlinear effects is developed. The focus of the new methodology lies on efficiency, robustness, and computational practicability. Monte-Carlo studies indicate that the method is highly…

  19. Reliable and More Powerful Methods for Power Analysis in Structural Equation Modeling

    Science.gov (United States)

    Yuan, Ke-Hai; Zhang, Zhiyong; Zhao, Yanyun

    2017-01-01

    The normal-distribution-based likelihood ratio statistic T[subscript ml] = nF[subscript ml] is widely used for power analysis in structural Equation modeling (SEM). In such an analysis, power and sample size are computed by assuming that T[subscript ml] follows a central chi-square distribution under H[subscript 0] and a noncentral chi-square…

  20. Maximum Likelihood Estimation of Nonlinear Structural Equation Models with Ignorable Missing Data

    Science.gov (United States)

    Lee, Sik-Yum; Song, Xin-Yuan; Lee, John C. K.

    2003-01-01

    The existing maximum likelihood theory and its computer software in structural equation modeling are established on the basis of linear relationships among latent variables with fully observed data. However, in social and behavioral sciences, nonlinear relationships among the latent variables are important for establishing more meaningful models…

  1. A Robust Bayesian Approach for Structural Equation Models with Missing Data

    Science.gov (United States)

    Lee, Sik-Yum; Xia, Ye-Mao

    2008-01-01

    In this paper, normal/independent distributions, including but not limited to the multivariate t distribution, the multivariate contaminated distribution, and the multivariate slash distribution, are used to develop a robust Bayesian approach for analyzing structural equation models with complete or missing data. In the context of a nonlinear…

  2. Does Method of Handling Missing Data Affect Results of a Structural Equation Model?

    Science.gov (United States)

    Witta, E. Lea

    The influence of method of handling missing data on estimates produced by a structural equation model of the effects of part-time work on high-school student achievement was investigated. Missing data methods studied were listwise deletion, pairwise deletion, the expectation maximization (EM) algorithm, regression, and response pattern. The 26…

  3. Use of Item Parceling in Structural Equation Modeling with Missing Data

    Science.gov (United States)

    Orcan, Fatih

    2013-01-01

    Parceling is referred to as a procedure for computing sums or average scores across multiple items. Parcels instead of individual items are then used as indicators of latent factors in the structural equation modeling analysis (Bandalos 2002, 2008; Little et al., 2002; Yang, Nay, & Hoyle, 2010). Item parceling may be applied to alleviate some…

  4. Anti-Transgender Prejudice: A Structural Equation Model of Associated Constructs

    Science.gov (United States)

    Tebbe, Esther N.; Moradi, Bonnie

    2012-01-01

    This study aimed to identify theoretically relevant key correlates of anti-transgender prejudice. Specifically, structural equation modeling was used to test the unique relations of anti-lesbian, gay, and bisexual (LGB) prejudice; traditional gender role attitudes; need for closure; and social dominance orientation with anti-transgender prejudice.…

  5. Investigation of Factors Influencing Turkey's PISA 2006 Science Achievement with Structural Equation Modelling

    Science.gov (United States)

    Anil, Duygu

    2011-01-01

    This study aims, in line with PISA (Programmes for International Students' Achievement Evaluation) 2006, at constructing a structural equation model between variables considered to be associated with 15 year old Turkish students' science achievement scores and their responses to students questionnaire. In this sense, this is a relational research…

  6. University Students' Behaviors Pertaining to Sustainability: A Structural Equation Model with Sustainability-Related Attributes

    Science.gov (United States)

    Sahin, Elvan; Ertepinar, Hamide; Teksoz, Gaye

    2012-01-01

    The purpose of this study is to construct a structural equation model to examine the links among attitudes, values, and behaviors pertaining to sustainability, participation in outdoor recreation as well as gender and tendency to follow mass media for university students. The data were collected by on-line administration of a survey to 958…

  7. Understanding the Impact of Trauma Exposure on Posttraumatic Stress Symptomatology: A Structural Equation Modeling Approach

    Science.gov (United States)

    Chen, Wei; Wang, Long; Zhang, Xing-Li; Shi, Jian-Nong

    2012-01-01

    The objective of this study was to investigate the impact of trauma exposure on the posttraumatic stress symptomatology (PTSS) of children who resided near the epicenter of the 2008 Wenchuan earthquake. The mechanisms of this impact were explored via structural equation models with self-esteem and coping strategies included as mediators. The…

  8. The relationship between personality, social functioning, and depression: a structural equation modeling analysis.

    Science.gov (United States)

    Tse, Wai S; Rochelle, Tina L; Cheung, Jacky C K

    2011-06-01

    The relationship between personality, social functioning, and depression remains unclear. The present study employs structural equation modeling to examine the mediating role of social functioning between harm avoidance (HA), self-directedness (SD), and depression. A sample of 902 individuals completed a self-report questionnaire consisting of the following scales: HA and SD subscales of the Temperament and Character Inventory (TCI), Beck Depression Inventory (BDI), and Social Adaptation Self-Evaluation Scale (SASS). Structural equation modeling via analysis of moment structure was used to estimate the fit of nine related models. Results indicated that social functioning is a mediator between harm avoidance or self-directness and depression. Self-directedness was also shown to have direct effects on depression. The results support the social reinforcement theory of depression and provide a theoretical account of how the variables are related based on correlation methods. Suggestions are offered for future experimental and longitudinal research.

  9. Applications of meta-analytic structural equation modelling in health psychology: examples, issues, and recommendations.

    Science.gov (United States)

    Cheung, Mike W-L; Hong, Ryan Y

    2017-09-01

    Statistical methods play an important role in behavioural, medical, and social sciences. Two recent statistical advances are structural equation modelling (SEM) and meta-analysis. SEM is used to test hypothesised models based on substantive theories, which can be path, confirmatory factor analytic, or full structural equation models. Meta-analysis is used to synthesise research findings in a particular topic. This article demonstrates another recent statistical advance - meta-analytic structural equation modelling (MASEM) - that combines meta-analysis and SEM to synthesise research findings for the purpose of testing hypothesised models. Using the theory of planned behaviour as an example, we show how MASEM can be used to address important research questions that cannot be answered by univariate meta-analyses on Pearson correlations. Specifically, MASEM allows researchers to: (1) test whether the proposed models are consistent with the data; (2) estimate partial effects after controlling for other variables; (3) estimate functions of parameter estimates such as indirect effects; and (4) include latent variables in the models. We illustrate the procedures with an example on the theory of planned behaviour. Practical issues in MASEM and suggested solutions are discussed.

  10. Investigating The Relationship Between Flourishing And Self-Compassion: A Structural Equation Modeling Approach

    OpenAIRE

    Seydi Ahmet Satici; Recep Uysal; Ahmet Akin

    2013-01-01

    The purpose of this study was to examine the relationships between flourishing and self-compassion. Participants were 347 (194 female and 153 male) university students, between age range of 18-24, who completed a questionnaire package that included the Flourishing Scale and the Self-compassion Scale. The relationships between flourishing and self-compassion were examined using correlation analysis and the hypothesis model was tested through structural equation modeling. In correlation analysi...

  11. Comparing Bayesian and Maximum Likelihood Predictors in Structural Equation Modeling of Children’s Lifestyle Index

    OpenAIRE

    Che Wan Jasimah bt Wan Mohamed Radzi; Huang Hui; Hashem Salarzadeh Jenatabadi

    2016-01-01

    Several factors may influence children’s lifestyle. The main purpose of this study is to introduce a children’s lifestyle index framework and model it based on structural equation modeling (SEM) with Maximum likelihood (ML) and Bayesian predictors. This framework includes parental socioeconomic status, household food security, parental lifestyle, and children’s lifestyle. The sample for this study involves 452 volunteer Chinese families with children 7–12 years old. The experimental results a...

  12. Airline Sustainability Modeling: A New Framework with Application of Bayesian Structural Equation Modeling

    Directory of Open Access Journals (Sweden)

    Hashem Salarzadeh Jenatabadi

    2016-11-01

    Full Text Available There are many factors which could influence the sustainability of airlines. The main purpose of this study is to introduce a framework for a financial sustainability index and model it based on structural equation modeling (SEM with maximum likelihood and Bayesian predictors. The introduced framework includes economic performance, operational performance, cost performance, and financial performance. Based on both Bayesian SEM (Bayesian-SEM and Classical SEM (Classical-SEM, it was found that economic performance with both operational performance and cost performance are significantly related to the financial performance index. The four mathematical indices employed are root mean square error, coefficient of determination, mean absolute error, and mean absolute percentage error to compare the efficiency of Bayesian-SEM and Classical-SEM in predicting the airline financial performance. The outputs confirmed that the framework with Bayesian prediction delivered a good fit with the data, although the framework predicted with a Classical-SEM approach did not prepare a well-fitting model. The reasons for this discrepancy between Classical and Bayesian predictions, as well as the potential advantages and caveats with the application of Bayesian approach in airline sustainability studies, are debated.

  13. Parallel workflows for data-driven structural equation modeling in functional neuroimaging

    Directory of Open Access Journals (Sweden)

    Sarah Kenny

    2009-10-01

    Full Text Available We present a computational framework suitable for a data-driven approach to structural equation modeling (SEM and describe several workflows for modeling functional magnetic resonance imaging (fMRI data within this framework. The Computational Neuroscience Applications Research Infrastructure (CNARI employs a high-level scripting language called Swift, which is capable of spawning hundreds of thousands of simultaneous R processes (R Core Development Team, 2008, consisting of self-contained structural equation models, on a high performance computing system (HPC. These self-contained R processing jobs are data objects generated by OpenMx, a plug-in for R, which can generate a single model object containing the matrices and algebraic information necessary to estimate parameters of the model. With such an infrastructure in place a structural modeler may begin to investigate exhaustive searches of the model space. Specific applications of the infrastructure, statistics related to model fit, and limitations are discussed in relation to exhaustive SEM. In particular, we discuss how workflow management techniques can help to solve large computational problems in neuroimaging.

  14. metaSEM: an R package for meta-analysis using structural equation modeling.

    Science.gov (United States)

    Cheung, Mike W-L

    2014-01-01

    The metaSEM package provides functions to conduct univariate, multivariate, and three-level meta-analyses using a structural equation modeling (SEM) approach via the OpenMx package in the R statistical platform. It also implements the two-stage SEM approach to conducting fixed- and random-effects meta-analytic SEM on correlation or covariance matrices. This paper briefly outlines the theories and their implementations. It provides a summary on how meta-analyses can be formulated as structural equation models. The paper closes with a conclusion on several relevant topics to this SEM-based meta-analysis. Several examples are used to illustrate the procedures in the supplementary material.

  15. A Structural Equation Modelling of the Academic Self-Concept Scale

    OpenAIRE

    Musa MATOVU

    2014-01-01

    The study aimed at validating the academic self-concept scale by Liu and Wang (2005) in measuring academic self-concept among university students. Structural equation modelling was used to validate the scale which was composed of two subscales; academic confidence and academic effort. The study was conducted on university students; males and females from different levels of study and faculties. In this study the influence of academic self-concept on academic achievement was assessed, tested w...

  16. Maternal feeding strategies and child's food intake: considering weight and demographic influences using structural equation modeling

    OpenAIRE

    Warschburger Petra; Kröller Katja

    2009-01-01

    Abstract Background Research concerning child's food intake have considered various influencing factors, for example parental feeding strategies, demographic and weight factors. At this time, however, there are few findings that explore these factors simultaneously. Accordingly, the aim of this study was to test a structural equation model regarding the associations between maternal feeding strategies and child's food intake. Methods 556 mothers and their children between 1 and 10 years of ag...

  17. Behavioural Comparison of Driverswhen Driving a Motorcycle or a Car: A Structural Equation Modelling Study

    OpenAIRE

    Darja Topolšek; Dejan Dragan

    2015-01-01

    The goal of the study was to investigate if the drivers behave in the same way when they are driving a motorcycle or a car. For this purpose, the Motorcycle Rider Behaviour Questionnaire and Driver Behaviour Questionnaire were conducted among the same drivers population. Items of questionnaires were used to develop a structural equation model with two factors, one for the motorcyclist’s behaviour, and the other for the car driver’s behaviour. Exploratory and confirmatory factor analyses were ...

  18. A STRUCTURAL EQUATION MODEL: THAILAND’S INTERNATIONAL TOURISM DEMAND FOR TOURIST DESTINATION

    OpenAIRE

    CHUKIAT CHAIBOONSRI; PRASERT CHAITIP

    2008-01-01

    Structural equation modelling (LISREL 8) was used to test the causal relationships between tourist travel motivations (travel cost satisfaction and tourist demographics) and tourist destination (tourism product, tourism product attributes, and tourism product management). A survey containing Likert-type scales was used in collecting data from 203 international tourists who had travelled to Thailand. Using factor analysis, dimensions were identified for scales used in the study: travel cost sa...

  19. A Structural Equation Model: India’s International Tourism Demand for Tourist Destination

    OpenAIRE

    N. Rangaswamy; Chukiat Chaiboonsri; Prasert Chaitip

    2008-01-01

    Structural equation modeling (LISREL 8) was used to test the causal relationships between tourist travel motivations (travel cost satisfaction) and tourist destination (tourism product, tourism product attributes, and tourism product management). A survey containing Likert-type scales was used in collecting data from 100 international tourists who had traveled to India. Using factor analysis, dimensions were identified for scales used in the study: travel cost satisfaction, tourism product, t...

  20. A STRUCTURAL EQUATION MODEL: GREECE’S TOURISM DEMAND FOR TOURIST DESTINATION

    OpenAIRE

    Chaitip, Prasert; Chaiboonsri, Chukiat; Kovacs, Sandor; Balogh, Peter

    2010-01-01

    Structural equation model (LISREL 8) was applied to test the causal relationships between tourist travel motivations and tourist destination. A survey containing Likert scale questions was conducted to collect data from 100 tourists who had travelled to Greece’s tourist destination. With the help of factor analysis, four dimensions were identified for scales used in the study: travel cost satisfaction, tourism product, tourism product attributes, and tourism product management. Results indi...

  1. Structural equation modeling: a framework for ocular and other medical sciences research.

    Science.gov (United States)

    Christ, Sharon L; Lee, David J; Lam, Byron L; Zheng, D Diane

    2014-02-01

    Structural equation modeling (SEM) is a modeling framework that encompasses many types of statistical models and can accommodate a variety of estimation and testing methods. SEM has been used primarily in social sciences but is increasingly used in epidemiology, public health, and the medical sciences. SEM provides many advantages for the analysis of survey and clinical data, including the ability to model latent constructs that may not be directly observable. Another major feature is simultaneous estimation of parameters in systems of equations that may include mediated relationships, correlated dependent variables, and in some instances feedback relationships. SEM allows for the specification of theoretically holistic models because multiple and varied relationships may be estimated together in the same model. SEM has recently expanded by adding generalized linear modeling capabilities that include the simultaneous estimation of parameters of different functional form for outcomes with different distributions in the same model. Therefore, mortality modeling and other relevant health outcomes may be evaluated. Random effects estimation using latent variables has been advanced in the SEM literature and software. In addition, SEM software has increased estimation options. Therefore, modern SEM is quite general and includes model types frequently used by health researchers, including generalized linear modeling, mixed effects linear modeling, and population average modeling. This article does not present any new information. It is meant as an introduction to SEM and its uses in ocular and other health research.

  2. Vector autoregression, structural equation modeling, and their synthesis in neuroimaging data analysis.

    Science.gov (United States)

    Chen, Gang; Glen, Daniel R; Saad, Ziad S; Paul Hamilton, J; Thomason, Moriah E; Gotlib, Ian H; Cox, Robert W

    2011-12-01

    Vector autoregression (VAR) and structural equation modeling (SEM) are two popular brain-network modeling tools. VAR, which is a data-driven approach, assumes that connected regions exert time-lagged influences on one another. In contrast, the hypothesis-driven SEM is used to validate an existing connectivity model where connected regions have contemporaneous interactions among them. We present the two models in detail and discuss their applicability to FMRI data, and their interpretational limits. We also propose a unified approach that models both lagged and contemporaneous effects. The unifying model, structural vector autoregression (SVAR), may improve statistical and explanatory power, and avoid some prevalent pitfalls that can occur when VAR and SEM are utilized separately.

  3. Trichotomous goals of elementary school students learning English as a foreign language: a structural equation model.

    Science.gov (United States)

    He, Tung-Hsien; Chang, Shan-Mao; Chen, Shu-Hui Eileen; Gou, Wen Johnny

    2012-02-01

    This study applied structural equation modeling (SEM) techniques to define the relations among trichotomous goals (mastery goals, performance-approach goals, and performance-avoidance goals), self-efficacy, use of metacognitive self-regulation strategies, positive belief in seeking help, and help-avoidance behavior. Elementary school students (N = 105), who were learning English as a foreign language, were surveyed using five self-report scales. The structural equation model showed that self-efficacy led to the adoption of mastery goals but discouraged the adoption of performance-approach goals and performance-avoidance goals. Furthermore, mastery goals increased the use of metacognitive self-regulation strategies, whereas performance-approach goals and performance-avoidance goals reduced their use. Mastery goals encouraged positive belief in help-seeking, but performance-avoidance goals decreased such belief. Finally, performance-avoidance goals directly led to help-avoidance behavior, whereas positive belief assumed a critical role in reducing help-avoidance. The established structural equation model illuminated the potential causal relations among these variables for the young learners in this study.

  4. A systematic review of the main factors that determine agility in sport using structural equation modeling.

    Science.gov (United States)

    Hojka, Vladimir; Stastny, Petr; Rehak, Tomas; Gołas, Artur; Mostowik, Aleksandra; Zawart, Marek; Musálek, Martin

    2016-09-01

    While tests of basic motor abilities such as speed, maximum strength or endurance are well recognized, testing of complex motor functions such as agility remains unresolved in current literature. Therefore, the aim of this review was to evaluate which main factor or factor structures quantitatively determine agility. In methodological detail, this review focused on research that explained or described the relationships between latent variables in a factorial model of agility using approaches such as principal component analysis, factor analysis and structural equation modeling. Four research studies met the defined inclusion criteria. No quantitative empirical research was found that tried to verify the quality of the whole suggested model of the main factors determining agility through the use of a structural equation modeling (SEM) approach or a confirmatory factor analysis. From the whole structure of agility, only change of direction speed (CODS) and some of its subtests were appropriately analyzed. The combination of common CODS tests is reliable and useful to estimate performance in sub-elite athletes; however, for elite athletes, CODS tests must be specific to the needs of a particular sport discipline. Sprinting and jumping tests are stronger factors for CODS than explosive strength and maximum strength tests. The authors suggest the need to verify the agility factorial model by a second generation data analysis technique such as SEM.

  5. A Model for Integrating Fixed-, Random-, and Mixed-Effects Meta-Analyses into Structural Equation Modeling

    Science.gov (United States)

    Cheung, Mike W.-L.

    2008-01-01

    Meta-analysis and structural equation modeling (SEM) are two important statistical methods in the behavioral, social, and medical sciences. They are generally treated as two unrelated topics in the literature. The present article proposes a model to integrate fixed-, random-, and mixed-effects meta-analyses into the SEM framework. By applying an…

  6. Do Test Design and Uses Influence Test Preparation? Testing a Model of Washback with Structural Equation Modeling

    Science.gov (United States)

    Xie, Qin; Andrews, Stephen

    2013-01-01

    This study introduces Expectancy-value motivation theory to explain the paths of influences from perceptions of test design and uses to test preparation as a special case of washback on learning. Based on this theory, two conceptual models were proposed and tested via Structural Equation Modeling. Data collection involved over 870 test takers of…

  7. Do Test Design and Uses Influence Test Preparation? Testing a Model of Washback with Structural Equation Modeling

    Science.gov (United States)

    Xie, Qin; Andrews, Stephen

    2013-01-01

    This study introduces Expectancy-value motivation theory to explain the paths of influences from perceptions of test design and uses to test preparation as a special case of washback on learning. Based on this theory, two conceptual models were proposed and tested via Structural Equation Modeling. Data collection involved over 870 test takers of…

  8. A STRUCTURAL EQUATION MODEL-II FOR WORK-LIFE BALANCE OF IT PROFESSIONALS IN CHENNAI

    Directory of Open Access Journals (Sweden)

    Rashida A. Banu

    2016-05-01

    Full Text Available The study developed and tested a model of work life balance of IT professionals employing structural equation modeling (SEM to analyze the relationship between work place support (WPS and work interference with personal life (WIPL, personal life interference with work (PLIW, satisfaction with work-life balance (SWLB and improved effectiveness at work (IEW. The model fit the data well and hypotheses are generally supported. WPS and SWLB are negatively related to WIPL and PLIW. However, there is a positive relationship between SWLB and IEW.

  9. Job and Professional Leaving Among Newly Licensed RNs: A Structural Equation Model.

    Science.gov (United States)

    Unruh, Lynn; Zhang, Ning Jackie; Chisolm, Latarsha

    2016-01-01

    With more than 50% of the nursing workforce close to retirement, it is especially important to keep younger nurses in nursing jobs and careers. This study empirically tests a structural equation model of registered nurse (RN) intent to leave the job and profession using data from a survey of newly licensed RNs (NLRNs). Job demands, difficulties and control, intent to leave the job, and intent to leave the profession were latent variables. A number of direct, indirect, and mediating relationships were modeled. Measurement models for all latent variables and the structural model had good fit. The final model showed a path from job demands, difficulties, and control to job satisfaction to intent to leave the job to intent to leave the profession. The results suggest that the process of an NLRN intending to leave the job and profession involves a number of mediators between the work environment and this intent.

  10. Somatic Expression of Psychological Problems (Somatization: Examination with Structural Equation Model

    Directory of Open Access Journals (Sweden)

    Tugba Seda Çolak

    2014-09-01

    Full Text Available The main purpose of the research is to define which psychological symptoms (somatization, depression, obsessive ‐ compulsive, hostility, interpersonal sensitivity, anxiety, phobic anxiety, paranoid ideation and psychoticism cause somatic reactions at most. Total effect of these psychological symptoms on somatic symptoms had been investigated. Study was carried out with structural equation model to research the relation between the psychological symptoms and somatization. The main material of the research is formed by the data obtained from 492 people. SCL‐90‐R scale was used in order to obtain the data. As a result of the structural equation analysis, it has been found that 1Psychoticism, phobic anxiety, and paranoid ideation do not predict somatic symptoms.2There is a negative relation between interpersonal sensitivity level mand somatic reactions.3Anxiety symptoms had been found as causative to occur the highest level of somatic reactions.

  11. Estimation of health effects of prenatal methylmercury exposure using structural equation models

    DEFF Research Database (Denmark)

    Budtz-Jørgensen, Esben; Keiding, Niels; Grandjean, Philippe

    2002-01-01

    BACKGROUND: Observational studies in epidemiology always involve concerns regarding validity, especially measurement error, confounding, missing data, and other problems that may affect the study outcomes. Widely used standard statistical techniques, such as multiple regression analysis, may...... to some extent adjust for these shortcomings. However, structural equations may incorporate most of these considerations, thereby providing overall adjusted estimations of associations. This approach was used in a large epidemiological data set from a prospective study of developmental methyl......-mercury toxicity. RESULTS: Structural equation models were developed for assessment of the association between biomarkers of prenatal mercury exposure and neuropsychological test scores in 7 year old children. Eleven neurobehavioral outcomes were grouped into motor function and verbally mediated function...

  12. Emotional dysregulation, internalizing symptoms, and self-injurious and suicidal behavior: Structural equation modeling analysis.

    Science.gov (United States)

    Kranzler, Amy; Fehling, Kara B; Anestis, Michael D; Selby, Edward A

    2016-07-01

    This study used structural equation modeling to examine the relationships between emotion dysregulation, internalizing symptoms, nonsuicidal self-injury (NSSI), and suicide. One hundred forty-eight undergraduates completed a brief structured interview and self-report measures of emotion dysregulation, internalizing symptoms, and NSSI and suicidal behaviors. Results indicated a significant indirect effect of emotion dysregulation on NSSI via internalizing symptoms and on suicide attempts via NSSI. Findings provide a more nuanced understanding of the indirect association between emotion dysregulation and NSSI and suicidal behaviors. Implications for the potential utility of targeting internalizing symptoms as well as emotion dysregulation in interventions addressing NSSI and suicidal behaviors are discussed.

  13. A Structural Equation Modelling for CRM Development in rural Tourism in the Catalan Pyrenees

    Directory of Open Access Journals (Sweden)

    José Mª Prat Forga

    2014-12-01

    Full Text Available This paper investigates the interrelationships between customer relationship management development in rural tourism, information and communication technologies level in the territory, perceived economic impacts and rural tourism development. A total of 76 respondents completed a survey conducted in the Spanish Pyrenees Mountains in order to examine the structural effects of these impact factors. The results reveal that the support for customer relationship management development in rural tourism shown by rural tourism workers mainly depends on the level of development of information and communication technologies. A confirmatory factor analysis and structural equation modelling procedure were performed, respectively, using the AMOS software. 

  14. A Structural Equation Modelling for Crm Development in Rural Tourism in the Catalan Pyrenees

    Directory of Open Access Journals (Sweden)

    José Mª Prat Forga

    2013-02-01

    Full Text Available This paper investigates the interrelationships between customer relationship management development in rural tourism, information and communication technologies level in the territory, perceived economic impacts and rural tourism development. A total of 76 respondents completed a survey conducted in the Spanish Pyrenees Mountains in order to examine the structural effects of these impact factors. The results reveal that the support for customer relationship management development in rural tourism shown by rural tourism workers mainly depends on the level of development of information and communication technologies. A confirmatory factor analysis and structural equation modelling procedure were performed, respectively, using the AMOS software.

  15. Multiple Group Analysis in Multilevel Structural Equation Model Across Level 1 Groups.

    Science.gov (United States)

    Ryu, Ehri

    2015-01-01

    This article introduces and evaluates a procedure for conducting multiple group analysis in multilevel structural equation model across Level 1 groups (MG1-MSEM; Ryu, 2014). When group membership is at Level 1, multiple group analysis raises two issues that cannot be solved by a simple extension of the standard multiple group analysis in single-level structural equation model. First, the Level 2 data are not independent between Level 1 groups. Second, the standard procedure fails to take into account the dependency between members of different Level 1 groups within the same cluster. The MG1-MSEM approach provides solutions to these problems. In MG1-MSEM, the Level 1 mean structure is necessary to represent the differences between Level 1 groups within clusters. The Level 2 model is the same regardless of Level 1 group membership. A simulation study examined the performance of MUML (Muthén's maximum likelihood) estimation in MG1-MSEM. The MG1-MSEM approach is illustrated for both a multilevel path model and a multilevel factor model using empirical data sets.

  16. OpenMx 2.0: Extended Structural Equation and Statistical Modeling.

    Science.gov (United States)

    Neale, Michael C; Hunter, Michael D; Pritikin, Joshua N; Zahery, Mahsa; Brick, Timothy R; Kirkpatrick, Robert M; Estabrook, Ryne; Bates, Timothy C; Maes, Hermine H; Boker, Steven M

    2016-06-01

    The new software package OpenMx 2.0 for structural equation and other statistical modeling is introduced and its features are described. OpenMx is evolving in a modular direction and now allows a mix-and-match computational approach that separates model expectations from fit functions and optimizers. Major backend architectural improvements include a move to swappable open-source optimizers such as the newly written CSOLNP. Entire new methodologies such as item factor analysis and state space modeling have been implemented. New model expectation functions including support for the expression of models in LISREL syntax and a simplified multigroup expectation function are available. Ease-of-use improvements include helper functions to standardize model parameters and compute their Jacobian-based standard errors, access to model components through standard R $ mechanisms, and improved tab completion from within the R Graphical User Interface.

  17. Representing general theoretical concepts in structural equation models: The role of composite variables

    Science.gov (United States)

    Grace, J.B.; Bollen, K.A.

    2008-01-01

    Structural equation modeling (SEM) holds the promise of providing natural scientists the capacity to evaluate complex multivariate hypotheses about ecological systems. Building on its predecessors, path analysis and factor analysis, SEM allows for the incorporation of both observed and unobserved (latent) variables into theoretically-based probabilistic models. In this paper we discuss the interface between theory and data in SEM and the use of an additional variable type, the composite. In simple terms, composite variables specify the influences of collections of other variables and can be helpful in modeling heterogeneous concepts of the sort commonly of interest to ecologists. While long recognized as a potentially important element of SEM, composite variables have received very limited use, in part because of a lack of theoretical consideration, but also because of difficulties that arise in parameter estimation when using conventional solution procedures. In this paper we present a framework for discussing composites and demonstrate how the use of partially-reduced-form models can help to overcome some of the parameter estimation and evaluation problems associated with models containing composites. Diagnostic procedures for evaluating the most appropriate and effective use of composites are illustrated with an example from the ecological literature. It is argued that an ability to incorporate composite variables into structural equation models may be particularly valuable in the study of natural systems, where concepts are frequently multifaceted and the influence of suites of variables are often of interest. ?? Springer Science+Business Media, LLC 2007.

  18. Evaluation of an occupational health educational program based on alumni perceptions in Iran: Structural equation model.

    Science.gov (United States)

    Mehralizadeh, Semira; Dehdashti, Alireza; Kashani, Masoud Motalebi

    2017-07-26

    Evaluating educational program can improve the quality of education that learners receive. The present study evaluated undergraduate occupational health educational program at Medical sciences university of Semnan, Iran, focused on the associations between alumni perceptions of learning environment and outcomes in occupational health program. cross-sectional questionnaire survey was carried out among alumni of occupational health enrolled in an undergraduate program. We asked alumni to rate their perceptions of the items based on a Likert four-point scale. The associations between alumni perceptions of educational program and curriculum, faculty, institutional resources and learning outcomes were modeled and described using structural equation modeling procedures. Descriptive perception indicated low evaluations for administration systems, practical and research based courses and the number of faculty members. Results indicated a structural model of the evaluation variables of curriculum, faculty qualification, and institutional resources significantly predict undergraduate educational program outcomes. Curriculum had direct and indirect effects on learning outcomes mediated by faculty. study findings highlight the usefulness of structural equation modeling approach with which to examine linking between variables of learning process and learning outcomes. Surveys among alumni permit to provide data to reassess the learning environment in the light of professional competencies needed for occupational health graduates.

  19. Determinants of quality of life in patients with fibromyalgia: A structural equation modeling approach

    Science.gov (United States)

    Lee, Jeong-Won; Lee, Kyung-Eun; Park, Dong-Jin; Kim, Seong-Ho; Nah, Seong-Su; Lee, Ji Hyun; Kim, Seong-Kyu; Lee, Yeon-Ah; Hong, Seung-Jae; Kim, Hyun-Sook; Lee, Hye-Soon; Kim, Hyoun Ah; Joung, Chung-Il; Kim, Sang-Hyon

    2017-01-01

    Objective Health-related quality of life (HRQOL) in patients with fibromyalgia (FM) is lower than in patients with other chronic diseases and the general population. Although various factors affect HRQOL, no study has examined a structural equation model of HRQOL as an outcome variable in FM patients. The present study assessed relationships among physical function, social factors, psychological factors, and HRQOL, and the effects of these variables on HRQOL in a hypothesized model using structural equation modeling (SEM). Methods HRQOL was measured using SF-36, and the Fibromyalgia Impact Questionnaire (FIQ) was used to assess physical dysfunction. Social and psychological statuses were assessed using the Beck Depression Inventory (BDI), the State-Trait Anxiety Inventory (STAI), the Arthritis Self-Efficacy Scale (ASES), and the Social Support Scale. SEM analysis was used to test the structural relationships of the model using the AMOS software. Results Of the 336 patients, 301 (89.6%) were women with an average age of 47.9±10.9 years. The SEM results supported the hypothesized structural model (χ2 = 2.336, df = 3, p = 0.506). The final model showed that Physical Component Summary (PCS) was directly related to self-efficacy and inversely related to FIQ, and that Mental Component Summary (MCS) was inversely related to FIQ, BDI, and STAI. Conclusions In our model of FM patients, HRQOL was affected by physical, social, and psychological variables. In these patients, higher levels of physical function and self-efficacy can improve the PCS of HRQOL, while physical function, depression, and anxiety negatively affect the MCS of HRQOL. PMID:28158289

  20. Health Promotion Behavior of Chinese International Students in Korea Including Acculturation Factors: A Structural Equation Model.

    Science.gov (United States)

    Kim, Sun Jung; Yoo, Il Young

    2016-03-01

    The purpose of this study was to explain the health promotion behavior of Chinese international students in Korea using a structural equation model including acculturation factors. A survey using self-administered questionnaires was employed. Data were collected from 272 Chinese students who have resided in Korea for longer than 6 months. The data were analyzed using structural equation modeling. The p value of final model is .31. The fitness parameters of the final model such as goodness of fit index, adjusted goodness of fit index, normed fit index, non-normed fit index, and comparative fit index were more than .95. Root mean square of residual and root mean square error of approximation also met the criteria. Self-esteem, perceived health status, acculturative stress and acculturation level had direct effects on health promotion behavior of the participants and the model explained 30.0% of variance. The Chinese students in Korea with higher self-esteem, perceived health status, acculturation level, and lower acculturative stress reported higher health promotion behavior. The findings can be applied to develop health promotion strategies for this population. Copyright © 2016. Published by Elsevier B.V.

  1. Guidelines for a graph-theoretic implementation of structural equation modeling

    Science.gov (United States)

    Grace, James B.; Schoolmaster, Donald R.; Guntenspergen, Glenn R.; Little, Amanda M.; Mitchell, Brian R.; Miller, Kathryn M.; Schweiger, E. William

    2012-01-01

    Structural equation modeling (SEM) is increasingly being chosen by researchers as a framework for gaining scientific insights from the quantitative analyses of data. New ideas and methods emerging from the study of causality, influences from the field of graphical modeling, and advances in statistics are expanding the rigor, capability, and even purpose of SEM. Guidelines for implementing the expanded capabilities of SEM are currently lacking. In this paper we describe new developments in SEM that we believe constitute a third-generation of the methodology. Most characteristic of this new approach is the generalization of the structural equation model as a causal graph. In this generalization, analyses are based on graph theoretic principles rather than analyses of matrices. Also, new devices such as metamodels and causal diagrams, as well as an increased emphasis on queries and probabilistic reasoning, are now included. Estimation under a graph theory framework permits the use of Bayesian or likelihood methods. The guidelines presented start from a declaration of the goals of the analysis. We then discuss how theory frames the modeling process, requirements for causal interpretation, model specification choices, selection of estimation method, model evaluation options, and use of queries, both to summarize retrospective results and for prospective analyses. The illustrative example presented involves monitoring data from wetlands on Mount Desert Island, home of Acadia National Park. Our presentation walks through the decision process involved in developing and evaluating models, as well as drawing inferences from the resulting prediction equations. In addition to evaluating hypotheses about the connections between human activities and biotic responses, we illustrate how the structural equation (SE) model can be queried to understand how interventions might take advantage of an environmental threshold to limit Typha invasions. The guidelines presented provide for

  2. Structural equation models of memory performance across noise conditions and age groups.

    Science.gov (United States)

    Enmarker, Ingela; Boman, Eva; Hygge, Staffan

    2006-12-01

    Competing models of declarative memory were tested with structural equation models to analyze whether a second-order latent variable structure for episodic and semantic memory was invariant across age groups and across noise exposure conditions. Data were taken from three previous experimental noise studies that were performed with the same design, procedure, and dependent measures, and with participants from four age groups (13-14, 18-20, 35-45, and 55-65 years). Two noise conditions, road traffic noise and meaningful irrelevant speech, were compared to a quiet control group. The structural models put to the test were taken from Nyberg et al. (2003), which employed several memory tests that were the same as ours and studied age-groups that partly overlapped with our groups. In addition we also varied noise exposure conditions. Our analyses replicated and supported the second-order semantic-episodic memory models in Nyberg et al. (2003). The latent variable structures were invariant across age groups, with the exception of our youngest group, which by itself showed a less clear latent structure. The obtained structures were also invariant across noise exposure conditions. We also noted that our text memory items, which did not have a counterpart in the study by Nyberg et al. (2003), tend to form a separate latent variable loading on episodic memory.

  3. Spatially-explicit matrix models. A mathematical analysis of stage-structured integrodifference equations.

    Science.gov (United States)

    Lutscher, Frithjof; Lewis, Mark A

    2004-03-01

    This paper is concerned with mathematical analysis of the 'critical domain-size' problem for structured populations. Space is introduced explicitly into matrix models for stage-structured populations. Movement of individuals is described by means of a dispersal kernel. The mathematical analysis investigates conditions for existence, stability and uniqueness of equilibrium solutions as well as some bifurcation behaviors. These mathematical results are linked to species persistence or extinction in connected habitats of different sizes or fragmented habitats; hence the framework is given for application of such models to ecology. Several approximations which reduce the complexity of integrodifference equations are given. A simple example is worked out to illustrate the analytical results and to compare the behavior of the integrodifference model to that of the approximations.

  4. Post-partum blues among Korean mothers: a structural equation modelling approach.

    Science.gov (United States)

    Chung, Sung Suk; Yoo, Il Young; Joung, Kyoung Hwa

    2013-08-01

    The objective of this study was to propose the post-partum blues (PPB) model and to estimate the effects of self-esteem, social support, antenatal depression, and stressful events during pregnancy on PPB. Data were collected from 249 women post-partum during their stay in the maternity units of three hospitals in Korea using a self-administered questionnaire. A structural equation modelling approach using the Analysis of Moments Structure program was used to identify the direct and indirect effects of the variables on PPB. The full model had a good fit and accounted for 70.3% of the variance of PPB. Antenatal depression and stressful events during pregnancy had strong direct effects on PPB. Household income showed indirect effects on PPB via self-esteem and antenatal depression. Social support indirectly affected PPB via self-esteem, antenatal depression, and stressful events during pregnancy.

  5. Direct and Indirect Effects of Education on Job Satisfaction: A Structural Equation Model for the Spanish Case

    Science.gov (United States)

    Fabra, M. Eugenia; Camison, Cesar

    2009-01-01

    Empirical literature has traditionally analyzed the effect of education on job satisfaction with single-equation models that ignore interrelationships between theoretical explanatory variables. Their results are somewhat inconclusive. We propose estimating a structural equation model to obtain both the direct effects and the set of indirect…

  6. An Investigation on Effects of Spiritual Leadership towards Employee’s Happiness Using Structural Equation Modeling

    Directory of Open Access Journals (Sweden)

    Farnaz Beheshti Zavvareh

    2013-08-01

    Full Text Available Some believe that there is always a link between happiness and an individual health. This paper addresses a researched question as: How does a leader’s spiritual beliefs and spiritual practices affects on happiness as perceived by ones followers. In this study, it was constructed an original model to carry out a research analysis at some universities in Isfahan. The main objective of the researched model is to investigate the employee’s happiness in terms of spiritual leadership. We used Structural Equation Modeling. In our proposed model, we assume that spiritual leadership is composed of: The values of vision, hope/faith, altruistic love, meaning/ calling and, membership. Additionally there is a link from spiritual leadership to happiness. The research was applied over 90 employees in universities of Isfahan. According to prepared results, it has been determined that the constructed model is significant and employee’s happiness and has some positive significant correlations with spiritual leadership.

  7. Students’ Decisions to Use an eLearning System: A Structural Equation Modelling Analysis

    Directory of Open Access Journals (Sweden)

    Muneer Abbad

    2009-12-01

    Full Text Available This research investigates and identifies some of the major factors affecting students’ adoption of an e-learning system at Arab Open University in Jordan. E-learning adoption is approached from the information systems acceptance point of view. An extended version of the Technology Acceptance Model (TAM was developed to investigate the underlying factors that influence students’ decisions to use an e-learning system. The proposed model uses the actual use of an e-learning system. It is different from most of the prior TAM studies, which only used a single dependent variable (intention to use. The model was estimated using Structural Equation Modelling (SEM. The final models derived from this study indicated that beliefs of usefulness and ease of use partially mediate the relationship between external factors and intention to use and actual use of e-learning systems.

  8. Latent variables and structural equation models for longitudinal relationships: an illustration in nutritional epidemiology

    Directory of Open Access Journals (Sweden)

    Basdevant Arnaud

    2010-04-01

    Full Text Available Abstract Background The use of structural equation modeling and latent variables remains uncommon in epidemiology despite its potential usefulness. The latter was illustrated by studying cross-sectional and longitudinal relationships between eating behavior and adiposity, using four different indicators of fat mass. Methods Using data from a longitudinal community-based study, we fitted structural equation models including two latent variables (respectively baseline adiposity and adiposity change after 2 years of follow-up, each being defined, by the four following anthropometric measurement (respectively by their changes: body mass index, waist circumference, skinfold thickness and percent body fat. Latent adiposity variables were hypothesized to depend on a cognitive restraint score, calculated from answers to an eating-behavior questionnaire (TFEQ-18, either cross-sectionally or longitudinally. Results We found that high baseline adiposity was associated with a 2-year increase of the cognitive restraint score and no convincing relationship between baseline cognitive restraint and 2-year adiposity change could be established. Conclusions The latent variable modeling approach enabled presentation of synthetic results rather than separate regression models and detailed analysis of the causal effects of interest. In the general population, restrained eating appears to be an adaptive response of subjects prone to gaining weight more than as a risk factor for fat-mass increase.

  9. Bidirectional Relationship between Chronic Kidney Disease and Periodontal Disease: Structural Equation Modeling

    Science.gov (United States)

    Fisher, Monica A.; Taylor, George W.; West, Brady T.; McCarthy, Ellen T.

    2011-01-01

    Periodontal disease is associated with diabetes, heart disease, and chronic kidney disease (CKD), an effect postulated to be due in part to endovascular inflammation. While a bidirectional relationship between CKD and periodontal disease is plausible, it has not been previously reported in the literature. Over 11 200 adults 18 years or older were identified in the Third National Health and Nutrition Examination Survey. Analyses were conducted in two stages. First, multivariable logistic regression models were fitted to test the hypothesis that periodontal disease was independently associated with CKD. Given the potential that the periodontal disease and CKD relationship may be bidirectional, a two-step analytic approach was used that involved 1) tests for mediation, and 2) structural equation models to examine more complex direct and indirect effects of periodontal disease on CKD, and vice versa. In two separate models periodontal disease (ORAdj =1.62 (95% CI: 1.17-2.26) and edentulism (ORAdj = 1.83 (1.31-2.55) and periodontal disease score (ORAdj = 1.01 (1.01-1.02) were associated with CKD, when simultaneously adjusting for 14 other factors. Three of four structural equation models were most plausible suggesting bidirectional relationships. Collectively, these analyses provide for the first time empirical support for a bidirectional relationship between CKD and periodontal disease, and mediation of that relationship by diabetes duration and hypertension. PMID:20927035

  10. Role of Student Well-Being: A Study Using Structural Equation Modeling.

    Science.gov (United States)

    Phan, Huy P; Ngu, Bing H; Alrashidi, Oqab

    2016-08-01

    The present study explored the effects of academic and social self-efficacy beliefs on students' well-being at school, academic engagement, and achievement outcome. Well-being at school is conceptualized as a central mediator of students' engagement and learning in achievement contexts. It was hypothesized that well-being at school would mediate the effects of social and academic self-efficacy beliefs on engagement and achievement outcome. This research focus has credence and may provide grounding for educational-social interventions. A cohort of 284 (122 girls, 162 boys) Year 11 secondary school students participated in this correlational study. A theoretical-conceptual model was explored and tested using structural equation modeling. Subsequent structural equation modeling analyses provided moderate support for the hypothesized model. The results showed that both academic and social self-efficacy depended on each other in their effect on well-being at school. Both academic engagement and well-being at school served as partial mediators of the effects of academic and social self-efficacy on academic engagement.

  11. Tourism sector, Travel agencies, and Transport Suppliers: Comparison of Different Estimators in the Structural Equation Modeling

    Directory of Open Access Journals (Sweden)

    Kovačić Nataša

    2015-11-01

    Full Text Available The paper addresses the effect of external integration (EI with transport suppliers on the efficiency of travel agencies in the tourism sector supply chains. The main aim is the comparison of different estimation methods used in the structural equation modeling (SEM, applied to discover possible relationships between EIs and efficiencies. The latter are calculated by the means of data envelopment analysis (DEA. While designing the structural equation model, the exploratory and confirmatory factor analyses are also used as preliminary statistical procedures. For the estimation of parameters of SEM model, three different methods are explained, analyzed and compared: maximum likelihood (ML method, Bayesian Markov Chain Monte Carlo (BMCMC method, and unweighted least squares (ULS method. The study reveals that all estimation methods calculate comparable estimated parameters. The results also give an evidence of good model fit performance. Besides, the research confirms that the amplified external integration with transport providers leads to increased efficiency of travel agencies, which might be a very interesting finding for the operational management.

  12. Analysis of factors affecting satisfaction level on problem based learning approach using structural equation modeling

    Science.gov (United States)

    Hussain, Nur Farahin Mee; Zahid, Zalina

    2014-12-01

    Nowadays, in the job market demand, graduates are expected not only to have higher performance in academic but they must also be excellent in soft skill. Problem-Based Learning (PBL) has a number of distinct advantages as a learning method as it can deliver graduates that will be highly prized by industry. This study attempts to determine the satisfaction level of engineering students on the PBL Approach and to evaluate their determinant factors. The Structural Equation Modeling (SEM) was used to investigate how the factors of Good Teaching Scale, Clear Goals, Student Assessment and Levels of Workload affected the student satisfaction towards PBL approach.

  13. Statistical Power Analysis with Missing Data A Structural Equation Modeling Approach

    CERN Document Server

    Davey, Adam

    2009-01-01

    Statistical power analysis has revolutionized the ways in which we conduct and evaluate research.  Similar developments in the statistical analysis of incomplete (missing) data are gaining more widespread applications. This volume brings statistical power and incomplete data together under a common framework, in a way that is readily accessible to those with only an introductory familiarity with structural equation modeling.  It answers many practical questions such as: How missing data affects the statistical power in a study How much power is likely with different amounts and types

  14. Application of Structural Equation Modeling to Evaluate Service Quality of Sportswear Retailing

    Institute of Scientific and Technical Information of China (English)

    LI Min; GU Tong-yu; YANG Yi-xiong; HONG Tao-min

    2008-01-01

    Structural Equation Modeling (SEM) used widely in sociology, economics and psychology is adopted. Based on data obtained from marketing research, and using statistical analysis software SPSS11.0 and LISREL8.7, Theory of Five Dimensions of service quality is proved to be suitable in sportswear retailing in China. It analyzes the relationship among five dimensions and puts them in order of importance as to service quality in sportswear retailing. Advices are given for sportswear retail companies to improve their service quality and enhance customer loyalty.

  15. IQ heritability estimation: analyzing genetically-informative data with structural equation models.

    Science.gov (United States)

    Gallardo Pujol, David; García-Forero, Carlos; Kramp, Uwe; Maydeu-Olivares, Albert; Andrés-Pueyo, Antonio

    2007-02-01

    When analyzing genetic data, Structural Equations Modeling (SEM) provides a straightforward methodology to decompose phenotypic variance using a model-based approach. Furthermore, several models can be easily implemented, tested, and compared using SEM, allowing the researcher to obtain valuable information about the sources of variability. This methodology is briefly described and applied to re-analyze a Spanish set of IQ data using the biometric ACE model. In summary, we report heritability estimates that are consistent with those of previous studies and support substantial genetic contribution to phenotypic IQ; around 40% of the variance can be attributable to it. With regard to the environmental contribution, shared environment accounts for 50% of the variance, and non-shared environment accounts for the remaining 10%. These results are discussed in the text.

  16. Analysis of traffic accident size for Korean highway using structural equation models.

    Science.gov (United States)

    Lee, Ju-Yeon; Chung, Jin-Hyuk; Son, Bongsoo

    2008-11-01

    Accident size can be expressed as the number of involved vehicles, the number of damaged vehicles, the number of deaths and/or the number of injured. Accident size is the one of the important indices to measure the level of safety of transportation facilities. Factors such as road geometric condition, driver characteristic and vehicle type may be related to traffic accident size. However, all these factors interact in complicate ways so that the interrelationships among the variables are not easily identified. A structural equation model is adopted to capture the complex relationships among variables because the model can handle complex relationships among endogenous and exogenous variables simultaneously and furthermore it can include latent variables in the model. In this study, we use 2649 accident data occurred on highways in Korea and estimate relationship among exogenous factors and traffic accident size. The model suggests that road factors, driver factors and environment factors are strongly related to the accident size.

  17. The performance effect of the Lean package – a survey study using a structural equation model

    DEFF Research Database (Denmark)

    Kristensen, Thomas Borup; Israelsen, Poul

    practices. Furthermore, the paper provides evidence that supports the view that actions of middle management enhance performance in the system-wide approach to Lean. Originality/value - In contrast to previous surveys, our results support case studies describing the multiple interdependencies of Lean......Purpose - Our aim is to test and validate a system-wide approach using mediating relationships in a structural equation model in order to understand how the practices of Lean affect performance. Design/methodology/approach – A cross-sectional survey with 200 responding companies indicating...... that they use Lean. This is analyzed in a structural quation model setting. Findings - Previous quantitative research has shown mixed results for the performance of Lean because they have not addressed the system-wide mediating relations between Lean practices. We find that Companies using a system...

  18. The Eating Attitudes Test-26 revisited using exploratory structural equation modeling.

    Science.gov (United States)

    Maïano, Christophe; Morin, Alexandre J S; Lanfranchi, Marie-Christine; Therme, Pierre

    2013-07-01

    Most previous studies have failed to replicate the original factor structure of the 26-item version of the Eating Attitudes Test (EAT-26) among community samples of adolescents. The main objective of the present series of four studies (n = 2178) was to revisit the factor structure of this instrument among mixed gender community samples of adolescents using both exploratory structural equation modeling (ESEM) and confirmatory factor analysis (CFA). First, results from the ESEM analyses provided satisfactory goodness-of-fit statistics and reliability coefficients for a six-factor model of the EAT with 18 items (EAT-18) closely corresponding to the original seven-factor structure proposed for the 40-item version of the EAT. Second, these analyses were satisfactorily replicated among a new sample of community adolescents using CFA. The results confirmed the factor loading and intercept invariance of this model across gender and age groups (i.e., early and late adolescence), as well as the complete invariance of the EAT-18 measurement model between ethnicities (i.e., European versus African origins) and across weight categories (i.e., underweight, normal weight and overweight). Finally, the last study provided support for convergent validity of the EAT-18 with the Eating Disorder Inventory and with instruments measuring global self-esteem, physical appearance, social physique anxiety and fear of negative appearance evaluation.

  19. Inferring phenotypic causal structures among meat quality traits and the application of a structural equation model in Japanese Black cattle.

    Science.gov (United States)

    Inoue, K; Valente, B D; Shoji, N; Honda, T; Oyama, K; Rosa, G J M

    2016-10-01

    Meat quality is one of the most important traits determining carcass price in the Japanese beef market. Optimized breeding goals and management practices for the improvement of meat quality traits requires knowledge regarding any potential functional relationships between them. In this context, the objective of this research was to infer phenotypic causal networks involving beef marbling score (BMS), beef color score (BCL), firmness of beef (FIR), texture of beef (TEX), beef fat color score (BFS), and the ratio of MUFA to SFA (MUS) from 11,855 Japanese Black cattle. The inductive causation (IC) algorithm was implemented to search for causal links among these traits and was conditionally applied to their joint distribution on genetic effects. This information was obtained from the posterior distribution of the residual (co)variance matrix of a standard Bayesian multiple trait model (MTM). Apart from BFS, the IC algorithm implemented with 95% highest posterior density (HPD) intervals detected only undirected links among the traits. However, as a result of the application of 80% HPD intervals, more links were recovered and the undirected links were changed into directed ones, except between FIR and TEX. Therefore, 2 competing causal networks resulting from the IC algorithm, with either the arrow FIR → TEX or the arrow FIR ← TEX, were fitted using a structural equation model () to infer causal structure coefficients between the selected traits. Results indicated similar genetic and residual variances as well as genetic correlation estimates from both structural equation models. The genetic variances in BMS, FIR, and TEX from the structural equation models were smaller than those obtained from the MTM. In contrast, the variances in BCL, BFS, and MUS, which were not conditioned on any of the other traits in the causal structures, had no significant differences between the structural equation model and MTM. The structural coefficient for the path from MUS (BCL) to BMS

  20. The Impact of Cocreation on the Student Satisfaction: Analysis through Structural Equation Modeling

    Directory of Open Access Journals (Sweden)

    Odette Pantoja Díaz

    2016-01-01

    Full Text Available The objective of this study is to apply the cocreation initiative as a marketing tool in the context of university undergraduate programs. Considering that cocreation is a practice that involves stakeholders in different phases of product production or service, this research analyzes the interactions between some of the factors during the cocreation process as students collaborate with the university. These factors are participation, communication, cocreation, and satisfaction, and this study focuses on how they fuse together at the moment of cocreation. After a literature review, which supplied the basis for creating a model, we used exploratory and confirmatory factor analysis and structural equation modeling to validate the hypothesized relations between the variables; finally, the proposed cocreation model was verified. The results could empower academic institutions to develop managerial strategies in order to increase students’ collaboration and satisfaction.

  1. Structural equation modeling analysis of factors influencing architects' trust in project design teams

    Institute of Scientific and Technical Information of China (English)

    DING Zhi-kun; NG Fung-fai; WANG Jia-yuan

    2009-01-01

    This paper describes a structural equation modeling (SEM) analysis of factors influencing architects' trust in project design teams. We undertook a survey of architects, during which we distributed 193 questionnaires in 29 A-level architectural We used Amos 6.0 for SEM to identify significant personal construct based factors affecting interpersonal trust. The results show that only social interaction between architects significantly affects their interpersonal trust. The explained variance of trust is not very high in the model. Therefore, future research should add more factors into the current model. The practical implication is that team managers should promote the social interactions between team members such that the interpersonal trust level between team members can be improved.

  2. Understanding Nomophobia: Structural Equation Modeling and Semantic Network Analysis of Smartphone Separation Anxiety.

    Science.gov (United States)

    Han, Seunghee; Kim, Ki Joon; Kim, Jang Hyun

    2017-07-01

    This study explicates nomophobia by developing a research model that identifies several determinants of smartphone separation anxiety and by conducting semantic network analyses on smartphone users' verbal descriptions of the meaning of their smartphones. Structural equation modeling of the proposed model indicates that personal memories evoked by smartphones encourage users to extend their identity onto their devices. When users perceive smartphones as their extended selves, they are more likely to get attached to the devices, which, in turn, leads to nomophobia by heightening the phone proximity-seeking tendency. This finding is also supplemented by the results of the semantic network analyses revealing that the words related to memory, self, and proximity-seeking are indeed more frequently used in the high, compared with low, nomophobia group.

  3. Should researchers use single indicators, best indicators, or multiple indicators in structural equation models?

    Directory of Open Access Journals (Sweden)

    Hayduk Leslie A

    2012-10-01

    Full Text Available Abstract Background Structural equation modeling developed as a statistical melding of path analysis and factor analysis that obscured a fundamental tension between a factor preference for multiple indicators and path modeling’s openness to fewer indicators. Discussion Multiple indicators hamper theory by unnecessarily restricting the number of modeled latents. Using the few best indicators – possibly even the single best indicator of each latent – encourages development of theoretically sophisticated models. Additional latent variables permit stronger statistical control of potential confounders, and encourage detailed investigation of mediating causal mechanisms. Summary We recommend the use of the few best indicators. One or two indicators are often sufficient, but three indicators may occasionally be helpful. More than three indicators are rarely warranted because additional redundant indicators provide less research benefit than single indicators of additional latent variables. Scales created from multiple indicators can introduce additional problems, and are prone to being less desirable than either single or multiple indicators.

  4. Presenting of Indifference Management Model of Education System in Ardabil Province Using Structural Equation Modeling

    Science.gov (United States)

    Abolfazli, Elham; Saidabadi, Reza Yousefi; Fallah, Vahid

    2016-01-01

    The purpose of the present study is to investigate indifference management structural model in education system of Ardabil Province. The research method was integration study using Alli modeling. Statistical society of research was 420 assistant professors of educational science, managers, and deputies of Ardabil's second period of high schools…

  5. The perceived quality of in-vehicle auditory signals: a structural equation modelling approach.

    Science.gov (United States)

    Chi, Chia-Fen; Dewi, Ratna Sari; Surbakti, Yopie Yutama; Hsieh, Dong-Yu

    2017-11-01

    The current study applied Structural Equation Modelling to analyse the relationship among pitch, loudness, tempo and timbre and their relationship with perceived sound quality. Twenty-eight auditory signals of horn, indicator, door open warning and parking sensor were collected from 11 car brands. Twenty-one experienced drivers were recruited to evaluate all sound signals with 11 semantic differential scales. The results indicate that for the continuous sounds, pitch, loudness and timbre each had a direct impact on the perceived quality. Besides the direct impacts, pitch also had an impact on loudness perception. For the intermittent sounds, tempo and timbre each had a direct impact on the perceived quality. These results can help to identify the psychoacoustic attributes affecting the consumers' quality perception and help to design preferable sounds for vehicles. In the end, a design guideline is proposed for the development of auditory signals that adopts the current study's research findings as well as those of other relevant research. Practitioner Summary: This study applied Structural Equation Modelling to analyse the relationship among pitch, loudness, tempo and timbre and their relationship with perceived sound quality. The result can help to identify psychoacoustic attributes affecting the consumers' quality perception and help to design preferable sounds for vehicles.

  6. Factors influencing adherence to psychopharmacological medications in psychiatric patients: a structural equation modeling approach

    Science.gov (United States)

    De las Cuevas, Carlos; de Leon, Jose; Peñate, Wenceslao; Betancort, Moisés

    2017-01-01

    Purpose To evaluate pathways through which sociodemographic, clinical, attitudinal, and perceived health control variables impact psychiatric patients’ adherence to psychopharmacological medications. Method A sample of 966 consecutive psychiatric outpatients was studied. The variables were sociodemographic (age, gender, and education), clinical (diagnoses, drug treatment, and treatment duration), attitudinal (attitudes toward psychopharmacological medication and preferences regarding participation in decision-making), perception of control over health (health locus of control, self-efficacy, and psychological reactance), and level of adherence to psychopharmacological medications. Structural equation modeling was applied to examine the nonstraightforward relationships and the interactive effects among the analyzed variables. Results Structural equation modeling demonstrated that psychiatric patients’ treatment adherence was associated: 1) negatively with cognitive psychological reactance (adherence decreased as cognitive psychological reactance increased), 2) positively with patients’ trust in their psychiatrists (doctors’ subscale), 3) negatively with patients’ belief that they are in control of their mental health and that their mental health depends on their own actions (internal subscale), and 4) positively (although weakly) with age. Self-efficacy indirectly influenced treatment adherence through internal health locus of control. Conclusion This study provides support for the hypothesis that perceived health control variables play a relevant role in psychiatric patients’ adherence to psychopharmacological medications. The findings highlight the importance of considering prospective studies of patients’ psychological reactance and health locus of control as they may be clinically relevant factors contributing to adherence to psychopharmacological medications.

  7. 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

  8. Structure analysis of solution to equations of quasi 3-D accretion disk model

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    In this paper we discuss the problems contained in the solution to the equations of quasi 3-D accretion disk model, and point out that the angular momentum equation should not be integrated directly. Finally, we develop a criterion of the existence of a disconnected solution to this model.

  9. The developmental antecedents of sexual coercion against women: testing alternative hypotheses with structural equation modeling.

    Science.gov (United States)

    Knight, Raymond A; Sims-Knight, Judith E

    2003-06-01

    A unified model of the origin of sexual aggression against women on both adult and juvenile sexual offender samples has been developed and successfully tested. This model proposed three major causal paths to sexual coercion against women. In the first path, physical and verbal abuse was hypothesized to produce callousness and lack of emotionality, which disinhibited sexual drive and sexual fantasies. These in turn disinhibited hostile sexual fantasies, and led to sexual coercion. In the second causal path, sexual abuse contributed directly to the disinhibition of sexual drive and sexual fantasies, which through hostile sexual fantasies led to sexual coercion. The third path operated through early antisocial behavior, including aggressive acts. It developed as a result of both physical/verbal abuse and callousness/lack of emotion. It in turn directly affected sexual coercion and worked indirectly through the hostile sexual fantasies path. In the present study, the anonymous responses of a group of 168 blue-collar, community males to an inventory (the Multidimensional Assessment of Sex and Aggression) were used in a structural equation model to test the validity of this model. Moreover, this model was pitted against (Malamuth's (1998)) two-path model. Whereas the three-path model had an excellent fit with the data (CFI =.951, RMSEA =.047), the two-path model fit less well (CFI =.857, RMSEA =.079). These results indicate the superiority of the three-path model and suggest that it constitutes a solid, empirically disconfirmable heuristic for the etiology of sexual coercion against women.

  10. Family Environment and Childhood Obesity: A New Framework with Structural Equation Modeling

    Directory of Open Access Journals (Sweden)

    Hui Huang

    2017-02-01

    Full Text Available The main purpose of the current article is to introduce a framework of the complexity of childhood obesity based on the family environment. A conceptual model that quantifies the relationships and interactions among parental socioeconomic status, family food security level, child’s food intake and certain aspects of parental feeding behaviour is presented using the structural equation modeling (SEM concept. Structural models are analysed in terms of the direct and indirect connections among latent and measurement variables that lead to the child weight indicator. To illustrate the accuracy, fit, reliability and validity of the introduced framework, real data collected from 630 families from Urumqi (Xinjiang, China were considered. The framework includes two categories of data comprising the normal body mass index (BMI range and obesity data. The comparison analysis between two models provides some evidence that in obesity modeling, obesity data must be extracted from the dataset and analysis must be done separately from the normal BMI range. This study may be helpful for researchers interested in childhood obesity modeling based on family environment.

  11. Family Environment and Childhood Obesity: A New Framework with Structural Equation Modeling.

    Science.gov (United States)

    Huang, Hui; Wan Mohamed Radzi, Che Wan Jasimah Bt; Salarzadeh Jenatabadi, Hashem

    2017-02-13

    The main purpose of the current article is to introduce a framework of the complexity of childhood obesity based on the family environment. A conceptual model that quantifies the relationships and interactions among parental socioeconomic status, family food security level, child's food intake and certain aspects of parental feeding behaviour is presented using the structural equation modeling (SEM) concept. Structural models are analysed in terms of the direct and indirect connections among latent and measurement variables that lead to the child weight indicator. To illustrate the accuracy, fit, reliability and validity of the introduced framework, real data collected from 630 families from Urumqi (Xinjiang, China) were considered. The framework includes two categories of data comprising the normal body mass index (BMI) range and obesity data. The comparison analysis between two models provides some evidence that in obesity modeling, obesity data must be extracted from the dataset and analysis must be done separately from the normal BMI range. This study may be helpful for researchers interested in childhood obesity modeling based on family environment.

  12. Using Structural Equation Modeling and the Behavioral Sciences Theories in Predicting Helmet Use

    Directory of Open Access Journals (Sweden)

    Kamarudin Ambak

    2011-01-01

    Full Text Available In Malaysia, according to road accidents data statistics motorcycle users contributes more than 50% of fatalities in traffic accidents, and the major cause due to head injuries. One strategy that can be used to reduce the severity of head injuries is by proper usage of helmet. Although the safety helmet is the best protective equipment to prevents head injury, majority motorcycle user did not use or did not fasten properly. In understanding this problem, the behavioral sciences theory and engineering aspect are needed to provide better explanation and comprehensive insights into solutions. The Theory Planned Behavior (TPB and Health Belief Model (HBM were used in predicting the behavioral intention toward proper helmet usage among motorcyclist. While, a new intervention approach were used in Technology Acceptance Model (TAM that based on the perception of a conceptual system called Safety Helmet Reminder System (SHR. Results show that the constructs variables are reliable and statistically significant with the exogenous and endogenous variables. The full structured models were proposed and tested, thus the significant predictors were identified. A multivariate analysis technique, known as Structural Equation Model (SEM was used in modeling exercise.  Finally, the good-of-fit models were used in interpreting the implication of intervention strategy toward motorcyclist injury prevention program.

  13. Analysis on influencing factors of clinical teachers’ job satisfaction by structural equation model

    Directory of Open Access Journals (Sweden)

    Haiyi Jia

    2017-02-01

    Full Text Available [Research objective] Analyze the influencing factors of clinical teachers’ job satisfaction. [Research method] The ERG theory was used as the framework to design the questionnaires. Data were analyzed by structural equation model for investigating the influencing factors. [Research result] The modified model shows that factors of existence needs and growth needs have direct influence on the job satisfaction of clinical teachers, the influence coefficients are 0.540 and 0.380. The three influencing factors have positive effects on each other, and the correlation coefficients are 0.620, 0.400 and 0.330 respectively. [Research conclusion] Relevant departments should take active measures to improve job satisfaction of clinical teachers from two aspects: existence needs and growth needs, and to improve their work enthusiasm and teaching quality.

  14. Implementing a Simulation Study Using Multiple Software Packages for Structural Equation Modeling

    Directory of Open Access Journals (Sweden)

    Sunbok Lee

    2015-07-01

    Full Text Available A Monte Carlo simulation study is an essential tool for evaluating the behavior of various quantitative methods including structural equation modeling (SEM under various conditions. Typically, a large number of replications are recommended for a Monte Carlo simulation study, and therefore automating a Monte Carlo simulation study is important to get the desired number of replications for a simulation study. This article is intended to provide concrete examples for automating a Monte Carlo simulation study using some standard software packages for SEM: Mplus, LISREL, SAS PROC CALIS, and R package lavaan. Also, the equivalence between the multilevel SEM and hierarchical linear modeling (HLM is discussed, and relevant examples are provided. It is hoped that the codes in this article can provide some building blocks for researchers to write their own code to automate simulation procedures.

  15. Examining the antecedents of Facebook acceptance via structural equation modeling: A case of CEGEP students

    Directory of Open Access Journals (Sweden)

    Tenzin Doleck

    2017-03-01

    Full Text Available Although the last decade has witnessed social networking sites of varied flavors, Facebook’s user growth continues to balloon, and relatedly, Facebook remains popular among the college populace. While there has been a growing body of work on ascertaining antecedents of Facebook use among college students, Collège d'enseignement général et professionnel (CEGEP students’ acceptance of Facebook remains underexplored. The purpose of this study was to analyze CEGEP students’ acceptance of Facebook using the technology acceptance model (TAM. Structural equation modeling was conducted on data from a survey of 214 CEGEP students. We find that Facebook use is motivated by the core TAM constructs as well as the added factors of peer influence, perceived enjoyment, perceived self-efficacy, relative advantage, risk, and trust.

  16. A Structural Equation Modelling of the Academic Self-Concept Scale

    Directory of Open Access Journals (Sweden)

    Musa MATOVU

    2014-03-01

    Full Text Available The study aimed at validating the academic self-concept scale by Liu and Wang (2005 in measuring academic self-concept among university students. Structural equation modelling was used to validate the scale which was composed of two subscales; academic confidence and academic effort. The study was conducted on university students; males and females from different levels of study and faculties. In this study the influence of academic self-concept on academic achievement was assessed, tested whether the hypothesised model fitted the data, analysed the invariance of the path coefficients among the moderating variables, and also, highlighted whether academic confidence and academic effort measured academic self-concept. The results from the model revealed that academic self-concept influenced academic achievement and the hypothesised model fitted the data. The results also supported the model as the causal structure was not sensitive to gender, levels of study, and faculties of students; hence, applicable to all the groups taken as moderating variables. It was also noted that academic confidence and academic effort are a measure of academic self-concept. According to the results the academic self-concept scale by Liu and Wang (2005 was deemed adequate in collecting information about academic self-concept among university students.

  17. E-business Adoption amongst SMEs: A Structural Equation Modeling Approach

    Directory of Open Access Journals (Sweden)

    Azyanee Luqman

    2011-08-01

    Full Text Available The adoption of e-business amongst small and medium sized enterprises in the state of Terengganu, Malaysia is still quite low. Hence, identifying the success factors that contribute to e-business adoption is crucial. This article examines the factors that determine the e-business adoption amongst small and medium enterprises and its causal effects using a theoretical model based on the Innovation Diffusion Theory. The research model consists of five exogenous latent constructs, namely relative advantage, compatibility, complexity, trialability and observability. Data relating to the constructs were collected from 337 small and medium sized enterprises located in the state of Terengganu, Malaysia and subjected to Structural Equation Modeling analysis. Confirmatory Factor Analysis (CFA was performed to examine the reliability, construct validity, convergent validity and goodness of fit of individual construct and measurement models. The hypothesized structural model fits the data well. Results indicate that the significant factor that leads to the adoption of e-business is compatibility. Finally, implications and suggestions of these findings are discussed.

  18. Structural Equation Modelling in Behavioral Intention to Use Safety Helmet Reminder System

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    Rosli Naida

    2016-01-01

    Full Text Available Motorcycle is one of private transportation which has been widely used in many countries including Malaysia. However, motorcycles are the most dangerous form of motorized transport. Royal Malaysian Police (PDRM statistics recorded that motorcycle is the highest vehicle (45.9% involved in traffic accident compared to other vehicles. The potential cause of the death to the motorcyclist was due to the head injury. One of strategy to mitigate this problem is through proper usage of safety helmet. Therefore, this paper was introduce a new approach on motorcyclist safety by using the Technology Acceptance Model (TAM with additional determinants that contribute to behavioral intention and to increase the proper usage of safety helmets among Malaysian motorcyclists. The Structural Equation Modelling (SEM was used to test the structural TAM proposed. The evaluation for structural model showed the goodness of fit indices are excellent fit. This study found that perceived ease of use, perceived usefulness and social norm are significant towards behavioral intention to use Safety Helmet Reminder System (SHR.

  19. Structural equation modeling identifies markers of damage and function in the aging male Fischer 344 rat.

    Science.gov (United States)

    Grunz-Borgmann, Elizabeth A; Nichols, LaNita A; Wiedmeyer, Charles E; Spagnoli, Sean; Trzeciakowski, Jerome P; Parrish, Alan R

    2016-06-01

    The male Fischer 344 rat is an established model to study progressive renal dysfunction that is similar, but not identical, to chronic kidney disease (CKD) in humans. These studies were designed to assess age-dependent alterations in renal structure and function at late-life timepoints, 16-24 months. Elevations in BUN and plasma creatinine were not significant until 24 months, however, elevations in the more sensitive markers of function, plasma cystatin C and proteinuria, were detectable at 16 and 18 months, respectively. Interestingly, cystatin C levels were not corrected by caloric restriction. Urinary Kim-1, a marker of CKD, was elevated as early as 16 months. Klotho gene expression was significantly decreased at 24 months, but not at earlier timepoints. Alterations in renal structure, glomerulosclerosis and tubulointerstitial fibrosis, were noted at 16 months, with little change from 18 to 24 months. Tubulointerstitial inflammation was increased at 16 months, and remained similar from 18 to 24 months. A SEM (structural equation modeling) model of age-related renal dysfunction suggests that proteinuria is a marker of renal damage, while urinary Kim-1 is a marker of both damage and function. Taken together, these results demonstrate that age-dependent nephropathy begins as early as 16 months and progresses rapidly over the next 8 months.

  20. Doubly-Latent Models of School Contextual Effects: Integrating Multilevel and Structural Equation Approaches to Control Measurement and Sampling Error

    Science.gov (United States)

    Marsh, Herbert W.; Ludtke, Oliver; Robitzsch, Alexander; Trautwein, Ulrich; Asparouhov, Tihomir; Muthen, Bengt; Nagengast, Benjamin

    2009-01-01

    This article is a methodological-substantive synergy. Methodologically, we demonstrate latent-variable contextual models that integrate structural equation models (with multiple indicators) and multilevel models. These models simultaneously control for and unconfound measurement error due to sampling of items at the individual (L1) and group (L2)…

  1. Race/Ethnicity and Social Capital among Middle- and Upper-Middle-Class Elementary School Families: A Structural Equation Model

    Science.gov (United States)

    Caldas, Stephen J.; Cornigans, Linda

    2015-01-01

    This study used structural equation modeling to conduct a first and second order confirmatory factor analysis (CFA) of a scale developed by McDonald and Moberg (2002) to measure three dimensions of social capital among a diverse group of middle- and upper-middle-class elementary school parents in suburban New York. A structural path model was…

  2. Railway noise annoyance: exposure-response relationships and testing a theoretical model by structural equation analysis.

    Science.gov (United States)

    Pennig, Sibylle; Schady, Arthur

    2014-01-01

    In some regions the exposure to railway noise is extremely concentrated, which may lead to high residential annoyance. Nonacoustical factors contribute to these reactions, but there is limited evidence on the interrelations between the nonacoustical factors that influence railway noise annoyance. The aims of the present study were (1) to examine exposure-response relationships between long-term railway noise exposure and annoyance in a region severely affected by railway noise and (2) to determine a priori proposed interrelations between nonacoustical factors by structural equation analysis. Residents (n = 320) living close to railway tracks in the Middle Rhine Valley completed a socio-acoustic survey. Individual noise exposure levels were calculated by an acoustical simulation model for this area. The derived exposure-response relationships indicated considerably higher annoyance at the same noise exposure level than would have been predicted by the European Union standard curve, particularly for the night-time period. In the structural equation analysis, 72% of the variance in noise annoyance was explained by the noise exposure (L(den)) and nonacoustical variables. The model provides insights into several causal mechanisms underlying the formation of railway noise annoyance considering indirect and reciprocal effects. The concern about harmful effects of railway noise and railway traffic, the perceived control and coping capacity, and the individual noise sensitivity were the most important factors that influence noise annoyance. All effects of the nonacoustical factors on annoyance were mediated by the perceived control and coping capacity and additionally proposed indirect effects of the theoretical model were supported by the data.

  3. Railway noise annoyance: Exposure-response relationships and testing a theoretical model by structural equation analysis

    Directory of Open Access Journals (Sweden)

    Sibylle Pennig

    2014-01-01

    Full Text Available In some regions the exposure to railway noise is extremely concentrated, which may lead to high residential annoyance. Nonacoustical factors contribute to these reactions, but there is limited evidence on the interrelations between the nonacoustical factors that influence railway noise annoyance. The aims of the present study were (1 to examine exposure-response relationships between long-term railway noise exposure and annoyance in a region severely affected by railway noise and (2 to determine a priori proposed interrelations between nonacoustical factors by structural equation analysis. Residents (n = 320 living close to railway tracks in the Middle Rhine Valley completed a socio-acoustic survey. Individual noise exposure levels were calculated by an acoustical simulation model for this area. The derived exposure-response relationships indicated considerably higher annoyance at the same noise exposure level than would have been predicted by the European Union standard curve, particularly for the night-time period. In the structural equation analysis, 72% of the variance in noise annoyance was explained by the noise exposure (Lden and nonacoustical variables. The model provides insights into several causal mechanisms underlying the formation of railway noise annoyance considering indirect and reciprocal effects. The concern about harmful effects of railway noise and railway traffic, the perceived control and coping capacity, and the individual noise sensitivity were the most important factors that influence noise annoyance. All effects of the nonacoustical factors on annoyance were mediated by the perceived control and coping capacity and additionally proposed indirect effects of the theoretical model were supported by the data.

  4. Structural equation modeling with latent variables for longitudinal blood pressure traits using general pedigrees.

    Science.gov (United States)

    Song, Yeunjoo E; Morris, Nathan J; Stein, Catherine M

    2016-01-01

    Structural equation modeling (SEM) has been used in a wide range of applied sciences including genetic analysis. The recently developed R package, strum, implements a framework for SEM for general pedigree data. We explored different SEM techniques using strum to analyze the multivariate longitudinal data and to ultimately test the association of genotypes on blood pressure traits. The quantitative blood pressure (BP) traits, systolic BP (SBP) and diastolic BP (DBP) were analyzed as the main traits of interest with age, sex, and smoking status as covariates. The single nucleotide polymorphism (SNP) genotype information from genome-wide association studies (GWAS) data was used for the test of association. The adjustment for hypertension treatment effect was done by the censored regression approach. Two different longitudinal data models, autoregressive model and latent growth curve model, were used to fit the longitudinal BP traits. The test of association for SNP was done using a novel score test within the SEM framework of strum. We found the 10 SNPs within the GWAS suggestive P value level, and among those 10, the most significant top 3 SNPs agreed in rank in both analysis models. The general SEM framework in strum is very useful to model and test for the association with massive genotype data and complex systems of multiple phenotypes with general pedigree data.

  5. Factors affecting pharmacy engagement and pharmacy customer devotion in community pharmacy: A structural equation modeling approach.

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    Nitadpakorn, Sujin; Farris, Karen B; Kittisopee, Tanattha

    2017-01-01

    The concept of customer engagement and devotion has been applied in various service businesses to keep the customers with business However, a limited number of studies were performed to examine the context of customer engagement and devotion in pharmacy business which focus on the impact of customer perceptions about pharmacists, perceived quality of pharmacy structure, medication price strategy on pharmacy engagement and pharmacy customer devotion in a pharmacy providing pharmaceutical care to the customers. This study aimed to assess a conceptual model depicting the relationships among customer perceptions about pharmacists, pharmacy quality structure, medication price, customer engagement, and customer devotion. And also aimed to assess and measure if there is a direct or indirect relationship between these factors. A quantitative study was conducted by using self-administered questionnaires. Two hundred and fifty three customers who regularly visited the pharmacy were randomly recruited from a purposively selected 30 community pharmacies in Bangkok. The survey was completed during February to April 2016. A structural equation model (SEM) was used to assess the direct and indirect relationships between constructs. A total of 253/300 questionnaires were returned for analysis, and the response rate was 84%. Only perceptions about pharmacist in customers receiving professional pharmacy services was statically significant regarding relationship with pharmacy engagement (beta=0.45). Concurrently, the model from empirical data fit with the hypothetical model (p-value = 0.06, adjusted chi-square (CMIN/DF)=1.16, Goodness of Fit Index (GFI)=0.93, Comparatively Fit Index (CFI)=0.99, and Root Mean Square Error Approximation (RMSEA)=0.03). The study confirmed the indirect positive influence of customer perceptions about pharmacist on pharmacy customer devotion in providing pharmacy services via pharmacy engagement It was customer perceptions about pharmacist that influenced

  6. Atomistic modeling of structure II gas hydrate mechanics: Compressibility and equations of state

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    Thomas M. Vlasic

    2016-08-01

    Full Text Available This work uses density functional theory (DFT to investigate the poorly characterized structure II gas hydrates, for various guests (empty, propane, butane, ethane-methane, propane-methane, at the atomistic scale to determine key structure and mechanical properties such as equilibrium lattice volume and bulk modulus. Several equations of state (EOS for solids (Murnaghan, Birch-Murnaghan, Vinet, Liu were fitted to energy-volume curves resulting from structure optimization simulations. These EOS, which can be used to characterize the compressional behaviour of gas hydrates, were evaluated in terms of their robustness. The three-parameter Vinet EOS was found to perform just as well if not better than the four-parameter Liu EOS, over the pressure range in this study. As expected, the Murnaghan EOS proved to be the least robust. Furthermore, the equilibrium lattice volumes were found to increase with guest size, with double-guest hydrates showing a larger increase than single-guest hydrates, which has significant implications for the widely used van der Waals and Platteeuw thermodynamic model for gas hydrates. Also, hydrogen bonds prove to be the most likely factor contributing to the resistance of gas hydrates to compression; bulk modulus was found to increase linearly with hydrogen bond density, resulting in a relationship that could be used predictively to determine the bulk modulus of various structure II gas hydrates. Taken together, these results fill a long existing gap in the material chemical physics of these important clathrates.

  7. Atomistic modeling of structure II gas hydrate mechanics: Compressibility and equations of state

    Science.gov (United States)

    Vlasic, Thomas M.; Servio, Phillip; Rey, Alejandro D.

    2016-08-01

    This work uses density functional theory (DFT) to investigate the poorly characterized structure II gas hydrates, for various guests (empty, propane, butane, ethane-methane, propane-methane), at the atomistic scale to determine key structure and mechanical properties such as equilibrium lattice volume and bulk modulus. Several equations of state (EOS) for solids (Murnaghan, Birch-Murnaghan, Vinet, Liu) were fitted to energy-volume curves resulting from structure optimization simulations. These EOS, which can be used to characterize the compressional behaviour of gas hydrates, were evaluated in terms of their robustness. The three-parameter Vinet EOS was found to perform just as well if not better than the four-parameter Liu EOS, over the pressure range in this study. As expected, the Murnaghan EOS proved to be the least robust. Furthermore, the equilibrium lattice volumes were found to increase with guest size, with double-guest hydrates showing a larger increase than single-guest hydrates, which has significant implications for the widely used van der Waals and Platteeuw thermodynamic model for gas hydrates. Also, hydrogen bonds prove to be the most likely factor contributing to the resistance of gas hydrates to compression; bulk modulus was found to increase linearly with hydrogen bond density, resulting in a relationship that could be used predictively to determine the bulk modulus of various structure II gas hydrates. Taken together, these results fill a long existing gap in the material chemical physics of these important clathrates.

  8. A structural equation model of the effect of poverty and unemployment on alcohol abuse.

    Science.gov (United States)

    Khan, Shaila; Murray, Robert P; Barnes, Gordon E

    2002-01-01

    The short- and long-term effects of poverty and unemployment on alcohol abuse are investigated using structural equation modelling (SEM) to better understand the observed conflicting relationships among them. We studied 795 community residents who provided complete data in both 1989 and 1991 in the Winnipeg Health and Drinking Survey (WHDS), with equal representation of males and females. Results indicate that (a) increased poverty causes increased alcohol use and alcohol problems, and (b) recent unemployment decreases alcohol use while longer unemployment increases it. It is concluded that the effect of unemployment on alcohol abuse changes direction with time and, thus, both cross-sectional and longitudinal data are required to assess any meaningful relationship between them.

  9. A Structural Equation Modeling of EFL Learners' Goal Orientation, Metacognitive Awareness, and Self-efficacy

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    Atefeh Zafarmand

    2014-12-01

    Full Text Available This article sets out to examine the relationship between EFL learners' goal orientation, metacognitive awareness and self-efficacy in a single framework. One hundred fifteen EFL students from two universities of Mashhad, a city in north-eastern Iran took part in this study. Structural equation modeling (SEM was utilized to examine the hypothesized relations. The results of SEM demonstrated that among goal orientations, mastery goal is a positive and significant predictor of metacognitive awareness. It also positively and significantly predicts self-efficacy. Furthermore, it was found that metacognitive awareness has a positive and significant role in self-efficacy. The results of correlation between subscales of metacognitive awareness and mastery goal indicated that the highest correlations were found between mastery goal, planning and monitoring. Identical analysis for performance goal revealed that there are significant but weak correlations between performance goal and declarative and procedural knowledge.

  10. Handling Missing Data With Multilevel Structural Equation Modeling and Full Information Maximum Likelihood Techniques.

    Science.gov (United States)

    Schminkey, Donna L; von Oertzen, Timo; Bullock, Linda

    2016-08-01

    With increasing access to population-based data and electronic health records for secondary analysis, missing data are common. In the social and behavioral sciences, missing data frequently are handled with multiple imputation methods or full information maximum likelihood (FIML) techniques, but healthcare researchers have not embraced these methodologies to the same extent and more often use either traditional imputation techniques or complete case analysis, which can compromise power and introduce unintended bias. This article is a review of options for handling missing data, concluding with a case study demonstrating the utility of multilevel structural equation modeling using full information maximum likelihood (MSEM with FIML) to handle large amounts of missing data. MSEM with FIML is a parsimonious and hypothesis-driven strategy to cope with large amounts of missing data without compromising power or introducing bias. This technique is relevant for nurse researchers faced with ever-increasing amounts of electronic data and decreasing research budgets. © 2016 Wiley Periodicals, Inc.

  11. Reporting Results from Structural Equation Modeling Analyses in Archives of Scientific Psychology.

    Science.gov (United States)

    Hoyle, Rick H; Isherwood, Jennifer C

    2013-02-01

    Psychological research typically involves the analysis of data (e.g., questionnaire responses, records of behavior) using statistical methods. The description of how those methods are used and the results they produce is a key component of scholarly publications. Despite their importance, these descriptions are not always complete and clear. In order to ensure the completeness and clarity of these descriptions, the Archives of Scientific Psychology requires that authors of manuscripts to be considered for publication adhere to a set of publication standards. Although the current standards cover most of the statistical methods commonly used in psychological research, they do not cover them all. In this manuscript, we propose adjustments to the current standards and the addition of additional standards for a statistical method not adequately covered in the current standards-structural equation modeling (SEM). Adherence to the standards we propose would ensure that scholarly publications that report results of data analyzed using SEM are complete and clear.

  12. From patterns to causal understanding: Structural equation modeling (SEM) in soil ecology

    Science.gov (United States)

    Eisenhauer, Nico; Powell, Jeff R; Grace, James B.; Bowker, Matthew A.

    2015-01-01

    In this perspectives paper we highlight a heretofore underused statistical method in soil ecological research, structural equation modeling (SEM). SEM is commonly used in the general ecological literature to develop causal understanding from observational data, but has been more slowly adopted by soil ecologists. We provide some basic information on the many advantages and possibilities associated with using SEM and provide some examples of how SEM can be used by soil ecologists to shift focus from describing patterns to developing causal understanding and inspiring new types of experimental tests. SEM is a promising tool to aid the growth of soil ecology as a discipline, particularly by supporting research that is increasingly hypothesis-driven and interdisciplinary, thus shining light into the black box of interactions belowground.

  13. Students attitude towards calculus subject: A case-study using structural equation modeling

    Science.gov (United States)

    Awang, Noorehan; Hamid, Nur Nadiah Abd.

    2015-10-01

    This study was designed to assess the attitude of Bumiputera students towards mathematics. The instrument used to measure the attitude was Test of Mathematics Related Attitude (TOMRA). This test measures students' attitudes in four criteria: normality of mathematics (N), attitudes towards mathematics inquiry (I), adoption of mathematics attitude (A) and enjoyment of mathematics lessons (E). The target population of this study was all computer science and quantitative science students who enrolled in a Calculus subject at UiTM Negeri Sembilan. Confirmatory Factor Analysis was carried out and the inter-relationship among the four criteria was analyzed using Structural Equation Modeling. The students scored high in E, moderately in A and relatively low in N and I.

  14. The relationship between market orientation and performance in the hospital industry: a structural equations modeling approach.

    Science.gov (United States)

    Raju, P S; Lonial, S C; Gupta, Y P; Ziegler, C

    2000-06-01

    There is general consensus in the research literature that market orientation is related to organizational performance. This study examines this relationship in the hospital industry. One unique feature of this study is that both market orientation and performance are conceptualized as being multi-dimensional constructs. Hence the technique of Structural Equations Modeling (SEM) is used to examine the relationship. Analyses were based on market orientation and performance data obtained from 175 hospitals in a five-state region of the United States. The SEM results confirm the multi-dimensional nature of both market orientation and performance, and the strong relationship between the constructs. Interestingly, this relationship is found to be much stronger for smaller hospitals than for larger hospitals. Implications for the hospital industry are discussed.

  15. Analyzing Sport Consumer Behaviour toward Sportswear Store: A Structural Equation Modelling Approach

    Directory of Open Access Journals (Sweden)

    Hafedh Ibrahim

    2014-03-01

    Full Text Available The aim of this study is to elucidate in sportswear store setting the relationships among psychological traits, loyalty to salesperson and behavioural intentions in three different sport consumers according to their switching behaviour. By means of structural equation modelling, we find a clear difference in the behaviour of the three groups. The results show that loyalty to salesperson is more influenced by need for social affiliation for the stayer customers. Whereas, for the dissatisfied and the satisfied switchers, need for variety makes the greatest contribution in explaining customer loyalty toward salespersons. These findings imply that sportswear stores must concentrate on employing enthusiastic, sociable salespersons who genuinely like being with people; and salesperson should be trained to solve patron problems and become personally concerned with the customer.

  16. Violence, stigma and mental health among female sex workers in China: A structural equation modeling.

    Science.gov (United States)

    Zhang, Liying; Li, Xiaoming; Wang, Bo; Shen, Zhiyong; Zhou, Yuejiao; Xu, Jinping; Tang, Zhenzhu; Stanton, Bonita

    2016-05-26

    Intimate partner violence is prevalent among female sex workers (FSWs) in China, and it is significantly associated with mental health problems among FSWs. However, limited studies have explored the mechanisms/process by which violence affects mental health. The purpose of this study was to explore the relationships among partner violence, internalized stigma, and mental health problems among FSWs. Data were collected using a self-administered cross-sectional survey administered to 1,022 FSWs in the Guangxi Zhuang Autonomous Region (Guangxi), China during 2008-2009. We used structural equation modeling to test the hypothesized relationships. Results indicated that violence perpetrated by either stable sexual partners or clients was directly and positively associated with mental health problems. Violence also had an indirect relation to mental health problems through stigma. Results highlight the need for interventions on counseling and care for FSWs who have experienced violence and for interventions to increase FSWs' coping skills and empowerment strategies.

  17. EXPLORING FACTORS INFLUENCING FINANCIAL PLANNING AFTER RETIREMENT: STRUCTURAL EQUATION MODELING APPROACH

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    Md. Abdul Jalil

    2013-01-01

    Full Text Available The study explores the critical factors that influence financial planning after retirement among Malaysians, an area which has somewhat been largely overlooked by the extant literature. The study has used a quantitative method to survey a sample of 170 Malaysian citizens, from various places in the Klang Valley area. Exploratory factor analysis, confirmatory factor analysis and structural equation modeling were used to analyze the data. The results suggest that the paths are interrelated to the casual processes significantly. Furthermore, individual’s income or monthly salary is found to be the most important factor influencing financial planning, followed by attitude and culture. The results are mainly favourable to academics and practitioners in Malaysia by contributing an understanding into critical factors that influence people to make financial plan before their retirement. The study provides implications of the findings in the concluding section.

  18. Applications of Generalizability Theory and Their Relations to Classical Test Theory and Structural Equation Modeling.

    Science.gov (United States)

    Vispoel, Walter P; Morris, Carrie A; Kilinc, Murat

    2017-01-23

    Although widely recognized as a comprehensive framework for representing score reliability, generalizability theory (G-theory), despite its potential benefits, has been used sparingly in reporting of results for measures of individual differences. In this article, we highlight many valuable ways that G-theory can be used to quantify, evaluate, and improve psychometric properties of scores. Our illustrations encompass assessment of overall reliability, percentages of score variation accounted for by individual sources of measurement error, dependability of cut-scores for decision making, estimation of reliability and dependability for changes made to measurement procedures, disattenuation of validity coefficients for measurement error, and linkages of G-theory with classical test theory and structural equation modeling. We also identify computer packages for performing G-theory analyses, most of which can be obtained free of charge, and describe how they compare with regard to data input requirements, ease of use, complexity of designs supported, and output produced. (PsycINFO Database Record

  19. Unified structural equation modeling approach for the analysis of multisubject, multivariate functional MRI data.

    Science.gov (United States)

    Kim, Jieun; Zhu, Wei; Chang, Linda; Bentler, Peter M; Ernst, Thomas

    2007-02-01

    The ultimate goal of brain connectivity studies is to propose, test, modify, and compare certain directional brain pathways. Path analysis or structural equation modeling (SEM) is an ideal statistical method for such studies. In this work, we propose a two-stage unified SEM plus GLM (General Linear Model) approach for the analysis of multisubject, multivariate functional magnetic resonance imaging (fMRI) time series data with subject-level covariates. In Stage 1, we analyze the fMRI multivariate time series for each subject individually via a unified SEM model by combining longitudinal pathways represented by a multivariate autoregressive (MAR) model, and contemporaneous pathways represented by a conventional SEM. In Stage 2, the resulting subject-level path coefficients are merged with subject-level covariates such as gender, age, IQ, etc., to examine the impact of these covariates on effective connectivity via a GLM. Our approach is exemplified via the analysis of an fMRI visual attention experiment. Furthermore, the significant path network from the unified SEM analysis is compared to that from a conventional SEM analysis without incorporating the longitudinal information as well as that from a Dynamic Causal Modeling (DCM) approach.

  20. Stress and resilience in functional somatic syndromes--a structural equation modeling approach.

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    Susanne Fischer

    Full Text Available BACKGROUND: Stress has been suggested to play a role in the development and perpetuation of functional somatic syndromes. The mechanisms of how this might occur are not clear. PURPOSE: We propose a multi-dimensional stress model which posits that childhood trauma increases adult stress reactivity (i.e., an individual's tendency to respond strongly to stressors and reduces resilience (e.g., the belief in one's competence. This in turn facilitates the manifestation of functional somatic syndromes via chronic stress. We tested this model cross-sectionally and prospectively. METHODS: Young adults participated in a web survey at two time points. Structural equation modeling was used to test our model. The final sample consisted of 3'054 participants, and 429 of these participated in the follow-up survey. RESULTS: Our proposed model fit the data in the cross-sectional (χ2(21  = 48.808, p<.001, CFI  = .995, TLI  = .992, RMSEA  = .021, 90% CI [.013.029] and prospective analyses (χ2(21  =  32.675, p<.05, CFI  = .982, TLI  = .969, RMSEA  = .036, 90% CI [.001.059]. DISCUSSION: Our findings have several clinical implications, suggesting a role for stress management training in the prevention and treatment of functional somatic syndromes.

  1. Assessing the Fit of Structural Equation Models With Multiply Imputed Data.

    Science.gov (United States)

    Enders, Craig K; Mansolf, Maxwell

    2016-11-28

    Multiple imputation has enjoyed widespread use in social science applications, yet the application of imputation-based inference to structural equation modeling has received virtually no attention in the literature. Thus, this study has 2 overarching goals: evaluate the application of Meng and Rubin's (1992) pooling procedure for likelihood ratio statistic to the SEM test of model fit, and explore the possibility of using this test statistic to define imputation-based versions of common fit indices such as the TLI, CFI, and RMSEA. Computer simulation results suggested that, when applied to a correctly specified model, the pooled likelihood ratio statistic performed well as a global test of model fit and was closely calibrated to the corresponding full information maximum likelihood (FIML) test statistic. However, when applied to misspecified models with high rates of missingness (30%-40%), the imputation-based test statistic generally exhibited lower power than that of FIML. Using the pooled test statistic to construct imputation-based versions of the TLI, CFI, and RMSEA worked well and produced indices that were well-calibrated with those of full information maximum likelihood estimation. This article gives Mplus and R code to implement the pooled test statistic, and it offers a number of recommendations for future research. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  2. The problem of effect size heterogeneity in meta-analytic structural equation modeling.

    Science.gov (United States)

    Yu, Jia Joya; Downes, Patrick E; Carter, Kameron M; O'Boyle, Ernest H

    2016-10-01

    Scholars increasingly recognize the potential of meta-analytic structural equation modeling (MASEM) as a way to build and test theory (Bergh et al., 2016). Yet, 1 of the greatest challenges facing MASEM researchers is how to incorporate and model meaningful effect size heterogeneity identified in the bivariate meta-analysis into MASEM. Unfortunately, common MASEM approaches in applied psychology (i.e., Viswesvaran & Ones, 1995) fail to account for effect size heterogeneity. This means that MASEM effect sizes, path estimates, and overall fit values may only generalize to a small segment of the population. In this research, we quantify this problem and introduce a set of techniques that retain both the true score relationships and the variability surrounding those relationships in estimating model parameters and fit indices. We report our findings from simulated data as well as from a reanalysis of published MASEM studies. Results demonstrate that both path estimates and overall model fit indices are less representative of the population than existing MASEM research would suggest. We suggest 2 extension MASEM techniques that can be conducted using online software or in R, to quantify the stability of model estimates across the population and allow researchers to better build and test theory. (PsycINFO Database Record

  3. Testing students' e-learning via Facebook through Bayesian structural equation modeling.

    Science.gov (United States)

    Salarzadeh Jenatabadi, Hashem; Moghavvemi, Sedigheh; Wan Mohamed Radzi, Che Wan Jasimah Bt; Babashamsi, Parastoo; Arashi, Mohammad

    2017-01-01

    Learning is an intentional activity, with several factors affecting students' intention to use new learning technology. Researchers have investigated technology acceptance in different contexts by developing various theories/models and testing them by a number of means. Although most theories/models developed have been examined through regression or structural equation modeling, Bayesian analysis offers more accurate data analysis results. To address this gap, the unified theory of acceptance and technology use in the context of e-learning via Facebook are re-examined in this study using Bayesian analysis. The data (S1 Data) were collected from 170 students enrolled in a business statistics course at University of Malaya, Malaysia, and tested with the maximum likelihood and Bayesian approaches. The difference between the two methods' results indicates that performance expectancy and hedonic motivation are the strongest factors influencing the intention to use e-learning via Facebook. The Bayesian estimation model exhibited better data fit than the maximum likelihood estimator model. The results of the Bayesian and maximum likelihood estimator approaches are compared and the reasons for the result discrepancy are deliberated.

  4. Applying the Bollen-Stine Bootstrap for Goodness-of-Fit Measures to Structural Equation Models with Missing Data.

    Science.gov (United States)

    Enders, Craig K.

    2002-01-01

    Proposed a method for extending the Bollen-Stine bootstrap model (K. Bollen and R. Stine, 1992) fit to structural equation models with missing data. Developed a Statistical Analysis System macro program to implement this procedure, and assessed its usefulness in a simulation. The new method yielded model rejection rates close to the nominal 5%…

  5. Integrating affective and cognitive correlates of heart rate variability: A structural equation modeling approach.

    Science.gov (United States)

    Mann, Sarah L; Selby, Edward A; Bates, Marsha E; Contrada, Richard J

    2015-10-01

    High frequency heart rate variability (HRV) is a measure of neurocardiac communication thought to reflect predominantly parasympathetic cardiac regulation. Low HRV has been associated empirically with clinical and subclinical levels of anxiety and depression and, more recently, high levels of HRV have been associated with better performance on some measures of executive functioning (EF). These findings have offered support for theories proposing HRV as an index measure of a broad, self-regulatory capacity underlying aspects of emotion regulation and executive control. This study sought to test that proposition by using a structural equation modeling approach to examine the relationships of HRV to negative affect (NA) and EF in a large sample of U.S. adults ages 30s-80s. HRV was modeled as a predictor of an NA factor (self-reported trait anxiety and depression symptoms) and an EF factor (performance on three neuropsychological tests tapping facets of executive abilities). Alternative models also were tested to determine the utility of HRV for predicting NA and EF, with and without statistical control of demographic and health-related covariates. In the initial structural model, HRV showed a significant positive relationship to EF and a nonsignificant relationship to NA. In a covariate-adjusted model, HRV's associations with both constructs were nonsignificant. Age emerged as the only significant predictor of NA and EF in the final model, showing inverse relationships to both. Findings may reflect population and methodological differences from prior research; they also suggest refinements to the interpretations of earlier findings and theoretical claims regarding HRV.

  6. The ways parents cope with stress in difficult parenting situations: the structural equation modeling approach

    Directory of Open Access Journals (Sweden)

    Agnieszka Szymańska

    2017-06-01

    Full Text Available The purpose of this study was to verify a theoretical model of parents’ responses to difficulties they experienced with their child. The model presents relationships between seven variables: (a discrepancy between parental goal and the child’s current level of development, (b parental experience of a difficulty, (c representation of the child in the parent’s mind, (d parent’s withdrawal from the parenting situation, (e seeking help, (f distancing oneself from the situation, and (g applying pressure on the child. The study involved 319 parents of preschool children: 66 parents of three-year-olds, 85 parents of four-year-olds, 99 parents of five-year-olds and 69 parents of six-year-old children. Structural equations modeling (SEM was used to verify the compounds described in the theoretical model. The studies revealed that when a parent is experiencing difficulties, the probability increases that the parent will have one of two reactions towards that type of stress: withdrawal from the situation or applying pressure on the child. Experiencing difficulties has no connection with searching for help and is negatively related to distancing oneself from the situation.

  7. Restaurant Service Consumers’ Value Perceptions: A Study with Structural Equation Modeling

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    George Bedinelli Rossi Bedinelli Rossi

    2012-12-01

    Full Text Available This research aims to create a model that could explain consumers‘ value perception of restaurants attended on Sundays in the city of São Paulo. The research was carried out in two phases: first was an exploratory research project—a focus group–type with two groups of eight individuals each, which had the objective of discovering the main variables that impact the value perception of consumers. Thus, a balanced Likert-type scale was generated, with seven levels of concurrence. The scale was submitted to five experts for theoretical validation and was applied to a non probabilistic sample pursuant to the judgment of 360 consumers. Then, in a second phase, validation of the scale by the Confirmatory Factor Analysis method was provided as well as the building and analysis of five causal models by the method of Structural Equation Modeling. The final model with a better adjustment was composed of PRICE as an endogenous variable and ENVIRONMENT, SERVICE, FOOD, and HYGIENE as exogenous variables. Such conclusions allow the prediction of the decision process in relation to restaurant selection in two phases: (1 when a group of restaurants is chosen, and (2 the moment when the PRICE variable takes over the role of defining the value offered by each restaurant, which will motivate the selection.

  8. Identifying determinants of nations' wetland management programs using structural equation modeling: An exploratory analysis

    Science.gov (United States)

    La Peyre, M.K.; Mendelssohn, I.A.; Reams, M.A.; Templet, P.H.; Grace, J.B.

    2001-01-01

    Integrated management and policy models suggest that solutions to environmental issues may be linked to the socioeconomic and political Characteristics of a nation. In this study, we empirically explore these suggestions by applying them to the wetland management activities of nations. Structural equation modeling was used to evaluate a model of national wetland management effort and one of national wetland protection. Using five predictor variables of social capital, economic capital, environmental and political characteristics, and land-use pressure, the multivariate models were able to explain 60% of the variation in nations' wetland protection efforts based on data from 90 nations, as defined by level of participation, in the international wetland convention. Social capital had the largest direct effect on wetland protection efforts, suggesting that increased social development may eventually lead to better wetland protection. In contrast, increasing economic development had a negative linear relationship with wetland protection efforts, suggesting the need for explicit wetland protection programs as nations continue to focus on economic development. Government, environmental characteristics, and land-use pressure also had a positive direct effect on wetland protection, and mediated the effect of social capital on wetland protection. Explicit wetland protection policies, combined with a focus on social development, would lead to better wetland protection at the national level.

  9. Comparing Bayesian and Maximum Likelihood Predictors in Structural Equation Modeling of Children’s Lifestyle Index

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    Che Wan Jasimah bt Wan Mohamed Radzi

    2016-11-01

    Full Text Available Several factors may influence children’s lifestyle. The main purpose of this study is to introduce a children’s lifestyle index framework and model it based on structural equation modeling (SEM with Maximum likelihood (ML and Bayesian predictors. This framework includes parental socioeconomic status, household food security, parental lifestyle, and children’s lifestyle. The sample for this study involves 452 volunteer Chinese families with children 7–12 years old. The experimental results are compared in terms of root mean square error, coefficient of determination, mean absolute error, and mean absolute percentage error metrics. An analysis of the proposed causal model suggests there are multiple significant interconnections among the variables of interest. According to both Bayesian and ML techniques, the proposed framework illustrates that parental socioeconomic status and parental lifestyle strongly impact children’s lifestyle. The impact of household food security on children’s lifestyle is rejected. However, there is a strong relationship between household food security and both parental socioeconomic status and parental lifestyle. Moreover, the outputs illustrate that the Bayesian prediction model has a good fit with the data, unlike the ML approach. The reasons for this discrepancy between ML and Bayesian prediction are debated and potential advantages and caveats with the application of the Bayesian approach in future studies are discussed.

  10. The impact of culture and employee-focused criteria on productivity: A structural equation modelling approach

    Science.gov (United States)

    Ab Hamid, Mohd Rashid; Mustafa, Zainol; Mohd Suradi, Nur Riza; Idris, Fazli; Abdullah, Mokhtar

    2013-04-01

    Culture and employee-focused criteria are important factors for the success of any organization. These factors have to be aligned with the productivity initiatives in the organization in order to gear ahead for excellence. Therefore, this article investigated the impact of culture and employee-focused criteria on productivity in Higher Education Institutions (HEIs) in Malaysia using intangible indicators through core values. The hypothesized relationship was tested using Structural Equation Modeling (SEM) with the PLS estimation technique. 429 questionnaires were returned from the target population. The results of the modelling revealed that the PLS estimation confirmed all the hypotheses tested as in the hypothesized model. The results generally support significant relationships between culture values, employee-focused values and productivity-focused values. The study also confirmed the mediating role of employee-focused values for the relationship between culture values and productivity-focused values. In conclusion, the empirically validated results supported the adequacy of the hypothezised model of the impact of culture and employee-focused criteria on productivity in HEI through value-based indicators.

  11. Algebraic Structure of tt * Equations for Calabi-Yau Sigma Models

    Science.gov (United States)

    Alim, Murad

    2017-08-01

    The tt * equations define a flat connection on the moduli spaces of {2d, \\mathcal{N}=2} quantum field theories. For conformal theories with c = 3 d, which can be realized as nonlinear sigma models into Calabi-Yau d-folds, this flat connection is equivalent to special geometry for threefolds and to its analogs in other dimensions. We show that the non-holomorphic content of the tt * equations, restricted to the conformal directions, in the cases d = 1, 2, 3 is captured in terms of finitely many generators of special functions, which close under derivatives. The generators are understood as coordinates on a larger moduli space. This space parameterizes a freedom in choosing representatives of the chiral ring while preserving a constant topological metric. Geometrically, the freedom corresponds to a choice of forms on the target space respecting the Hodge filtration and having a constant pairing. Linear combinations of vector fields on that space are identified with the generators of a Lie algebra. This Lie algebra replaces the non-holomorphic derivatives of tt * and provides these with a finer and algebraic meaning. For sigma models into lattice polarized K3 manifolds, the differential ring of special functions on the moduli space is constructed, extending known structures for d = 1 and 3. The generators of the differential rings of special functions are given by quasi-modular forms for d = 1 and their generalizations in d = 2, 3. Some explicit examples are worked out including the case of the mirror of the quartic in {\\mathbbm{P}^3}, where due to further algebraic constraints, the differential ring coincides with quasi modular forms.

  12. Evaluating Fit Indices for Multivariate t-Based Structural Equation Modeling with Data Contamination

    Directory of Open Access Journals (Sweden)

    Mark H. C. Lai

    2017-07-01

    Full Text Available In conventional structural equation modeling (SEM, with the presence of even a tiny amount of data contamination due to outliers or influential observations, normal-theory maximum likelihood (ML-Normal is not efficient and can be severely biased. The multivariate-t-based SEM, which recently got implemented in Mplus as an approach for mixture modeling, represents a robust estimation alternative to downweigh the impact of outliers and influential observations. To our knowledge, the use of maximum likelihood estimation with a multivariate-t model (ML-t to handle outliers has not been shown in SEM literature. In this paper we demonstrate the use of ML-t using the classic Holzinger and Swineford (1939 data set with a few observations modified as outliers or influential observations. A simulation study is then conducted to examine the performance of fit indices and information criteria under ML-Normal and ML-t in the presence of outliers. Results showed that whereas all fit indices got worse for ML-Normal with increasing amount of outliers and influential observations, their values were relatively stable with ML-t, and the use of information criteria was effective in selecting ML-normal without data contamination and selecting ML-t with data contamination, especially when the sample size was at least 200.

  13. Investigating The Relationship Between Flourishing And Self-Compassion: A Structural Equation Modeling Approach

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    Seydi Ahmet Satici

    2013-12-01

    Full Text Available The purpose of this study was to examine the relationships between flourishing and self-compassion. Participants were 347 (194 female and 153 male university students, between age range of 18-24, who completed a questionnaire package that included the Flourishing Scale and the Self-compassion Scale. The relationships between flourishing and self-compassion were examined using correlation analysis and the hypothesis model was tested through structural equation modeling. In correlation analysis, self-kindness, common humanity, and mindfulness factors of self-compassion were found positively and self-judgment, isolation, and over-identification factors of self-compassion were found negatively related to flourishing. The model demonstrated fit (χ²=37.12, χ²/df = 4.12, RMSEA = .095, SRMR = .074, GFI = .97, AGFI = .91, CFI= .97, and NFI = .96. According to path analysis results, self-kindness, common humanity, and mindfulness were predicted positively by flourishing. Further, flourishing predicted self-judgment, isolation, and over-identification in a negative way. Results were discussed in the light of the related literature.

  14. The Factors Influencing Satisfaction with Public City Transport: A Structural Equation Modelling Approach

    Directory of Open Access Journals (Sweden)

    Pawlasova Pavlina

    2015-12-01

    Full Text Available Satisfaction is one of the key factors which influences customer loyalty. We assume that the satisfied customer will be willing to use the ssame service provider again. The overall passengers´ satisfaction with public city transport may be affected by the overall service quality. Frequency, punctuality, cleanliness in the vehicle, proximity, speed, fare, accessibility and safety of transport, information and other factors can influence passengers´ satisfaction. The aim of this paper is to quantify factors and identify the most important factors influencing customer satisfaction with public city transport within conditions of the Czech Republic. Two methods of analysis are applied in order to fulfil the aim. The method of factor analysis and the method Varimax were used in order to categorize variables according to their mutual relations. The method of structural equation modelling was used to evaluate the factors and validate the model. Then, the optimal model was found. The logistic parameters, including service continuity and frequency, and service, including information rate, station proximity and vehicle cleanliness, are the factors influencing passengers´ satisfaction on a large scale.

  15. A structural equation model analysis of phosphorus transformations in global unfertilized and uncultivated soils

    Science.gov (United States)

    Hou, Enqing; Chen, Chengrong; Kuang, Yuanwen; Zhang, Yuguang; Heenan, Marijke; Wen, Dazhi

    2016-09-01

    Understanding the soil phosphorus (P) cycle is a prerequisite for predicting how environmental changes may influence the dynamics and availability of P in soil. We compiled a database of P fractions sequentially extracted by the Hedley procedure and its modification in 626 unfertilized and uncultivated soils worldwide. With this database, we applied structural equation modeling to test hypothetical soil P transformation models and to quantify the importance of different soil P pools and P transformation pathways in shaping soil P availability at a global scale. Our models revealed that soluble inorganic P (Pi, a readily available P pool) was positively and directly influenced by labile Pi, labile organic P (Po), and primary mineral P and negatively and directly influenced by secondary mineral P; soluble Pi was not directly influenced by moderately labile Po or occluded P. The overall effect on soluble Pi was greatest for labile Pi followed by the organic P pools, occluded P, and then primary mineral P; the overall influence from secondary mineral P was small. Labile Pi was directly linked to all other soil P pools and was more strongly linked than soluble Pi to labile Po and primary mineral P. Our study highlights the important roles of labile Pi in mediating P transformations and in determining overall P availability in soils throughout the world.

  16. Diagnosis Analysis of 4 TCM Patterns in Suboptimal Health Status: A Structural Equation Modelling Approach

    Directory of Open Access Journals (Sweden)

    Li-Min Wang

    2012-01-01

    Full Text Available Background. We illustrated an example of structure equation modelling (SEM in the research on SHS to explore the diagnosis of the Sub optimal health status (SHS and provide evidence for the standardization of traditional Chinese medicine (TCM patterns in SHS. And the diagnosis of 4 TCM patterns in SHS was evaluated in this analysis. Methods. This study assessed data on 2807 adults (aged 18 to 49 with SHS from 6 clinical centres. SEM was used to analyze the patterns of SHS in TCM. Parameters in the introduced model were estimated by the maximum likelihood method. Results. The discussed model fits the SHS data well with CFI = 0.851 and RMSEA = 0.075. The direct effect of Qi deficiency pattern on dampness pattern had the highest magnitude (value of estimate is 0.822. With regard to the construct of “Qi deficiency pattern”, “fire pattern”, “stagnation pattern” and “dampness pattern”, the indicators with the highest load were myasthenia of limbs, vexation, deprementia, and dizziness, respectively. It had been shown that estimate factor should indicate the important degree of different symptoms in pattern. Conclusions. The weights of symptoms in the respective pattern can be statistical significant and theoretical meaningful for the 4 TCM patterns identification in SHS research. The study contributed to a theoretical framework, which has implications for the diagnosis points of SHS.

  17. A Structural Equation Model (SEM of Governing Factors Influencing the Implementation of T-Government

    Directory of Open Access Journals (Sweden)

    Sameer Alshetewi

    2015-11-01

    Full Text Available Governments around the world have invested significant sums of money on Information and Communication Technology (ICT to improve the efficiency and effectiveness of services been provided to their citizens. However, they have not achieved the desired results because of the lack of interoperability between different government entities. Therefore, many governments have started shifting away from the original concept of e-Government towards a much more transformational approach that encompasses the entire relationship between different government departments and users of public services, which can be termed as transformational government (t- Government. In this paper, a model is proposed for governing factors that impact the implementation of t-Government such as strategy, leadership, stakeholders, citizen centricity and funding in the context of Saudi Arabia. Five constructs are hypothesised to be related to the implementation of t-Government. To clarify the relationships among these constructs, a structural equation model (SEM is utilised to examine the model fit with the five hypotheses. The results show that there are positive and significant relationships among the constructs such as the relationships between strategy and t-Government; the relationships between stakeholders and t-Government; the relationships between leadership and t-Government. This study also showed an insignificant relationship between citizens’ centricity and t-Government and also an insignificant relationship between funding and t-Government. document is a “live” template and already defines the components of your paper [title, text, heads, etc.] in its style sheet.

  18. Negative Cognition, Depressed Mood, and Paranoia: A Longitudinal Pathway Analysis Using Structural Equation Modeling

    Science.gov (United States)

    Fowler, David; Hodgekins, Joanne; Garety, Philippa; Freeman, Daniel; Kuipers, Elizabeth; Dunn, Graham; Smith, Ben; Bebbington, Paul E.

    2012-01-01

    The role of negative cognition and effect in maintaining psychotic symptoms is increasingly recognized but has yet to be substantiated though longitudinal analysis. Based on an a priori theoretical model, we hypothesized that negative cognition and depressed mood play a direct causal role in maintaining paranoia in people with psychosis and that the effect of mood is mediated by negative cognition. We used data from the 301 patients in the Prevention of Relapse in Psychosis Trial of cognitive behavior therapy. They were recruited from consecutive Community Mental Health Team clients presenting with a recent relapse of psychosis. The teams were located in inner and outer London and the rural county of Norfolk, England. The study followed a longitudinal cohort design, with initial measures repeated at 3 and 12 months. Structural equation modeling was used to investigate the direction of effect between negative cognition, depressed mood, and paranoia. Overall fit was ambiguous in some analyses and confounding by unidentified variables cannot be ruled out. Nevertheless, the most plausible models were those incorporating pathways from negative cognition and depressed mood to paranoid symptoms: There was no evidence whatsoever for pathways in the reverse direction. The link between depressed mood and paranoia appeared to be mediated by negative cognition. Our hypotheses were thus corroborated. This study provides evidence for the role of negative cognition in the maintenance of paranoia, a role of central relevance, both to the design of psychological interventions and to the conceptualizations of psychosis. PMID:21474550

  19. Linking impulsivity to dysfunctional thought control and insomnia: a structural equation model.

    Science.gov (United States)

    Schmidt, Ralph E; Gay, Philippe; Ghisletta, Paolo; VAN DER Linden, Martial

    2010-03-01

    According to cognitive models of insomnia, excessive mental activity at bedtime may be viewed as an important impediment to the process of falling asleep. A further assumption of these models is that 'cognitive arousal' may be perpetuated and exacerbated by counterproductive strategies of thought management. As yet, little is known about factors that may predispose people to rely on these strategies when confronted with thoughts that keep them awake at night. This study examined the relations between impulsivity, use of different thought-control strategies and insomnia severity. A sample of 391 university students completed the UPPS Impulsive Behavior Scale, the Thought Control Questionnaire Insomnia-Revised and the Insomnia Severity Index. Correlation analyses revealed that two facets of impulsivity (urgency and lack of perseverance), two strategies of thought control (aggressive suppression and worry) and insomnia severity were positively associated. Follow-up structural equation modeling analyses showed that the two mentioned thought-control strategies mediated the effects of the two facets of impulsivity on sleep problems. These findings extend existing cognitive accounts of insomnia by suggesting how predisposing and perpetuating factors may be related: specific personality traits may incline individuals to respond with dysfunctional thought-control strategies to unwanted mental activity at night.

  20. Pediatric health-related quality of life: a structural equation modeling approach.

    Directory of Open Access Journals (Sweden)

    Ester Villalonga-Olives

    Full Text Available OBJECTIVES: One of the most referenced theoretical frameworks to measure Health Related Quality of Life (HRQoL is the Wilson and Cleary framework. With some adaptions this framework has been validated in the adult population, but has not been tested in pediatric populations. Our goal was to empirically investigate it in children. METHODS: The contributory factors to Health Related Quality of Life that we included were symptom status (presence of chronic disease or hospitalizations, functional status (developmental status, developmental aspects of the individual (social-emotional behavior, and characteristics of the social environment (socioeconomic status and area of education. Structural equation modeling was used to assess the measurement structure of the model in 214 German children (3-5 years old participating in a follow-up study that investigates pediatric health outcomes. RESULTS: Model fit was χ2 = 5.5; df = 6; p = 0.48; SRMR  = 0.01. The variance explained of Health Related Quality of Life was 15%. Health Related Quality of Life was affected by the area education (i.e. where kindergartens were located and development status. Developmental status was affected by the area of education, socioeconomic status and individual behavior. Symptoms did not affect the model. CONCLUSIONS: The goodness of fit and the overall variance explained were good. However, the results between children' and adults' tests differed and denote a conceptual gap between adult and children measures. Indeed, there is a lot of variety in pediatric Health Related Quality of Life measures, which represents a lack of a common definition of pediatric Health Related Quality of Life. We recommend that researchers invest time in the development of pediatric Health Related Quality of Life theory and theory based evaluations.

  1. Assessing overall patient satisfaction in inflammatory bowel disease using structural equation modeling.

    Science.gov (United States)

    Soares, João-Bruno; Marinho, Ana S; Fernandes, Dália; Moreira Gonçalves, Bruno; Camila-Dias, Cláudia; Gonçalves, Raquel; Magro, Fernando

    2015-08-01

    Structural equation modeling (SEM) is a very popular data-analytic technique for the evaluation of customer satisfaction. We aimed to measure the overall satisfaction of inflammatory bowel disease (IBD) patients with healthcare in Portugal and to define its main determinants using SEM. The study included three steps: (i) specification of a patient satisfaction model that included the following dimensions: Image, Expectations, Facilities, Admission process, Assistant staff, Nursing staff, Medical staff, Treatment, Inpatient care, Outpatient care, Overall quality, Overall satisfaction, and Loyalty; (ii) sample survey from 2000 patients, members of the Portuguese Association of the IBD; and (iii) estimation of the satisfaction model using partial least squares (XLSTAT-PLSPM). We received 498 (25%) valid questionnaires from 324 (66%) patients with Crohn's disease and 162 (33%) patients with ulcerative colitis. Our model provided a substantial explanation for Overall satisfaction (R=0.82). The mean index of overall satisfaction was 74.4 (0-100 scale). The main determinants of Overall satisfaction were the Image (β=0.26), Outpatient care (β=0.23), and Overall quality (β=0.21), whose mean indices were 83, 75, and 81, respectively. Facilities and Inpatient care were the variables with a significant impact on Overall satisfaction and the worst mean indices. SEM is useful for the evaluation of IBD patient satisfaction. The Overall satisfaction of IBD patients with healthcare in Portugal is good, but to increase it, IBD services need to focus on the improvement of Outpatient care, Facilities, and Inpatient care. Our model could be a matrix for a global model of IBD patient satisfaction.

  2. Construct Validity of the Social Provisions Scale: A Bifactor Exploratory Structural Equation Modeling Approach.

    Science.gov (United States)

    Perera, Harsha N

    2016-12-01

    Extant theory posits well-differentiated dimensions of perceived social support as measured using the Social Provisions Scale (SPS). However, evidence is inconsistent with this multidimensionality perspective, with SPS factor correlations near unity and higher between-factor than within-factor item correlations. This article reports on research investigating the internal structure, gender invariance, and predictive validity of SPS scores. The analyses are conducted in a novel bifactor exploratory structural equation modeling (ESEM) framework, which is designed to account for presumed psychometric multidimensionality in SPS items due to (a) their fallibility as pure indicators of the constructs they are purported to measure and (b) the coexistence of general and specific factors. Based on 376 item responses, evidence was obtained for a bifactor-ESEM representation of the SPS data. In addition, support was found for the invariance of item thresholds and the latent mean invariance of six of the seven SPS factors in the retained solution. Only mean levels of Social Integration were found to differ by gender, with men scoring higher than women. Finally, evidence was obtained for the predictive validity of SPS scores with respect to loneliness and psychological well-being. Quite apart from yielding evidence validating the SPS, this research demonstrates the utility of bifactor ESEM for psychological assessment.

  3. Factors Determinants the Choice of Mobile Service Providers: Structural Equation Modeling Approach on Bangladeshi Consumers

    Directory of Open Access Journals (Sweden)

    Ahasanul Haque

    2010-07-01

    Full Text Available The aim of this study is to find out what were the factors that may have played significant role to select the telecommunication service providers. In general this research has an intention to develop a research framework grounded on a strong theoretical and literature review background. The survey instruments employed on Bangladeshi consumers included demographic background, price, service quality, product quality and availability and promotional offers for consumer perception. Thus the structural equation modeling approach was necessary in order to examine the variables. The data analysis was conducted using SPSS and AMOS (Analysis of Moment Structure with the software package for windows. From the result it is revealed that paths are related to the casual processes significantly. Among all the significant variables, from our result, Price is the most important among our respondents followed by Service quality, product quality and promotion. Further research should be considered to gather more information regarding the service quality and customers’ satisfaction dimensions in context of the Bangladeshi mobile phone operators. It is hoped that the findings of this study may assist mobile phone industry in Bangladesh about their services and promotion of their services. However, the findings of this study may provide needed feedback and contribute to the improvement of players’ strategy and their marketing program

  4. Analysis of heterogeneity and epistasis in physiological mixed populations by combined structural equation modelling and latent class analysis

    DEFF Research Database (Denmark)

    Fenger, Mogens; Linneberg, A.; Werge, Thomas Mears

    2008-01-01

    and genetic variations of such networks. METHODS: In this study on type 2 diabetes mellitus, heterogeneity was resolved in a latent class framework combined with structural equation modelling using phenotypic indicators of distinct physiological processes. We modelled the clinical condition "the metabolic...

  5. Examining the Relationship between Middle School Students' Critical Reading Skills, Science Literacy Skills and Attitudes: A Structural Equation Modeling

    Science.gov (United States)

    Karademir, Ersin; Ulucinar, Ufuk

    2017-01-01

    The purpose of this study is to verify the causal relationship between middle school students' critical reading skills, science literacy skills and attitudes towards science literacy with research data according to the default model. Through the structural equation modeling, path analysis has been applied in the study which was designed in…

  6. The Effects of Cognitive Style on Edmodo Users' Behaviour: A Structural Equation Modeling-Based Multi-Group Analysis

    Science.gov (United States)

    Ursavas, Omer Faruk; Reisoglu, Ilknur

    2017-01-01

    Purpose: The purpose of this paper is to explore the validity of extended technology acceptance model (TAM) in explaining pre-service teachers' Edmodo acceptance and the variation of variables related to TAM among pre-service teachers having different cognitive styles. Design/methodology/approach: Structural equation modeling approach was used to…

  7. Role of transformational leadership on employee productivity of teaching hospitals: using structural equation modeling.

    Science.gov (United States)

    Vatankhah, Soudabeh; Alirezaei, Samira; Khosravizadeh, Omid; Mirbahaeddin, Seyyed Elmira; Alikhani, Mahtab; Alipanah, Mobarakeh

    2017-08-01

    In today's transforming world, increased productivity and efficient use of existing facilities are practically beyond a choice and become a necessity. In this line, attention to change and transformation is one of the affecting factors on the growth of productivity in organizations, especially in hospitals. To examine the effect of transformational leadership on the productivity of employees in teaching hospitals affiliated to Iran University of Medical Sciences. This cross-sectional study was conducted on 254 participants from educational and medical centers affiliated to Iran University of Medical Sciences (Tehran, Iran) in 2016. The standard questionnaires of Bass & Avolio and of Hersi & Goldsmith were used to respectively assess transformational leadership and level of productivity. The research assumptions were tested in a significance level of 0.05 by applying descriptive statistics and structural equations modeling (SEM) using SPSS 19 and Amos 24. Results of the fitting indicators of the assessing model after amending includes Chi-square two to degrees of freedom of 2.756, CFI indicator 0.95, IFI indicator 0.92, Root mean square error of approximation (RMSEA) indicator 0.10. These results indicate that the assessing model is well fitting after the amendment. Also, analysis of the model's assumptions and the final model of the research reveals the effect of transformational leadership on employees' productivity with a significance level of 0.83 (p=0.001). This research indicates that the more the leadership and decision-making style in hospitals lean towards transformational mode, the more positive outcomes it brings among employees and the organization due to increased productivity. Therefore, it is essential to pay focused attention to training/educational programs in organizations to create and encourage transformational leadership behaviors which hopefully lead to more productive employees.

  8. Predictors of Quality of Life in Portuguese Obese Patients: A Structural Equation Modeling Application

    Directory of Open Access Journals (Sweden)

    Estela Vilhena

    2014-01-01

    Full Text Available Living with obesity is an experience that may affect multiple aspects of an individual’s life. Obesity is considered a relevant public health problem in modern societies. To determine the comparative efficacy of different treatments and to assess their impact on patients’ everyday life, it is important to identify factors that are relevant to the quality of life of obese patients. The present study aims to evaluate, in Portuguese obese patients, the simultaneous impact of several psychosocial factors on quality of life. This study also explores the mediating role of stigma in the relationship between positive/negative affect and quality of life. A sample of 215 obese patients selected from the main hospitals in Portugal completed self-report questionnaires to assess sociodemographic, clinical, psychosocial, and quality of life variables. Data were analysed using structural equation modeling. The model fitted the data reasonably well, CFI = 0.9, RMSEA = 0.06. More enthusiastic and more active patients had a better quality of life. Those who reflect lower perception of stigma had a better physical and mental health. Partial mediation effects of stigma between positive affect and mental health and between negative affect and physical health were found. The stigma is pervasive and causes consequences for psychological and physical health.

  9. Corruption and population health outcomes: an analysis of data from 133 countries using structural equation modeling.

    Science.gov (United States)

    Factor, Roni; Kang, Minah

    2015-09-01

    The current study aims to develop a theoretical framework for understanding the antecedents of corruption and the effects of corruption on various health indicators. Using structural equation models, we analyzed a multinational dataset of 133 countries that included three main groups of variables--antecedents of corruption, corruption measures, and health indicators. Controlling for various factors, our results suggest that corruption rises as GDP per capita falls and as the regime becomes more autocratic. Higher corruption is associated with lower levels of health expenditure as a percentage of GDP per capita, and with poorer health outcomes. Countries with higher GDP per capita and better education for women have better health outcomes regardless of health expenditures and regime type. Our results suggest that there is no direct relationship between health expenditures and health outcomes after controlling for the other factors in the model. Our study enhances our understanding of the conceptual and theoretical links between corruption and health outcomes in a population, including factors that may mediate how corruption can affect health outcomes.

  10. The relationship between occupational culture dimensions and reward preferences: A structural equation modelling approach

    Directory of Open Access Journals (Sweden)

    Mark Bussin

    2016-02-01

    Full Text Available Orientation: Reward has links to employee attraction and retention and as such has a role to play in managing talent. However, despite a range of research, there is still lack of clarity on employee preferences relating to reward.Research purpose: The purpose of the research was to recommend and appraise a theoretical model of the relationship between occupational culture dimensions and reward preferences of specific occupational groups in the South African context.Motivation for the study: The motivation for this study was to address the gap that exists with reward preferences and occupational culture with a view to identifying and gaining insight into individual preferences.Research design, approach and method: A structural equation modelling approach was adopted in exploring the proposed relationships. A South African Information, Communication, and Technology (ICT organisation served as the population, and a web-based survey assisted in gathering study data (n = 1362.Main findings: The findings provided support for the relationship between occupational culture dimensions and certain reward preferences. In particular, statistically significant results were obtained with the inclusion of the Environment, Team, and Time occupational culture dimensions as independent variables.Practical implications and value-add: The study provides workable input to organisations and reward professionals in the design of their reward strategies and programmes.Keywords: compensation; employee preferences; occupational culture; remuneration; reward preferences

  11. Structural equation model to investigate the factors influencing quality performance in Indian construction projects

    Indian Academy of Sciences (India)

    S Shanmugapriya; K Subramanian

    2015-09-01

    Indian construction industry has seen remarkable growth and it is an integral part of the economy with massive foreign investments which demands quality construction. The pressure to reduce time and cost of construction increases the risk on the part of stakeholders with respect to quality and safety of the construction. The problem is serious and dangerous in developing countries like India which requires focus and attention for sustained growth in construction sector. This research reports on the adoption and development of structural equation model to study the fundamental relationship between five enablers of European Foundation for quality management (EFQM) framework to improve the quality performance in Indian construction projects. Data collected from clients, contractors and consultants of Indian construction industry through questionnaire survey was used to analyze the conceptual framework using smart PLS software. The conceptual model in this research includes eight hypotheses and T-statistics values is used for checking the significance of the hypothesis. The findings of the study revealed that leadership factor has strongest total effect on people factor (Path coefficient = 0.77) and process factor has strongest effect in achieving the goals of quality performance improvement in construction projects (Path coefficient = 0.7). The results indicate that Indian construction organizations must give top priority to leadership and process related problems in various phases of the project to result in continuous improvement in quality performance.

  12. Selected neurophysiological, psychological, and behavioral influences on subjective sleep quality in nurses: a structure equation model.

    Directory of Open Access Journals (Sweden)

    Min-Huey Chung

    Full Text Available Few studies have examined relationships among neurophysiological, psychological, and behavioral factors with regard to their effects on sleep quality. We used a structure equation model to investigate behavioral and psychological factors that influence neurophysiological regulation of sleep in shift workers. Using a cross-sectional study design, we tested the model with a sample of 338 female nurses working rotating shifts at an urban regional hospital. The Morningness-Eveningness Questionnaire (MEQ and short-form Menstrual Distress Questionnaire (MDQ were used to measure neurophysiological factors involved in morningness-eveningness and menstrual distress. The Sleep Hygiene Awareness and Practice Scale (SHAPS and Profile of Mood States Short Form (POMS-SF were completed to measure behavioral factors of sleep hygiene practices and psychological factors of mood states. In addition, the Pittsburgh Sleep Quality Index (PSQI measured participant's self-reported sleep quality. The results revealed that sleep hygiene practices and mood states mediated the effects of morningness-eveningness and menstrual distress on sleep quality. Our findings provide support for developing interventions to enhance sleep hygiene and maintain positive mood states to reduce the influence of neurophysiological factors on sleep quality among shift workers.

  13. Selected neurophysiological, psychological, and behavioral influences on subjective sleep quality in nurses: a structure equation model.

    Science.gov (United States)

    Chung, Min-Huey; Liu, Wen-I; Lee, Hui-Ling; Hsu, Nanly

    2013-01-01

    Few studies have examined relationships among neurophysiological, psychological, and behavioral factors with regard to their effects on sleep quality. We used a structure equation model to investigate behavioral and psychological factors that influence neurophysiological regulation of sleep in shift workers. Using a cross-sectional study design, we tested the model with a sample of 338 female nurses working rotating shifts at an urban regional hospital. The Morningness-Eveningness Questionnaire (MEQ) and short-form Menstrual Distress Questionnaire (MDQ) were used to measure neurophysiological factors involved in morningness-eveningness and menstrual distress. The Sleep Hygiene Awareness and Practice Scale (SHAPS) and Profile of Mood States Short Form (POMS-SF) were completed to measure behavioral factors of sleep hygiene practices and psychological factors of mood states. In addition, the Pittsburgh Sleep Quality Index (PSQI) measured participant's self-reported sleep quality. The results revealed that sleep hygiene practices and mood states mediated the effects of morningness-eveningness and menstrual distress on sleep quality. Our findings provide support for developing interventions to enhance sleep hygiene and maintain positive mood states to reduce the influence of neurophysiological factors on sleep quality among shift workers.

  14. Psychosocial sources of stress and burnout in the construction sector: a structural equation model.

    Science.gov (United States)

    Meliá, Josep L; Becerril, Marta

    2007-11-01

    This study develops and tests a structural equation model of social stress factors in the construction industry. Leadership behaviours, role conflict and mobbing behaviours are considered exogenous sources of stress; the experience of tension and burnout are considered mediator variables; and psychological well-being, propensity to quit and perceived quality are the final dependent variables. A sample of Spanish construction workers participated voluntarily and anonymously in the study. After considering the indices of modification, leadership showed direct effects on the propensity to quit and perceived quality. The overall fit of the model is adequate (chi2 (13)= 10.69, p = .637, GFI= .975, AGFI= .93, RMR= .230, NFI= .969, TLI= 1.016, CFI= 1.000, RMSEA= .329). Construction has been considered a sector characterized more by high physical risks than socially-related risks. In this context, these findings about the effects of social sources of stress in construction raise new questions about the organizational characteristics of the sector and their psychosocial risks.

  15. The effect of community stress and problems on psychopathology: A structural equation modeling study.

    Science.gov (United States)

    Lyu, Juncheng; Shi, Hong; Wang, Suzhen; Zhang, Jie

    2016-02-01

    This research aimed to estimate the effect of perceived social factors in the community stress and problems on the residents' psychopathology such as depression and suicidal behaviors. Subjects of this study were the informants (N=1618) in a psychological autopsy (PA) study with a case-control design. We interviewed two informants (a family member and a close friend) for 392 suicides and 416 living controls, which came from 16 rural counties randomly selected from three provinces of China. Community stress and problems were measured by the WHO SUPRE-MISS scale. Depression was measured by CES-D scale, and suicidal behavior was assessed by NCS-R scale. Multivariable liner and logistic regression models and the Structural Equation Modeling (SEM) were applied to probe the correlation of the depression and the suicidal behaviors with some major demographic variables as covariates. It was found that community stress and problems were directly associated with rural Chinese residents' depression (Path coefficient=0.127, Pstress and problem and suicidal behaviors, but community stress and problem can affect suicidal behaviors indirectly through depression. The path coefficient between depression and suicidal behaviors was 0.975. The current study predicts a new research viewpoint, that is, the depression is the intermediate between community stress and problem and suicidal behaviors. It might be an effective route to prevent depression directly and suicidal behaviors indirectly by reducing the community stress and problems.

  16. Empirical investigation of e-learning acceptance and assimilation: A structural equation model

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    Said S. Al-Gahtani

    2016-01-01

    Full Text Available E-learning has become progressively more vital for academia and corporate training and has potentially become one of the most significant developments and applications in Information Technologies (ITs. This study used a quantitative approach seeking a causative explanation of the decision behavior of individuals toward the acceptance and assimilation of e-learning in academic settings. A survey of 286 participants (students was conducted to collect the research data. Our study framework was based on the third version of the Technology Acceptance Model (i.e., TAM3 and the data were analyzed using structural equation modeling in order to determine the factors that influence the learners’ intention to use e-learning. Results show the predicting (promoting/inhibiting factors of e-learning technology acceptance, while also examining some related post-implementation interventions expected to contribute to the acceptance and assimilation of e-learning systems. Our results also indicate that TAM3 holds well in the Arabian culture and also outline valuable outcomes such as: managerial interventions and controls for better organizational e-learning management that can lead to greater acceptance and effective utilization. Hopefully, this study provides a roadmap to more understanding of the success factors and post-implementation interventions contributing to the acceptance and assimilation of e-learning systems in developing countries.

  17. Neurological abnormalities and neurocognitive functions in healthy elder people: A structural equation modeling analysis

    Directory of Open Access Journals (Sweden)

    Chan Raymond CK

    2011-08-01

    Full Text Available Abstract Background/Aims Neurological abnormalities have been reported in normal aging population. However, most of them were limited to extrapyramidal signs and soft signs such as motor coordination and sensory integration have received much less attention. Very little is known about the relationship between neurological soft signs and neurocognitive function in healthy elder people. The current study aimed to examine the underlying relationships between neurological soft signs and neurocognition in a group of healthy elderly. Methods One hundred and eighty healthy elderly participated in the current study. Neurological soft signs were evaluated with the subscales of Cambridge Neurological Inventory. A set of neurocognitive tests was also administered to all the participants. Structural equation modeling was adopted to examine the underlying relationship between neurological soft signs and neurocognition. Results No significant differences were found between the male and female elder people in neurocognitive function performances and neurological soft signs. The model fitted well in the elderly and indicated the moderate associations between neurological soft signs and neurocognition, specifically verbal memory, visual memory and working memory. Conclusions The neurological soft signs are more or less statistically equivalent to capture the similar information done by conventional neurocognitive function tests in the elderly. The implication of these findings may serve as a potential neurological marker for the early detection of pathological aging diseases or related mental status such as mild cognitive impairment and Alzheimer's disease.

  18. Determinants of phubbing, which is the sum of many virtual addictions: a structural equation model.

    Science.gov (United States)

    Karadağ, Engin; Tosuntaş, Şule Betül; Erzen, Evren; Duru, Pinar; Bostan, Nalan; Şahin, Berrak Mizrak; Çulha, İlkay; Babadağ, Burcu

    2015-06-01

    Phubbing can be described as an individual looking at his or her mobile phone during a conversation with other individuals, dealing with the mobile phone and escaping from interpersonal communication. In this research, determinants of phubbing behavior were investigated; in addition, the effects of gender, smart phone ownership and social media membership were tested as moderators. To examine the cause-effect relations among the variables of the theoretical model, the research employs a correlational design. Participants were 409 university students who were selected via random sampling. Phubbing was obtained via the scales featuring mobile phone addiction, SMS addiction, internet addiction, social media addiction and game addiction. The obtained data were analyzed using a correlation analysis, multiple linear regression analysis and structural equation model. The results showed that the most important determinants of phubbing behavior are mobile phone, SMS, social media and internet addictions. Although the findings show that the highest correlation value explaining phubbing is a mobile phone addiction, the other correlation values reflect a dependency on the phone. There is an increasing tendency towards mobile phone use, and this tendency prepares the basis of phubbing.

  19. Behavioural Comparison of Driverswhen Driving a Motorcycle or a Car: A Structural Equation Modelling Study

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    Darja Topolšek

    2015-12-01

    Full Text Available The goal of the study was to investigate if the drivers behave in the same way when they are driving a motorcycle or a car. For this purpose, the Motorcycle Rider Behaviour Questionnaire and Driver Behaviour Questionnaire were conducted among the same drivers population. Items of questionnaires were used to develop a structural equation model with two factors, one for the motorcyclist’s behaviour, and the other for the car driver’s behaviour. Exploratory and confirmatory factor analyses were also applied in this study. Results revealed a certain difference in driving behaviour. The principal reason lies probably in mental consciousness that the risk-taking driving of a motorbike can result in much more catastrophic consequences than when driving a car. The drivers also pointed out this kind of thinking and the developed model has statistically confirmed the behavioural differences. The implications of these findings are also argued in relation to the validation of the appropriateness of the existing traffic regulations.

  20. Nonparametric Estimates of Gene × Environment Interaction Using Local Structural Equation Modeling

    Science.gov (United States)

    Briley, Daniel A.; Harden, K. Paige; Bates, Timothy C.; Tucker-Drob, Elliot M.

    2017-01-01

    Gene × Environment (G×E) interaction studies test the hypothesis that the strength of genetic influence varies across environmental contexts. Existing latent variable methods for estimating G×E interactions in twin and family data specify parametric (typically linear) functions for the interaction effect. An improper functional form may obscure the underlying shape of the interaction effect and may lead to failures to detect a significant interaction. In this article, we introduce a novel approach to the behavior genetic toolkit, local structural equation modeling (LOSEM). LOSEM is a highly flexible nonparametric approach for estimating latent interaction effects across the range of a measured moderator. This approach opens up the ability to detect and visualize new forms of G×E interaction. We illustrate the approach by using LOSEM to estimate gene × socioeconomic status (SES) interactions for six cognitive phenotypes. Rather than continuously and monotonically varying effects as has been assumed in conventional parametric approaches, LOSEM indicated substantial nonlinear shifts in genetic variance for several phenotypes. The operating characteristics of LOSEM were interrogated through simulation studies where the functional form of the interaction effect was known. LOSEM provides a conservative estimate of G×E interaction with sufficient power to detect statistically significant G×E signal with moderate sample size. We offer recommendations for the application of LOSEM and provide scripts for implementing these biometric models in Mplus and in OpenMx under R. PMID:26318287

  1. [Antecedents and consequences of workplace bullying: a longitudinal analysis with a structural equation model].

    Science.gov (United States)

    Carretero Domínguez, Noelia; Gil-Monte, Pedro Rafael; Luciano Devis, Juan Vicente

    2011-11-01

    Most studies focusing on the antecedents and consequences of workplace bullying have used a cross-sectional design, which impedes determining the causality of the relationships. In the present work, we analyzed, by means of structural equation models, the relationship between workplace bullying and some variables that are considered antecedents (interpersonal conflicts, role ambiguity, role conflict, and workplace social support) or consequences (health complaints and inclination to absenteeism from work) of this phenomenon. Multicenter study with two phases. The sample consisted of 696 employees from 66 centers. Workplace bullying was assessed by means of the "Mobbing-UNIPSICO" questionnaire, and the other variables with frequency scales. The cross-sectional models indicated a significant association between role conflict, workplace social support, and workplace bullying in both study periods. Concerning the longitudinal relationships, only workplace social support was a significant predictor of workplace bullying, which, in turn, was a cross-sectional and longitudinal predictor of workers' health complaints. Our results show the mediating effect of workplace bullying between certain work conditions and health complaints, and it is recommendable to replicate these findings in a multi-occupational sample.

  2. Perievent Panic Attack and Depression after the World Trade Center Disaster: A Structural Equation Model Analysis

    Science.gov (United States)

    Adams, Richard E.; Boscarino, Joseph A.

    2011-01-01

    Research suggests that perievent panic attacks – panic attacks in temporal proximity to traumatic events – are predictive of later mental health status, including the onset of depression. Using a community sample of New York City residents interviewed 1 year and 2 years after the World Trade Center Disaster, we estimated a structural equation model (SEM) using pre-disaster psychological status and post-disaster life events, together with psychosocial resources, to assess the relationship between perievent panic and later onset depression. Bivariate results revealed a significant association between perievent panic and both year-1 and year-2 depression. Results for the SEM, however, showed that perievent panic was predictive of year-1 depression, but not year-2 depression, once potential confounders were controlled. Year-2 stressors and year-2 psychosocial resources were the best predictors of year-2 depression onset. Pre-disaster psychological problems were directly implicated in year-1 depression, but not year-2 depression. We conclude that a conceptual model that includes pre- and post-disaster variables best explains the complex causal pathways between psychological status, stressor exposure, perievent panic attacks, and depression onset two years after the World Trade Center attacks. PMID:21957721

  3. Delay equation formulation of a cyclin-structured cell population model

    NARCIS (Netherlands)

    Borges, Ricardo; Calsina, Angel; Cuadrado, Silvia; Diekmann, Odo

    2014-01-01

    The aim of this paper is to derive a system of two renewal equations from individual-level assumptions concerning a cyclin-structured cell population. Nonlinearity arises from the assumption that the rate at which quiescent cells become proliferating is determined by feedback. In fact, we assume tha

  4. Structural Equation Modeling Applied to the Reaction to Stock Dividends and Stock Splits: integrating signaling, liquidity and optimal price level

    Directory of Open Access Journals (Sweden)

    Kelmara Mendes Vieira

    2011-03-01

    Full Text Available This work develops a hybrid model of structural equations able to take simultaneously the hypotheses of signaling, liquidity, and optimal price level to explain the reaction to the stock dividends and stock splits. In the measurement model four constructs were defined: trading activity, spread, size, and price. The structural model defines extant relations from the proposition of 22 sub-hypotheses. A sample of 321 splits performed in the Brazilian market between 1990 and 2004 was used for assessing the model. Confirmatory factor analysis revealed the validity and coherence of the four constructs. The structural model confirmed 9 original sub-hypotheses.

  5. Cognitive processes in university learning: a developmental framework using structural equation modelling.

    Science.gov (United States)

    Phan, Huy P

    2011-09-01

    BACKGROUND. Both achievement goals and study processing strategies theories have been shown to contribute to the prediction of students' academic performance. Existing research studies (Fenollar, Román, & Cuestas, 2007; Liem, Lau, & Nie, 2008; Simons, Dewitte, & Lens, 2004) amalgamating these two theoretical orientations in different causal models have reported their associations with other adaptive strategies and motivational constructs - for example, effort expenditure. Despite this recognition, there have been to date very few studies that explored the relations between achievement goals, study processing strategies, effort, and academic performance over time. AIM OF STUDY. The primary focus of our study is to explore the relations between the aforementioned theoretical constructs over a 2-year period. Specifically, we tested an empirical model that conceptualized the relations between performance-approach and mastery goals, deep processing strategies, effort, and academic performance across six time points of data collection. METHODOLOGY. Two hundred and eighty-one (161 females, 120 males) university students took part in this study. The participants were administered various Likert-scale inventories and the overall course mark and final examination were used as indexes of academic performance. RESULTS. Structural equation modelling indicated a relatively good fit to the a posteriori model and the hypothesized paths were, in part, supported. The major findings included the predictive effects of performance-approach goals at Time 1 on deep processing strategies at Time 2 and mastery goals at Time 3; the predictive effect of mastery goals at Time 3 on effort at Time 4; the predictive effects of deep processing at Time 2 on mastery goals at Time 3 and Time 4. Furthermore, the placement of deep processing and effort in this structural model also accentuated the performance-approach goals - mastery goals - effort - academic performance relation, and the performance

  6. Modelling of the education quality of a high schools in Sumenep Regency using spatial structural equation modelling

    Science.gov (United States)

    Anekawati, Anik; Widjanarko Otok, Bambang; Purhadi; Sutikno

    2017-09-01

    In some cases, education research often involves the latent variables that have a causal relationship as well as a spatial effect. Therefore, it requires a statistical analysis technique called spatial structural equation modelling (spatial SEM). In this research, a spatial SEM was developed to model the quality of education in high schools in Sumenep Regency. This model was improved after the evaluation of an outer and inner model of the model scheme centroid, factor and path since some indicators were not valid. The path scheme model showed better results compared to the other schemes since all of its indicators were valid and its value of R-square increased. Furthermore, only the model of path scheme was tested for spatial effects. The result of the identification test of spatial effects on the inner model using a robust Lagrange multiplier test (using queen contiguity) showed that the education quality model leads to a spatial autoregressive model (SAR in SEM) with a significance level α of 5%, while the model of school infrastructure has no significant spatial effects. The improved model of SAR in SEM, the R2 value obtained was 47.33%, so that it is clear that data variation can be explained by the model of SAR in SEM for the quality of education in high schools.

  7. Species richness and soil properties in Pinus ponderosa forests: A structural equation modeling analysis

    Science.gov (United States)

    Laughlin, D.C.; Abella, S.R.; Covington, W.W.; Grace, J.B.

    2007-01-01

    Question: How are the effects of mineral soil properties on understory plant species richness propagated through a network of processes involving the forest overstory, soil organic matter, soil nitrogen, and understory plant abundance? Location: North-central Arizona, USA. Methods: We sampled 75 0.05-ha plots across a broad soil gradient in a Pinus ponderosa (ponderosa pine) forest ecosystem. We evaluated multivariate models of plant species richness using structural equation modeling. Results: Richness was highest at intermediate levels of understory plant cover, suggesting that both colonization success and competitive exclusion can limit richness in this system. We did not detect a reciprocal positive effect of richness on plant cover. Richness was strongly related to soil nitrogen in the model, with evidence for both a direct negative effect and an indirect non-linear relationship mediated through understory plant cover. Soil organic matter appeared to have a positive influence on understory richness that was independent of soil nitrogen. Richness was lowest where the forest overstory was densest, which can be explained through indirect effects on soil organic matter, soil nitrogen and understory cover. Finally, model results suggest a variety of direct and indirect processes whereby mineral soil properties can influence richness. Conclusions: Understory plant species richness and plant cover in P. ponderosa forests appear to be significantly influenced by soil organic matter and nitrogen, which are, in turn, related to overstory density and composition and mineral soil properties. Thus, soil properties can impose direct and indirect constraints on local species diversity in ponderosa pine forests. ?? IAVS; Opulus Press.

  8. Inferring transcriptional compensation interactions in yeast via stepwise structure equation modeling

    Directory of Open Access Journals (Sweden)

    Wang Woei-Fuh

    2008-03-01

    Full Text Available Abstract Background With the abundant information produced by microarray technology, various approaches have been proposed to infer transcriptional regulatory networks. However, few approaches have studied subtle and indirect interaction such as genetic compensation, the existence of which is widely recognized although its mechanism has yet to be clarified. Furthermore, when inferring gene networks most models include only observed variables whereas latent factors, such as proteins and mRNA degradation that are not measured by microarrays, do participate in networks in reality. Results Motivated by inferring transcriptional compensation (TC interactions in yeast, a stepwise structural equation modeling algorithm (SSEM is developed. In addition to observed variables, SSEM also incorporates hidden variables to capture interactions (or regulations from latent factors. Simulated gene networks are used to determine with which of six possible model selection criteria (MSC SSEM works best. SSEM with Bayesian information criterion (BIC results in the highest true positive rates, the largest percentage of correctly predicted interactions from all existing interactions, and the highest true negative (non-existing interactions rates. Next, we apply SSEM using real microarray data to infer TC interactions among (1 small groups of genes that are synthetic sick or lethal (SSL to SGS1, and (2 a group of SSL pairs of 51 yeast genes involved in DNA synthesis and repair that are of interest. For (1, SSEM with BIC is shown to outperform three Bayesian network algorithms and a multivariate autoregressive model, checked against the results of qRT-PCR experiments. The predictions for (2 are shown to coincide with several known pathways of Sgs1 and its partners that are involved in DNA replication, recombination and repair. In addition, experimentally testable interactions of Rad27 are predicted. Conclusion SSEM is a useful tool for inferring genetic networks, and the

  9. An Analysis of Technology Acceptance in Turkey using Fuzzy Logic and Structural Equation Modelling

    Directory of Open Access Journals (Sweden)

    Bilgin Şenel

    2011-12-01

    Full Text Available Technology is in a constant progress in the way of satisfying increasing human needs. This fact will hold true for the years to come. However, the level of adaptation to technological advancements varies greatly across countries. The pace of adjustment is directly proportional to the importance attached to and the funds allocated for this purpose. Despite the abundance of technological investments in Turkey in recent years, there are only a few studies analyzing the current level of individual interest in technology. This study therefore aims to determine the technology acceptance of Turkish people by using the Technology Acceptance Model (TAM developed by Davis (1989 and to demonstrate the reasons to accept or not accept technology departing from the links between dimensions. While accomplishing this aim, Structural Equation Model (SEM that is a highly strong multivariable analysis technique that makes possible the evaluation of latent structures like psychosocial needs, and the Fuzzy Logic Theorem that provides strong and significant instruments for the measurement of ambiguities and provides the opportunity to meaningfully represent ambiguous concepts expressed in the natural language were used. According to the findings of this study, it was determined that the perceived ease of use is more influential in people’s acceptance of technology than the perceived usefulness is. It was also found that technology acceptance does not differ significantly at the statistical significance level of 0.05 with respect to the participants’ demographic characteristics (age, gender, education level, hometown etc.. In addition, analyses performed to define the relationships between the dimensions of the TAM yielded results that highly supported the TAM. In other words, the dimensions affect technology acceptance to positive and significant degrees

  10. Structural Analysis of Port Brand Equity Using Structural Equation Modeling1

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    Taehwee Lee

    2014-12-01

    Full Text Available Port competition, especially in the Northeast Asia (NEA region, can be described as a price war. In this price competition, it is necessary to build up the brand concept to acquire higher market share. This paper aims to provide structural relationships for port brand equity (PBE and explore the PBE stages statistically. The stages are divided into three steps: port service quality as the precedent of PBE, the PBE dimensions (brand awareness [BA] and brand loyalty [BL], and the antecedent of PBE (overall value of brand equity [OVBE]. From a survey conducted with port users in Korea, the empirical results revealed several significant relationship: between tangibles (TA dimension of port service quality and BL, between the empathy (EMP dimension of port service quality and both BA and BL, and between BA and BL and OVBE. From the empirical analysis, this study suggests both managerial and academic contributions for port managers and scholars for further policy development and research in this important area.

  11. Connecting Athletes’ Self-Perceptions and Metaperceptions of Competence: a Structural Equation Modeling Approach

    Directory of Open Access Journals (Sweden)

    Cecchini Jose A.

    2015-06-01

    Full Text Available This study explored the relationships between athletes’ competence self-perceptions and metaperceptions. Two hundred and fifty one student-athletes (14.26 ± 1.89 years, members of twenty different teams (basketball, soccer completed a questionnaire which included the Perception of Success Questionnaire, the Competence subscale of the Intrinsic Motivation Inventory, and modified versions of both questionnaires to assess athletes’ metaperceptions. Structural equation modelling analysis revealed that athletes’ task and ego metaperceptions positively predicted task and ego self-perceptions, respectively. Competence metaperceptions were strong predictors of competence selfperceptions, confirming the atypical metaperception formation in outcome-dependent contexts such as sport. Task and ego metaperceptions positively predicted athletes’ competence metaperceptions. How coaches value their athletes’ competence is more influential on what the athletes think of themselves than their own self-perceptions. Athletes’ ego and task metaperceptions influenced their competence metaperceptions (how coaches rate their competence. Therefore, athletes build their competence metaperceptions using all information available from their coaches. Finally, only taskself perfections positively predicted athletes’ competence self-perceptions.

  12. Relationships between dimensions of disability experienced by adults living with HIV: a structural equation model analysis.

    Science.gov (United States)

    O'Brien, Kelly K; Davis, Aileen M; Gardner, Sandra; Bayoumi, Ahmed M; Rueda, Sergio; Hart, Trevor A; Cooper, Curtis; Solomon, Patricia; Rourke, Sean B; Hanna, Steven

    2014-02-01

    As individuals age with HIV it is increasingly important to consider the health-related consequences of HIV and multiple morbidities, known as disability. We assessed relationships between four dimensions of disability among adults living with HIV. We conducted a structural equation modeling analysis using data from 913 participants in the Ontario HIV Treatment Network Cohort Study to determine relationships between four latent variables of disability in the Episodic Disability Framework: physical symptoms and impairments, mental health symptoms and impairments, difficulties with day-to-day activities, and challenges to social inclusion. Results indicated that physical symptoms and impairments, mental health symptoms and impairments and difficulties with day-to-day activities directly or indirectly predicted challenges to social inclusion for adults living with HIV. Challenges to social inclusion were directly predicted by mental health symptoms and indirectly by physical health symptoms via (mediated by) having difficulties carrying out day-to-day activities and mental health symptoms and impairments. These findings provide a basis for conceptualizing disability experienced by people living with HIV.

  13. An Empirical Investigation of the Universal Effectiveness of Quality Management Practices: A Structural Equation Modeling Approach

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    Young Sik Cho

    2016-05-01

    Full Text Available Institutional theory argues that the isomorphic nature of quality management (QM practices leads to similar QM implementation and performance among QM-embedded firms. However, contingency theory questions such 'universal effectiveness of QM practices'. Considering these conflicting arguments, this study tests samples from the U.S. and China to examine whether the 'universal effectiveness of QM practices’ across national boundaries actually exists. First, the confirmatory factor analysis was performed to examine the validity of the survey instruments developed in this study. Then, the hypotheses were tested using the structural equation modeling (SEM analysis. The SEM test results indicated that the positive effect of behavioral QM on firm performance was more significant in the U.S. sample than in the China sample. The test results also presented that the relative effect of behavioral QM versus technical QM on firm performance was noticeably different in service firms, according to national economic maturity. The study’s findings demonstrated that a firm's contingency factors, such as national economic maturity and industry type, could result in the heterogeneous implementation of the firm’s TQM program; consequently, the findings weakened the 'universal effectiveness of QM practices'.

  14. Determining rural risk for aneurysmal subarachnoid hemorrhages: A structural equation modeling approach

    Science.gov (United States)

    Nichols, Linda Jayne; Gall, Seana; Stirling, Christine

    2016-01-01

    An aneurysmal subarachnoid hemorrhage (aSAH) carries a high disability burden. The true impact of rurality as a predictor of outcome severity is unknown. Our aim is to clarify the relationship between the proposed explanations of regional and rural health disparities linked to severity of outcome following an aSAH. An initial literature search identified limited data directly linking geographical location, rurality, rural vulnerability, and aSAH. A further search noting parallels with ischemic stroke and acute myocardial infarct literature presented a number of diverse and interrelated predictors. This a priori knowledge informed the development of a conceptual framework that proposes the relationship between rurality and severity of outcome following an aSAH utilizing structural equation modeling. The presented conceptual framework explores a number of system, environmental, and modifiable risk factors. Socioeconomic characteristics, modifiable risk factors, and timely treatment that were identified as predictors of severity of outcome following an aSAH and within each of these defined predictors a number of contributing specific individual predictors are proposed. There are considerable gaps in the current knowledge pertaining to the impact of rurality on the severity of outcome following an aSAH. Absent from the literature is any investigation of the cumulative impact and multiplicity of risk factors associated with rurality. The proposed conceptual framework hypothesizes a number of relationships between both individual level and system level predictors, acknowledging that intervening predictors may mediate the effect of one variable on another. PMID:27695237

  15. Delay Mitigation in the Malaysian Housing Industry: A Structural Equation Modelling Approach

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    Chang Saar Chai

    2015-01-01

    Full Text Available The housing industry is one of the major contributors to the economy in Malaysia due to the constantly high housing demand. The housing demand has increased due to the rapid growth in population and urbanisation in the country. One of the major challenges in the housing industry is the late delivery of housing supply, which in some instances leads to sick and abandoned housing projects. Despite being extensively investigated, th in a negative impact, there is a strong need to review the housing delay mitigation measures practised in Malaysia. This paper aims to evaluate the current delay mitigation measures and its main objective is to explore the relationship between the mitigation measures and delay in housing via a Structural Equation Modelling (SEM approach. A questionnaire survey through an online survey tool was conducted across 13 states and three Federal Territories in Malaysia. The target respondents are the local authorities, developers, consultants (principal submitting persons and contractors. The findings show that 17 predictive, preventive, organisational or corrective. This paper demonstrates that preventive measures are the most influential mitigation measures for housing delivery delay.

  16. A STRUCTURAL EQUATION MODELING OF UNIVERSITY STUDENTS’ SMARTPHONE DEPENDENCE IN AN EMERGING COUNTRY

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    Zafer Aykanat

    2016-09-01

    Full Text Available Smartphone dependence has been emerged as a crucial concern especially for young consumers along with rapid technological advances over the past decades. Better understanding the determinants of smartphone dependence on young consumers may be valuable to decrease compulsive smartphone use in the future. The main objective of this study is to examine the association between smartphone dependence and product features, brand name, product price, social influence and social needs using a Structural Equation Modeling (SEM. For this purpose, a well-established survey was conducted to 411 university students in a north-eastern university of Turkey. The empirical evidence of the present study reveals that there exists a positive relationship between smartphone dependence and social influence and social needs. Results also suggest that product price has a negative impact on smartphone dependence. This study is most probably the first attempt to examine factors affecting smartphone dependence in this specific sample. The results of this study may add value to explain the key drivers of problematic smartphone use in emerging countries.

  17. Food Insecurity and Common Mental Disorders among Ethiopian Youth: Structural Equation Modeling.

    Science.gov (United States)

    Jebena, Mulusew G; Lindstrom, David; Belachew, Tefera; Hadley, Craig; Lachat, Carl; Verstraeten, Roos; De Cock, Nathalie; Kolsteren, Patrick

    2016-01-01

    Although the consequences of food insecurity on physical health and nutritional status of youth living have been reported, its effect on their mental health remains less investigated in developing countries. The aim of this study was to examine the pathways through which food insecurity is associated with poor mental health status among youth living in Ethiopia. We used data from Jimma Longitudinal Family Survey of Youth (JLFSY) collected in 2009/10. A total of 1,521 youth were included in the analysis. We measured food insecurity using a 5-items scale and common mental disorders using the 20-item Self-Reporting Questionnaire (SRQ-20). Structural and generalized equation modeling using maximum likelihood estimation method was used to analyze the data. The prevalence of common mental disorders was 30.8% (95% CI: 28.6, 33.2). Food insecurity was independently associated with common mental disorders (β = 0.323, Pfood insecurity on common mental disorders was direct and only 8.2% of their relationship was partially mediated by physical health. In addition, poor self-rated health (β = 0.285, Pdisorders. Food insecurity is directly associated with common mental disorders among youth in Ethiopia. Interventions that aim to improve mental health status of youth should consider strategies to improve access to sufficient, safe and nutritious food.

  18. [Structural equation model in the study of risk factors in the maintenance of binge eating].

    Science.gov (United States)

    Bastianelli, A; Vicentini, M; Spoto, A; Vidotto, G

    2007-01-01

    This study investigated, in a sample of 483 adolescent girls, a number of risk factors associated with Binge Eating (BE) disorder, i.e. negative feelings, dieting behaviour, social influence and body dissatisfaction. Participants completed the following questionnaires: Bulimia Test, Depression Questionnaire, Dieting Self-Efficacy Measure, Dieting Success, Dieting Status Measure, Dutch Eating Behavior Questionnaire, Eating Disorder Inventory, Positive and Negative Affect Scale Revised, Rosenberg Self-Esteem Scale and Socio-cultural Attitudes Towards Appearance Questionnaire. Structural equation modeling was used in the data analysis to verify the hypothesized relations among the variables, with the aim of identifying the main predictors of BE. This methodology explains the correlation between the considered variables, and determines, using quantitative good fit indexes, both the strength of the correlations and the plausibility of the causal links between the hypothesized factors. Our findings confirm that negative feelings (Negative Affect) are the primary predictor for the maintenance of BE and highlight the significant role played by Social Influence. While Dieting Behaviour is not a primary predictor for the maintenance of BE it appears to influence it through its link with Negative Affect.

  19. Determining rural risk for aneurysmal subarachnoid hemorrhages: A structural equation modeling approach.

    Science.gov (United States)

    Nichols, Linda Jayne; Gall, Seana; Stirling, Christine

    2016-01-01

    An aneurysmal subarachnoid hemorrhage (aSAH) carries a high disability burden. The true impact of rurality as a predictor of outcome severity is unknown. Our aim is to clarify the relationship between the proposed explanations of regional and rural health disparities linked to severity of outcome following an aSAH. An initial literature search identified limited data directly linking geographical location, rurality, rural vulnerability, and aSAH. A further search noting parallels with ischemic stroke and acute myocardial infarct literature presented a number of diverse and interrelated predictors. This a priori knowledge informed the development of a conceptual framework that proposes the relationship between rurality and severity of outcome following an aSAH utilizing structural equation modeling. The presented conceptual framework explores a number of system, environmental, and modifiable risk factors. Socioeconomic characteristics, modifiable risk factors, and timely treatment that were identified as predictors of severity of outcome following an aSAH and within each of these defined predictors a number of contributing specific individual predictors are proposed. There are considerable gaps in the current knowledge pertaining to the impact of rurality on the severity of outcome following an aSAH. Absent from the literature is any investigation of the cumulative impact and multiplicity of risk factors associated with rurality. The proposed conceptual framework hypothesizes a number of relationships between both individual level and system level predictors, acknowledging that intervening predictors may mediate the effect of one variable on another.

  20. Disengaged parenting: Structural equation modeling with child abuse, insecure attachment, and adult symptomatology.

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    Briere, John; Runtz, Marsha; Eadie, Erin; Bigras, Noémie; Godbout, Natacha

    2017-03-09

    Based on attachment theory, we hypothesized that self-reported childhood experiences of disengaged parenting (DP) would predict adults' psychological symptoms even more than, on average, childhood sexual, physical, or psychological abuse. In a large (N=640) university sample, bootstrapped multiple regression analyses indicated that although various forms of child maltreatment were correlated with symptomatology at the univariate level, DP was the primary multivariate predictor. Structural equation modeling indicated significant direct paths from (a) DP to both nonsexual child maltreatment and sexual abuse, (b) DP and nonsexual child maltreatment to insecure attachment, and (c) sexual abuse and insecure attachment to symptomatology. There were significant indirect effects of DP on psychological symptoms through sexual and nonsexual abuse, as well as through attachment. These results suggest that although child abuse has direct and indirect impacts on psychological symptoms, exposure to DP may be especially detrimental, both by increasing the risk of child abuse and by virtue of its impacts on attachment insecurity. They also support the potential use of attachment-oriented intervention in the treatment of adults maltreated as children.

  1. A STRUCTURAL EQUATION MODEL: THAILAND’S INTERNATIONAL TOURISM DEMAND FOR TOURIST DESTINATION

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    CHUKIAT CHAIBOONSRI

    2008-01-01

    Full Text Available Structural equation modelling (LISREL 8 was used to test the causal relationships between tourist travel motivations (travel cost satisfaction and tourist demographics and tourist destination (tourism product, tourism product attributes, and tourism product management. A survey containing Likert-type scales was used in collecting data from 203 international tourists who had travelled to Thailand. Using factor analysis, dimensions were identified for scales used in the study: travel cost satisfaction, tourist demographics, tourism product, tourism product attributes, and tourism product management. Results indicated that the travel cost satisfaction of international tourists had a positive influenced on tourism product attributes at 0.07 (t=1.96 with statistics significant at the level of 0.05. Also the travel cost satisfaction had a positive influence on tourism product management at 0.13 (t=4.02 with statistics significant at the level of 0.05. And the tourist demographics had a positive influenced on tourism product at 0.11(t=3.47 with statistic significant at the level of 0.05. As well as tourist demographics, which had a positive influenced on tourism management at 0.11 (t=3.57 with statistics significant at the level of 0.05. The results of the research suggested that if the tourist destinations in Thailand are improved in quality then not only will international tourist revisit Thailand but also the numbers of tourists travelling to Thailand will increase.

  2. Contextual Factors Affecting the Innovation Performance of Manufacturing SMEs in Korea: A Structural Equation Modeling Approach

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    Ye Seul Choi

    2017-07-01

    Full Text Available This study empirically explores the relationship between innovation performance and the internal and contextual factors driving technological innovation in manufacturing small and medium-sized enterprises (SMEs in metropolitan areas of Korea using structural equation modeling (SEM. Our analysis is based on firm-level data from the Korean Innovation Survey conducted by the Science and Technology Policy Institute in 2012. According to the results, SMEs’ innovation capacity was positively related to technological innovation performance, and SMEs’ skills and technology acquisition is a contextual factor that positively influences their innovation performance. In this process, SMEs’ innovation capacity is a partial mediator between skills and technology acquisition and SMEs’ technological innovation performance. Moreover, the results show that the relationship between government and public policies and SMEs’ innovation performance is mediated by SMEs’ internal innovation capacity. The results imply that both skills and technology acquisition and government and public policies are important contextual factors can increase SMEs’ innovation performance. Based on the results, this study provides implications for policy makers in terms of the policies that provide both direct and support roles in fostering and sustaining innovation, which drives regional economic growth and development.

  3. "Great expectations" of adoptive parents: theory extension through structural equation modeling.

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    Foli, Karen J; Lim, Eunjung; South, Susan C; Sands, Laura P

    2014-01-01

    Most of the 2 million adoptive parents in the United States make the transition to parenting successfully. Adoptive parents who do not make the transition easily may put their children at risk for negative outcomes. The aim of this study was to further refine Foli's midrange theory of postadoption depression, which postulates that fulfillment of expectations is a principal contributor to parental emotional health status, aggravation, and bonding. The linked dataset (National Survey of Children's Health and National Survey of Adoptive Parents) was used for structural equation modeling. The sample consisted of 1,426 parents with adopted children who had been placed in the home more than 2 years before survey completion. Special services and child's behaviors were direct determinants of parental expectations, and parental expectations were direct determinants of parental aggravation and parentalbonding. As anticipated, parental expectations served as a mediator between child-related variables and parental outcomes. A path was also found between child's behaviors and special services and parental emotional health status. Child's past trauma was also associated with parental bonding. Parental expectations showed direct relationships with the latent variables of parental aggravation and bonding. Future research should examine factors associated with early transition when children have been in the adoptive home less than 2 years and include specific expectations held by parents.

  4. Analyzing Factors Influencing Teaching as a Career Choice Using Structural Equation Modeling

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    Budhinath Padhy

    2015-02-01

    Full Text Available The purpose of the study is to analyze factors influencing students’ perceptions of teaching as a career choice using structural equation modeling with the goal of shaping a teacher education recruitment program. In this study, 458 students from a Midwestern university in the United States responded to an online survey about career-related factors they value, their expectation that teaching would offer those factors, and any social-influence factors that might encourage them to choose a teaching career. The effect of 10 exogenous motivation variables (value-environment, value-intrinsic, value-extrinsic, value-altruistic, expectancy-environment, expectancy-intrinsic, expectancy-extrinsic, social-media-education, social-prior-experience, and social-suggestions on choosing a teaching career was examined. Results of our analysis showed that the factors related to expectancy-environment, expectancy-intrinsic, social-media-education, social-prior-experience, and social-suggestions were found to be significant, whereas value-related factors and expectancy-extrinsic factors were found to be insignificant.

  5. Structural equation modeling of factors contributing to quality of life in Japanese patients with multiple sclerosis

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    Kikuchi Hiromi

    2013-01-01

    Full Text Available Abstract Background To improve quality of life (QOL in patients with multiple sclerosis (MS, it is important to decrease disability and prevent relapse. The aim of this study was to examine the causal and mutual relationships contributing to QOL in Japanese patients with MS, develop path diagrams, and explore interventions with the potential to improve patient QOL. Methods Data of 163 Japanese MS patients were obtained using the Functional Assessment of MS (FAMS and Nottingham Adjustment Scale-Japanese version (NAS-J tests, as well as four additional factors that affect QOL (employment status, change of income, availability of disease information, and communication with medical staff. Data were then used in structural equation modeling to develop path diagrams for factors contributing to QOL. Results The Expanded Disability Status Scale (EDSS score had a significant effect on the total FAMS score. Although EDSS negatively affected the FAMS symptom score, NAS-J subscale scores of anxiety/depression and acceptance were positively related to the FAMS symptom score. Changes in employment status after MS onset negatively affected all NAS-J scores. Knowledge of disease information improved the total NAS-J score, which in turn improved many FAMS subscale scores. Communication with doctors and nurses directly and positively affected some FAMS subscale scores. Conclusions Disability and change in employment status decrease patient QOL. However, the present findings suggest that other factors, such as acquiring information on MS and communicating with medical staff, can compensate for the worsening of QOL.

  6. Structural equation modeling of factors contributing to quality of life in Japanese patients with multiple sclerosis.

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    Kikuchi, Hiromi; Mifune, Nobuhiro; Niino, Masaaki; Kira, Jun-Ichi; Kohriyama, Tatsuo; Ota, Kohei; Tanaka, Masami; Ochi, Hirofumi; Nakane, Shunya; Kikuchi, Seiji

    2013-01-22

    To improve quality of life (QOL) in patients with multiple sclerosis (MS), it is important to decrease disability and prevent relapse. The aim of this study was to examine the causal and mutual relationships contributing to QOL in Japanese patients with MS, develop path diagrams, and explore interventions with the potential to improve patient QOL. Data of 163 Japanese MS patients were obtained using the Functional Assessment of MS (FAMS) and Nottingham Adjustment Scale-Japanese version (NAS-J) tests, as well as four additional factors that affect QOL (employment status, change of income, availability of disease information, and communication with medical staff). Data were then used in structural equation modeling to develop path diagrams for factors contributing to QOL. The Expanded Disability Status Scale (EDSS) score had a significant effect on the total FAMS score. Although EDSS negatively affected the FAMS symptom score, NAS-J subscale scores of anxiety/depression and acceptance were positively related to the FAMS symptom score. Changes in employment status after MS onset negatively affected all NAS-J scores. Knowledge of disease information improved the total NAS-J score, which in turn improved many FAMS subscale scores. Communication with doctors and nurses directly and positively affected some FAMS subscale scores. Disability and change in employment status decrease patient QOL. However, the present findings suggest that other factors, such as acquiring information on MS and communicating with medical staff, can compensate for the worsening of QOL.

  7. Structural equation modeling of factors contributing to quality of life in Japanese patients with multiple sclerosis

    Science.gov (United States)

    2013-01-01

    Background To improve quality of life (QOL) in patients with multiple sclerosis (MS), it is important to decrease disability and prevent relapse. The aim of this study was to examine the causal and mutual relationships contributing to QOL in Japanese patients with MS, develop path diagrams, and explore interventions with the potential to improve patient QOL. Methods Data of 163 Japanese MS patients were obtained using the Functional Assessment of MS (FAMS) and Nottingham Adjustment Scale-Japanese version (NAS-J) tests, as well as four additional factors that affect QOL (employment status, change of income, availability of disease information, and communication with medical staff). Data were then used in structural equation modeling to develop path diagrams for factors contributing to QOL. Results The Expanded Disability Status Scale (EDSS) score had a significant effect on the total FAMS score. Although EDSS negatively affected the FAMS symptom score, NAS-J subscale scores of anxiety/depression and acceptance were positively related to the FAMS symptom score. Changes in employment status after MS onset negatively affected all NAS-J scores. Knowledge of disease information improved the total NAS-J score, which in turn improved many FAMS subscale scores. Communication with doctors and nurses directly and positively affected some FAMS subscale scores. Conclusions Disability and change in employment status decrease patient QOL. However, the present findings suggest that other factors, such as acquiring information on MS and communicating with medical staff, can compensate for the worsening of QOL. PMID:23339479

  8. Association of father involvement and neighborhood quality with kindergartners' physical activity: a multilevel structural equation model.

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    Beets, Michael W; Foley, John T

    2008-01-01

    Examine the effects of father-child involvement and neighborhood characteristics with young children's physical activity (PA) within a multilevel framework. Cross-sectional analysis of the Early Childhood Longitudinal Study-Kindergarten Cohort 1998. Nationally representative sample. Data were available for 10,694 kindergartners (5-6 years; 5240 girls) living in 1053 neighborhoods. Parental report of child's PA level, father characteristics (e.g., time spent with child, age, education, socioeconomic status, hours worked), family time spent doing sports/ activities together, and neighborhood quality (e.g., safety, presence of crime violence, garbage). Child weight status, motor skills, ethnicity, and television viewing were used as covariates. Multilevel structural equation modeling with children nested within neighborhoods. At the child level father-child time and family time doing sports together were positively associated with children's PA. At the neighborhood level parental perception of a neighborhood's safety for children to play outside fully mediated the effect of neighborhood quality on children's PA. Overall 19.1% and 7.6% of the variance in PA was explained at the child and neighborhood levels, respectively. Family-based interventions for PA should consider father-child time, with this contributing to a child's overall PA level. Further, neighborhood quality is an important predictor of PA only to the extent by which parents perceive it to be unsafe for their child to play outdoors.

  9. Food Insecurity and Common Mental Disorders among Ethiopian Youth: Structural Equation Modeling

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    Lindstrom, David; Belachew, Tefera; Hadley, Craig; Lachat, Carl; Verstraeten, Roos; De Cock, Nathalie; Kolsteren, Patrick

    2016-01-01

    Background Although the consequences of food insecurity on physical health and nutritional status of youth living have been reported, its effect on their mental health remains less investigated in developing countries. The aim of this study was to examine the pathways through which food insecurity is associated with poor mental health status among youth living in Ethiopia. Methods We used data from Jimma Longitudinal Family Survey of Youth (JLFSY) collected in 2009/10. A total of 1,521 youth were included in the analysis. We measured food insecurity using a 5-items scale and common mental disorders using the 20-item Self-Reporting Questionnaire (SRQ-20). Structural and generalized equation modeling using maximum likelihood estimation method was used to analyze the data. Results The prevalence of common mental disorders was 30.8% (95% CI: 28.6, 33.2). Food insecurity was independently associated with common mental disorders (β = 0.323, Pfood insecurity on common mental disorders was direct and only 8.2% of their relationship was partially mediated by physical health. In addition, poor self-rated health (β = 0.285, PFood insecurity is directly associated with common mental disorders among youth in Ethiopia. Interventions that aim to improve mental health status of youth should consider strategies to improve access to sufficient, safe and nutritious food. PMID:27846283

  10. Emotion dysregulation mediates the relationship between child maltreatment and psychopathology: A structural equation model.

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    Jennissen, Simone; Holl, Julia; Mai, Hannah; Wolff, Sebastian; Barnow, Sven

    2016-12-01

    The present study investigated the mediating effects of emotion dysregulation on the relationship between child maltreatment and psychopathology. An adult sample (N=701) from diverse backgrounds of psychopathology completed the Childhood Trauma Questionnaire (CTQ), the Difficulties in Emotion Regulation Scale (DERS), the Brief Symptom Inventory (BSI), and the negative affect subscale of the Positive and Negative Affect Schedule (PANAS) in a cross-sectional online survey. Correlational analyses showed that all types of child maltreatment were uniformly associated with emotion dysregulation, and dimensions of emotion dysregulation were strongly related to psychopathology. Limited access to strategies for emotion regulation emerged as the most powerful predictor. Structural equation modeling analyses revealed that emotion dysregulation partially mediated the relationship between child maltreatment and psychopathology, even after controlling for shared variance with negative affect. These findings emphasize the importance of emotion dysregulation as a possible mediating mechanism in the association between child maltreatment and later psychopathology. Additionally, interventions targeting specific emotion regulation strategies may be effective to reduce psychopathology in victims of child maltreatment.

  11. Relation between body mass index and depression: a structural equation modeling approach

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    Akhtar-Danesh Noori

    2007-04-01

    Full Text Available Abstract Background Obesity and depression are two major diseases which are associated with many other health problems such as hypertension, dyslipidemia, diabetes mellitus, coronary heart disease, stroke, myocardial infarction, heart failure in patients with systolic hypertension, low bone mineral density and increased mortality. Both diseases share common health complications but there are inconsistent findings concerning the relationship between obesity and depression. In this work we used the structural equation modeling (SEM technique to examine the relation between body mass index (BMI, as a proxy for obesity, and depression using the Canadian Community Health Survey, Cycle 1.2. Methods In this SEM model we postulate that 1 BMI and depression are directly related, 2 BMI is directly affected by the physical activity and, 3depression is directly influenced by stress. SEM was also used to assess the relation between BMI and depression separately for males and females. Results The results indicate that higher BMI is associated with more severe form of depression. On the other hand, the more severe form of depression may result in less weight gain. However, the association between depression and BMI is gender dependent. In males, the higher BMI may result in a more severe form of depression while in females the relation may not be the same. Also, there was a negative relationship between physical activity and BMI. Conclusion In general, use of SEM method showed that the two major diseases, obesity and depression, are associated but the form of the relation is different among males and females. More research is necessary to further understand the complexity of the relationship between obesity and depression. It also demonstrated that SEM is a feasible technique for modeling the relation between obesity and depression.

  12. Examining the link between patient satisfaction and adherence to HIV care: a structural equation model.

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    Dang, Bich N; Westbrook, Robert A; Black, William C; Rodriguez-Barradas, Maria C; Giordano, Thomas P

    2013-01-01

    Analogous to the business model of customer satisfaction and retention, patient satisfaction could serve as an innovative, patient-centered focus for increasing retention in HIV care and adherence to HAART, and ultimately HIV suppression. To test, through structural equation modeling (SEM), a model of HIV suppression in which patient satisfaction influences HIV suppression indirectly through retention in HIV care and adherence to HAART. We conducted a cross-sectional study of adults receiving HIV care at two clinics in Texas. Patient satisfaction was based on two validated items, one adapted from the Consumer Assessment of Healthcare Providers and Systems survey ("Would you recommend this clinic to other patients with HIV?) and one adapted from the Delighted-Terrible Scale, ("Overall, how do you feel about the care you got at this clinic in the last 12 months?"). A validated, single-item question measured adherence to HAART over the past 4 weeks. Retention in HIV care was based on visit constancy in the year prior to the survey. HIV suppression was defined as plasma HIV RNA survey. We used SEM to test hypothesized relationships. The analyses included 489 patients (94% of eligible patients). The patient satisfaction score had a mean of 8.5 (median 9.2) on a 0- to 10- point scale. A total of 46% reported "excellent" adherence, 76% had adequate retention, and 70% had HIV suppression. In SEM analyses, patient satisfaction with care influences retention in HIV care and adherence to HAART, which in turn serve as key determinants of HIV suppression (all psatisfaction may have direct effects on retention in HIV care and adherence to HAART. Interventions to improve the care experience, without necessarily targeting objective clinical performance measures, could serve as an innovative method for optimizing HIV outcomes.

  13. A Model and Questionnaire of Language Identity in Iran: A Structural Equation Modelling Approach

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    Khatib, Mohammad; Rezaei, Saeed

    2013-01-01

    This study consisted of three main phases including the development of a hypothesised model of language identity in Iran, developing and validating a questionnaire based on this model and finally testing the model based on the questionnaire data. In the first phase of this research, a hypothesised model of language identity in Iran was developed…

  14. A structural equation modelling approach to explore the determinants of quality of life in schizophrenia.

    Science.gov (United States)

    Alessandrini, Marine; Lançon, Christophe; Fond, Guillaume; Faget-Agius, Catherine; Richieri, Raphaelle; Faugere, Melanie; Metairie, Emeline; Boucekine, Mohamed; Llorca, Pierre-Michel; Auquier, Pascal; Boyer, Laurent

    2016-03-01

    This study aimed to analyse the relationships among psychotic symptoms, depression, neurocognition and functioning as determinants of quality of life (QoL) in patients with schizophrenia. In this cross-sectional study, we evaluated QoL with the Schizophrenia Quality of Life 18-item scale (S-QoL 18), neurocognition with multiple tests exploring memory, attention and executive functions, the severity of psychotic symptoms with the Positive and Negative Syndrome Scale (PANSS), depression with the Calgary Depression Scale for Schizophrenia (CDSS) and functioning using the Functional Remission Of General Schizophrenia (FROGS) scale. We used Structural Equation Modelling (SEM) to describe the relationships among the severity of psychotic symptoms, depression, neurocognition, functioning and QoL. Two hundred and seventy-one outpatients with schizophrenia participated in our study. SEM showed good fit with χ(2)/df=1.97, root mean square error of approximation=0.06, comparative fit index=0.93 and standardized root mean square residuals=0.05. This model revealed that depression was the most important feature associated with QoL, mainly for the self-esteem, autonomy and resilience dimensions (direct path coefficient=-0.46). The direct path between functioning and QoL was also significant (path coefficient=0.26). The severity of psychotic symptoms and neurocognitive impairment were weakly and indirectly associated with QoL via functioning (path coefficients=-0.18 and 0.04, respectively). This study contributes to a better understanding of the determinants of QoL in schizophrenia. Our findings should be considered in developing effective strategies for improving QoL among this population. Copyright © 2016 Elsevier B.V. All rights reserved.

  15. Smart Phone Acceptance among Physicians: Application of Structural Equation Modelling in the Largest Iranian University.

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    Nematollahi, M; Faghiri, K; Barati, O; Bastani, P

    2017-03-01

    The present study aimed to determine attitudes and effective factors in the acceptance of smart phones by physicians of the largest University of Medical Sciences in the south of Iran. This cross-sectional study was performed using Structural Equation Modelling (SEM) in 2014. Study participants included 200 physicians working in the hospitals of Shiraz University of Medical Sciences selected through two-stage stratified sampling, but 185 participants completed the study. The study data were collected using a researcher-made questionnaire completed through a 5-point Likert scale. The content validity of the questionnaire was confirmed by a panel of experts, its construct validity by confirmatory factor analysis, and its reliability by Cronbach's alpha of 0.802. All data analyses were performed using SPSS (version 22) and LISREL (version 8.8). Results showed that most physicians had a desirable attitude towards using smart phones. Besides, the results of SEM indicated a significant relationship between attitude and compatibility, observability, personal experience, voluntariness of use and perceived usefulness. Moreover, some important fitness indices revealed appropriate fitness of the study model (p=0.26, X2/df=1.35, RMR=0.070, GFI=0.77, AGFI=0.71, NNFI=0.93, CFI=0.94). The results revealed that compatibility, observability, personal experience, voluntariness of use and perceived usefulness were effective in the physicians' attitude towards using smart phones. Thus, by preparation of the required infrastructures, policymakers in the field of health technology can enhance the utilization of smart phones in hospitals.

  16. A structural equation model analysis of postfire plant diversity in California shrublands

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    Grace, J.B.; Keeley, J.E.

    2006-01-01

    This study investigates patterns of plant diversity following wildfires in fire-prone shrublands of California, seeks to understand those patterns in terms of both local and landscape factors, and considers the implications for fire management. Ninety study sites were established following extensive wildfires in 1993, and 1000-m2 plots were used to sample a variety of parameters. Data on community responses were collected for five years following fire. Structural equation modeling (SEM) was used to relate plant species richness to plant abundance, fire severity, abiotic conditions, within-plot heterogeneity, stand age, and position in the landscape. Temporal dynamics of average richness response was also modeled. Richness was highest in the first year following fire, indicating postfire enhancement of diversity. A general decline in richness over time was detected, with year-to-year variation attributable to annual variations in precipitation. Peak richness in the landscape was found where (1) plant abundance was moderately high, (2) within-plot heterogeneity was high, (3) soils were moderately low in nitrogen, high in sand content, and with high rock cover, (4) fire severity was low, and (5) stands were young prior to fire. Many of these characteristics were correlated with position in the landscape and associated conditions. We infer from the SEM results that postfire richness in this system is strongly influenced by local conditions and that these conditions are, in turn, predictably related to landscape-level conditions. For example, we observed that older stands of shrubs were characterized by more severe fires, which were associated with a low recovery of plant cover and low richness. These results may have implications for the use of prescribed fire in this system if these findings extrapolate to prescribed burns as we would expect. ?? 2006 by the Ecological Society of America.

  17. Neurocognition, insight and medication nonadherence in schizophrenia: a structural equation modeling approach.

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    Laurent Boyer

    Full Text Available OBJECTIVE: The aim of this study was to examine the complex relationships among neurocognition, insight and nonadherence in patients with schizophrenia. METHODS: DESIGN: Cross-sectional study. INCLUSION CRITERIA: Diagnosis of schizophrenia according to the DSM-IV-TR criteria. DATA COLLECTION: Neurocognition was assessed using a global approach that addressed memory, attention, and executive functions; insight was analyzed using the multidimensional 'Scale to assess Unawareness of Mental Disorder;' and nonadherence was measured using the multidimensional 'Medication Adherence Rating Scale.' ANALYSIS: Structural equation modeling (SEM was applied to examine the non-straightforward relationships among the following latent variables: neurocognition, 'awareness of positive symptoms' and 'negative symptoms', 'awareness of mental disorder' and nonadherence. RESULTS: One hundred and sixty-nine patients were enrolled. The final testing model showed good fit, with normed χ(2 = 1.67, RMSEA = 0.063, CFI = 0.94, and SRMR = 0.092. The SEM revealed significant associations between (1 neurocognition and 'awareness of symptoms,' (2 'awareness of symptoms' and 'awareness of mental disorder' and (3 'awareness of mental disorder' and nonadherence, mainly in the 'attitude toward taking medication' dimension. In contrast, there were no significant links between neurocognition and nonadherence, neurocognition and 'awareness of mental disorder,' and 'awareness of symptoms' and nonadherence. CONCLUSIONS: Our findings support the hypothesis that neurocognition influences 'awareness of symptoms,' which must be integrated into a higher level of insight (i.e., the 'awareness of mental disorder' to have an impact on nonadherence. These findings have important implications for the development of effective strategies to enhance medication adherence.

  18. Inference of gene regulatory networks with sparse structural equation models exploiting genetic perturbations.

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    Xiaodong Cai

    Full Text Available Integrating genetic perturbations with gene expression data not only improves accuracy of regulatory network topology inference, but also enables learning of causal regulatory relations between genes. Although a number of methods have been developed to integrate both types of data, the desiderata of efficient and powerful algorithms still remains. In this paper, sparse structural equation models (SEMs are employed to integrate both gene expression data and cis-expression quantitative trait loci (cis-eQTL, for modeling gene regulatory networks in accordance with biological evidence about genes regulating or being regulated by a small number of genes. A systematic inference method named sparsity-aware maximum likelihood (SML is developed for SEM estimation. Using simulated directed acyclic or cyclic networks, the SML performance is compared with that of two state-of-the-art algorithms: the adaptive Lasso (AL based scheme, and the QTL-directed dependency graph (QDG method. Computer simulations demonstrate that the novel SML algorithm offers significantly better performance than the AL-based and QDG algorithms across all sample sizes from 100 to 1,000, in terms of detection power and false discovery rate, in all the cases tested that include acyclic or cyclic networks of 10, 30 and 300 genes. The SML method is further applied to infer a network of 39 human genes that are related to the immune function and are chosen to have a reliable eQTL per gene. The resulting network consists of 9 genes and 13 edges. Most of the edges represent interactions reasonably expected from experimental evidence, while the remaining may just indicate the emergence of new interactions. The sparse SEM and efficient SML algorithm provide an effective means of exploiting both gene expression and perturbation data to infer gene regulatory networks. An open-source computer program implementing the SML algorithm is freely available upon request.

  19. Smart Phone Acceptance among Physicians: Application of Structural Equation Modelling in the Largest Iranian University

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    Nematollahi M.

    2017-03-01

    Full Text Available Background: The present study aimed to determine attitudes and effective factors in the acceptance of smart phones by physicians of the largest University of Medical Sciences in the south of Iran. Methods: This cross-sectional study was performed using Structural Equation Modelling (SEM in 2014. Study participants included 200 physicians working in the hospitals of Shiraz University of Medical Sciences selected through two-stage stratified sampling, but 185 participants completed the study. The study data were collected using a researcher-made questionnaire completed through a 5-point Likert scale. The content validity of the questionnaire was confirmed by a panel of experts, its construct validity by confirmatory factor analysis, and its reliability by Cronbach’s alpha of 0.802. All data analyses were performed using SPSS (version 22 and LISREL (version 8.8. Results: Results showed that most physicians had a desirable attitude towards using smart phones. Besides, the results of SEM indicated a significant relationship between attitude and compatibility, observability, personal experience, voluntariness of use and perceived usefulness. Moreover, some important fitness indices revealed appropriate fitness of the study model (p=0.26, X2 /df=1.35, RMR=0.070, GFI=0.77, AGFI=0.71, NNFI=0.93, CFI=0.94. Conclusion: The results revealed that compatibility, observability, personal experience, voluntariness of use and perceived usefulness were effective in the physicians’ attitude towards using smart phones. Thus, by preparation of the required infrastructures, policymakers in the field of health technology can enhance the utilization of smart phones in hospitals.

  20. Modeling of Structural Equation Teachers’ Job satisfaction in Agricultural High School, Mazandaran Province, Iran

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    M. Alikhani Dadoukolaei

    2015-05-01

    Full Text Available Job satisfaction is a positive or pleasant emotional state resulting from a person’s appreciation of his/her own job or experience. The study purpose was to model job satisfaction for teachers working in Agricultural institutes within Mazandaran province of Iran. The study used a descriptive-correlative design . The statistical population (including all instructors working for agricultural Institutes within Mazandaran Province of Iran was es 127 teachers. Using Cochran’s formula, the sample size was estimated at 85 teachers. To increase the viability of the study, the planned sample size was determined att 110 teachers from which 108 teachers completed the questionnaires. The study was conducted using questionnaire. The content validity of the questionnaire was assessed by a group of extension specialists. In order to measure the reliability of research questionnaires, 29 teachers who were randomly selected. completed some questionnaires. Cronbach's alpha, ordinal theta and combination reliability were calculated by 0.95, 0.92 and 0.87 respectively. The results indicate that the magnitude of job satisfaction for %85.2 of instructors working in Agricultural institutes within Mazandaran province was moderate and relatively high. Based on the estimated Structural equation model, the highest effect on the job satisfaction was related to the environmental factor with the path coefficient of 0.64. Motivational factor with the path coefficient of 0.26 had a significant effect on job satisfaction. In addition, the environmental factor with the path coefficient of 0.55 had a significant effect on the Motivational factor.

  1. The Internal Structure of Responses to the Trait Emotional Intelligence Questionnaire-Short Form: An Exploratory Structural Equation Modeling Approach.

    Science.gov (United States)

    Perera, Harsha N

    2015-01-01

    Notwithstanding the wide use of the Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF) as a brief assessment of trait emotional intelligence (TEI), the psychometric properties of this measure have not been systematically examined. This article reports on research conducted to evaluate the latent structure underlying TEIQue-SF item data and test the gender invariance of scores as critical initial steps in determining the psychometric robustness of the inventory. In doing so, the article demonstrates an application of exploratory structural equation modeling as an alternative to the more restrictive independent clusters model of confirmatory factor analysis for examining factorially complex personality data. On the basis of 476 responses to the TEIQue-SF, evidence was obtained for the multidimensionality of the inventory reflected in a retained correlated traits solution. Tests of gender invariance revealed equivalence of item factor loadings, intercepts, uniquenesses, correlated uniquenesses, and the factor variance-covariance matrix, but not latent means. Men were found to be moderately higher on self-control and sociability than women, whereas women scored marginally higher on emotionality than men. No significant gender differences were found on mean levels of well-being. The benefits of the multidimensionality of the TEIQue-SF, limitations of the study, and directions for future research are discussed.

  2. Are Teachers' Approaches to Teaching Responsive to Individual Student Variation? A Two-Level Structural Equation Modeling

    Science.gov (United States)

    Rosário, Pedro; Núñez, José Carlos; Vallejo, Guilermo; Paiva, Olímpia; Valle, António; Fuentes, Sonia; Pinto, Ricardo

    2014-01-01

    In the framework of teacher's approaches to teaching, this study investigates the relationship between student-related variables (i.e., study time, class absence, domain knowledge, and homework completion), students' approaches to learning, and teachers' approaches to teaching using structural equation modeling (SEM) with two…

  3. Pathways of inhalation exposure to manganese in children living near a ferromanganese refinery: A structural equation modeling approach

    Science.gov (United States)

    Manganese (Mn) is both essential element and neurotoxicant. Exposure to Mn can occur from various sources and routes. Structural equation modeling was used to examine routes of exposure to Mn among children residing near a ferromanganese refinery in Marietta, Ohio. An inhalation ...

  4. Study of Factors Preventing Children from Enrolment in Primary School in the Republic of Honduras: Analysis Using Structural Equation Modelling

    Science.gov (United States)

    Ashida, Akemi

    2015-01-01

    Studies have investigated factors that impede enrolment in Honduras. However, they have not analysed individual factors as a whole or identified the relationships among them. This study used longitudinal data for 1971 children who entered primary schools from 1986 to 2000, and employed structural equation modelling to examine the factors…

  5. Socioeconomic Status and Asian American and Pacific Islander Students' Transition to College: A Structural Equation Modeling Analysis

    Science.gov (United States)

    Museus, Samuel D.; Vue, Rican

    2013-01-01

    The purpose of this study is to examine socioeconomic differences in the interpersonal factors that influence college access among Asian Americans and Pacific Islanders (AAPIs). Data on 1,460 AAPIs from the Education Longitudinal Study (ELS: 02/06) were analyzed using structural equation modeling techniques. Findings suggest that parental…

  6. Maximum Likelihood Methods in Treating Outliers and Symmetrically Heavy-Tailed Distributions for Nonlinear Structural Equation Models with Missing Data

    Science.gov (United States)

    Lee, Sik-Yum; Xia, Ye-Mao

    2006-01-01

    By means of more than a dozen user friendly packages, structural equation models (SEMs) are widely used in behavioral, education, social, and psychological research. As the underlying theory and methods in these packages are vulnerable to outliers and distributions with longer-than-normal tails, a fundamental problem in the field is the…

  7. Are Teachers' Approaches to Teaching Responsive to Individual Student Variation? A Two-Level Structural Equation Modeling

    Science.gov (United States)

    Rosário, Pedro; Núñez, José Carlos; Vallejo, Guilermo; Paiva, Olímpia; Valle, António; Fuentes, Sonia; Pinto, Ricardo

    2014-01-01

    In the framework of teacher's approaches to teaching, this study investigates the relationship between student-related variables (i.e., study time, class absence, domain knowledge, and homework completion), students' approaches to learning, and teachers' approaches to teaching using structural equation modeling (SEM) with two…

  8. A Theoretical Investigation of the Relationship between Structural Equation Modeling and Partial Correlation in Functional MRI Effective Connectivity

    Directory of Open Access Journals (Sweden)

    Guillaume Marrelec

    2009-01-01

    evidence. In this paper, we provide theoretical fundaments explaining why and in what measure structural equation modeling and partial correlations are related. This gives better insight regarding what parts of SEM can be retrieved by partial correlation analysis and what remains inaccessible. We illustrate the different results with real data.

  9. Pathways of inhalation exposure to manganese in children living near a ferromanganese refinery: A structural equation modeling approach

    Science.gov (United States)

    Manganese (Mn) is both essential element and neurotoxicant. Exposure to Mn can occur from various sources and routes. Structural equation modeling was used to examine routes of exposure to Mn among children residing near a ferromanganese refinery in Marietta, Ohio. An inhalation ...

  10. Structural equation modeling of the proximal–distal continuum of adherence drivers

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    McHorney CA

    2012-11-01

    Full Text Available Colleen A McHorney,1 Ning Jackie Zhang,2 Timothy Stump,3 Xiaoquan Zhao41US Outcomes Research, Merck, North Wales, PA, 2University of Central Florida, Orlando, 3Indiana University School of Medicine, Indianapolis, 4George Mason University, Fairfax, USAObjectives: Nonadherence to prescription medications has been shown to be significantly influenced by three key medication-specific beliefs: patients' perceived need for the prescribed medication, their concerns about the prescribed medication, and perceived medication affordability. Structural equation modeling was used to test the predictors of these three proximal determinants of medication adherence using the proximal–distal continuum of adherence drivers as the organizing conceptual framework.Methods: In Spring 2008, survey participants were selected from the Harris Interactive Chronic Illness Panel, an internet-based panel of hundreds of thousands of adults with chronic disease. Respondents were eligible for the survey if they were aged 40 years and older, resided in the US, and reported having at least one of six chronic diseases: asthma, diabetes, hyperlipidemia, hypertension, osteoporosis, or other cardiovascular disease. A final sample size of 1072 was achieved. The proximal medication beliefs were measured by three multi-item scales: perceived need for medications, perceived medication concerns, and perceived medication affordability. The intermediate sociomedical beliefs and skills included four multi-item scales: perceived disease severity, knowledge about the prescribed medication, perceived immunity to side effects, and perceived value of nutraceuticals. Generic health beliefs and skills consisted of patient engagement in their care, health information-seeking tendencies, internal health locus of control, a single-item measure of self-rated health, and general mental health. Structural equation modeling was used to model proximal–distal continuum of adherence drivers.Results: The

  11. Analyzing Latent State-Trait and Multiple-Indicator Latent Growth Curve Models as Multilevel Structural Equation Models

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    Christian eGeiser

    2013-12-01

    Full Text Available Latent state-trait (LST and latent growth curve (LGC models are frequently used in the analysis of longitudinal data. Although it is well-known that standard single-indicator LGC models can be analyzed within either the structural equation modeling (SEM or multilevel (ML; hierarchical linear modeling frameworks, few researchers realize that LST and multivariate LGC models, which use multiple indicators at each time point, can also be specified as ML models. In the present paper, we demonstrate that using the ML-SEM rather than the SL-SEM framework to estimate the parameters of these models can be practical when the study involves (1 a large number of time points, (2 individually-varying times of observation, (3 unequally spaced time intervals, and/or (4 incomplete data. Despite the practical advantages of the ML-SEM approach under these circumstances, there are also some limitations that researchers should consider. We present an application to an ecological momentary assessment study (N = 158 youths with an average of 23.49 observations of positive mood per person using the software Mplus (Muthén & Muthén, 1998-2012 and discuss advantages and disadvantages of using the ML-SEM approach to estimate the parameters of LST and multiple-indicator LGC models.

  12. The assessment of the performance of covariance-based structural equation modeling and partial least square path modeling

    Science.gov (United States)

    Aimran, Ahmad Nazim; Ahmad, Sabri; Afthanorhan, Asyraf; Awang, Zainudin

    2017-05-01

    Structural equation modeling (SEM) is the second generation statistical analysis technique developed for analyzing the inter-relationships among multiple variables in a model. Previous studies have shown that there seemed to be at least an implicit agreement about the factors that should drive the choice between covariance-based structural equation modeling (CB-SEM) and partial least square path modeling (PLS-PM). PLS-PM appears to be the preferred method by previous scholars because of its less stringent assumption and the need to avoid the perceived difficulties in CB-SEM. Along with this issue has been the increasing debate among researchers on the use of CB-SEM and PLS-PM in studies. The present study intends to assess the performance of CB-SEM and PLS-PM as a confirmatory study in which the findings will contribute to the body of knowledge of SEM. Maximum likelihood (ML) was chosen as the estimator for CB-SEM and was expected to be more powerful than PLS-PM. Based on the balanced experimental design, the multivariate normal data with specified population parameter and sample sizes were generated using Pro-Active Monte Carlo simulation, and the data were analyzed using AMOS for CB-SEM and SmartPLS for PLS-PM. Comparative Bias Index (CBI), construct relationship, average variance extracted (AVE), composite reliability (CR), and Fornell-Larcker criterion were used to study the consequence of each estimator. The findings conclude that CB-SEM performed notably better than PLS-PM in estimation for large sample size (100 and above), particularly in terms of estimations accuracy and consistency.

  13. Biomarkers and neurodevelopment in perinatally HIV-infected or exposed youth: a structural equation model analysis.

    Science.gov (United States)

    Kapetanovic, Suad; Griner, Ray; Zeldow, Bret; Nichols, Sharon; Leister, Erin; Gelbard, Harris A; Miller, Tracie L; Hazra, Rohan; Mendez, Armando J; Malee, Kathleen; Kammerer, Betsy; Williams, Paige L

    2014-01-28

    To examine the relationship between markers of vascular dysfunction and neurodevelopmental outcomes in perinatally HIV-infected (PHIV+) and perinatally HIV-exposed but uninfected (PHEU) youth. Cross-sectional design within a prospective, 15-site US-based cohort study. Neurodevelopmental outcomes were evaluated in relation to nine selected vascular biomarkers in 342 youth (212 PHIV+, 130 PHEU). Serum levels were assessed for adiponectin, C-reactive protein (CRP), fibrinogen, interleukin-6 (IL-6), soluble vascular cell adhesion molecule-1 (sVCAM-1), E-selectin (sE-selectin), monocyte chemoattractant protein (sMCP-1), intercellular adhesion molecule-1 (sICAM-1), and P-selectin (sP-selectin). The Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) was administered at entry, yielding a Full-Scale IQ score, and four index scores. Factor analysis was conducted to reduce the biomarkers to fewer factors with related biological roles. Structural equation models (SEMs) were used to measure associations between resulting factors and WISC-IV scores. Mean participant age was 11.4 years, 54% were female, 70% black. The nine biomarkers were clustered into three factor groups: F1 (fibrinogen, CRP, and IL-6); F2 (sICAM-1 and sVCAM-1); and F3 (MCP-1, sP-selectin, and sE-selectin). Adiponectin showed little correlation with any factor. SEMs revealed significant negative association of F1 with WISC-IV processing speed score in the total cohort. This effect remained significant after adjusting for HIV status and other potential confounders. A similar association was observed when restricted to PHIV+ participants in both unadjusted and adjusted SEMs. Aggregate measures of fibrinogen, CRP, and IL-6 may serve as a latent biomarker associated with relatively decreased processing speed in both PHIV+ and PHEU youth.

  14. Environmental and Individual Determinants of Female Entrepreneurship in Algeria: Applying the Structural Equation Modeling

    Directory of Open Access Journals (Sweden)

    Abderrezzak BENHABIB

    2014-03-01

    Full Text Available On the basis of the seminal work of Fishbein and Ajzen (1975, we try  to clarify  how  individual  and  environment  factors  influence  the students’  attitudes towards Entrepreneurship and Entrepreneurial Intention. After a short review of literature, we present the results of an empirical study conducted among a sample of 290 final year students by using a structural  equation  modeling  validated  through  the  use  of  a  two-stage  analysis  of Anderson  and  Gerbing  (1988  and  a  factorial  confirmatory  analysis  and  a measurement adjustment (Hair et al.1998. Attitude driven from individual variables is negative while that derived from environmental  variables  is  positive.  Our  results  show  furthermore,  that  the  role  of media and institutions is still Limited and needs redeployment. Woman is now recognized as one of the  sources of  economic  growth  (Arasti  2008.  Although  female  entrepreneurship  is  attracting more and more researchers, it is still considered as an understudied field of research (De Bruin et al.2006, 2007; Brush, De Bruin, & Welter, 2009. Research  on  female  entrepreneurship  has  intensified since  the  early  80s,  but  few  have  explored  the  influence  of  environmental  and individual factors related to female entrepreneurship.

  15. Forest owner representation of forest management and perception of resource efficiency: a structural equation modeling study

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    Andrej Ficko

    2015-03-01

    Full Text Available Underuse of nonindustrial private forests in developed countries has been interpreted mostly as a consequence of the prevailing noncommodity objectives of their owners. Recent empirical studies have indicated a correlation between the harvesting behavior of forest owners and the specific conceptualization of appropriate forest management described as "nonintervention" or "hands-off" management. We aimed to fill the huge gap in knowledge of social representations of forest management in Europe and are the first to be so rigorous in eliciting forest owner representations in Europe. We conducted 3099 telephone interviews with randomly selected forest owners in Slovenia, asking them whether they thought they managed their forest efficiently, what the possible reasons for underuse were, and what they understood by forest management. Building on social representations theory and applying a series of structural equation models, we tested the existence of three latent constructs of forest management and estimated whether and how much these constructs correlated to the perception of resource efficiency. Forest owners conceptualized forest management as a mixture of maintenance and ecosystem-centered and economics-centered management. None of the representations had a strong association with the perception of resource efficiency, nor could it be considered a factor preventing forest owners from cutting more. The underuse of wood resources was mostly because of biophysical constraints in the environment and not a deep-seated philosophical objection to harvesting. The difference between our findings and other empirical studies is primarily explained by historical differences in forestland ownership in different parts of Europe and the United States, the rising number of nonresidential owners, alternative lifestyle, and environmental protectionism, but also as a consequence of our high methodological rigor in testing the relationships between the constructs

  16. Factors contributing to academic achievement: a Bayesian structure equation modelling study

    Science.gov (United States)

    Payandeh Najafabadi, Amir T.; Omidi Najafabadi, Maryam; Farid-Rohani, Mohammad Reza

    2013-06-01

    In Iran, high school graduates enter university after taking a very difficult entrance exam called the Konkoor. Therefore, only the top-performing students are admitted by universities to continue their bachelor's education in statistics. Surprisingly, statistically, most of such students fall into the following categories: (1) do not succeed in their education despite their excellent performance on the Konkoor and in high school; (2) graduate with a grade point average (GPA) that is considerably lower than their high school GPA; (3) continue their master's education in majors other than statistics and (4) try to find jobs unrelated to statistics. This article employs the well-known and powerful statistical technique, the Bayesian structural equation modelling (SEM), to study the academic success of recent graduates who have studied statistics at Shahid Beheshti University in Iran. This research: (i) considered academic success as a latent variable, which was measured by GPA and other academic success (see below) of students in the target population; (ii) employed the Bayesian SEM, which works properly for small sample sizes and ordinal variables; (iii), which is taken from the literature, developed five main factors that affected academic success and (iv) considered several standard psychological tests and measured characteristics such as 'self-esteem' and 'anxiety'. We then study the impact of such factors on the academic success of the target population. Six factors that positively impact student academic success were identified in the following order of relative impact (from greatest to least): 'Teaching-Evaluation', 'Learner', 'Environment', 'Family', 'Curriculum' and 'Teaching Knowledge'. Particularly, influential variables within each factor have also been noted.

  17. Fatigue of Chinese railway employees and its influential factors: Structural equation modelling.

    Science.gov (United States)

    Tsao, Liuxing; Chang, Jing; Ma, Liang

    2017-07-01

    Fatigue is an identifiable and preventable cause of accidents in transport operations. Regarding the railway sector, incident logs and simulation studies show that employee fatigue leads to lack of alertness, impaired performance, and occurrence of incidents. China has one of the largest rail systems in the world, and Chinese railway employees work under high fatigue risks; therefore, it is important to assess their fatigue level and find the major factors leading to fatigue. We designed a questionnaire that uses Multidimensional Fatigue Instrument (MFI-20), NASA-TLX and subjective rating of work overtime feelings to assess employee fatigue. The contribution of each influential factor of fatigue was analysed using structural equation modelling. In total, 297 employees from the rail maintenance department and 227 employees from the locomotive department returned valid responses. The average scores and standard deviations for the five subscales of MFI-20, namely General Fatigue, Physical Fatigue, Reduced Activity, Reduced Motivation, and Mental Fatigue, were 2.9 (0.8), 2.8 (0.8), 2.5 (0.8), 2.5 (0.7), and 2.4 (0.8) among the rail maintenance employees and 3.5 (0.8), 3.5 (0.7), 3.3 (0.7), 3.0 (0.6), and 3.1 (0.7), respectively, among the locomotive employees. The fatigue of the locomotive employees was influenced by feelings related to working overtime (standardized r = 0.22) and workload (standardized r = 0.27). The work overtime control and physical working environment significantly influenced subjective feelings (standardized r = -0.25 and 0.47, respectively), while improper work/rest rhythms and an adverse physical working environment significantly increased the workload (standardized r = 0.48 and 0.33, respectively). Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. [Structural Equation Modeling of Quality of Work Life in Clinical Nurses based on the Culture-Work-Health Model].

    Science.gov (United States)

    Kim, Miji; Ryu, Eunjung

    2015-12-01

    The purpose of this study was to construct and test a structural equation model of quality of work life for clinical nurses based on Peterson and Wilson's Culture-Work-Health model (CWHM). A structured questionnaire was completed by 523 clinical nurses to analyze the relationships between concepts of CWHM-organizational culture, social support, employee health, organizational health, and quality of work life. Among these conceptual variables of CWHM, employee health was measured by perceived health status, and organizational health was measured by presenteeism. SPSS21.0 and AMOS 21.0 programs were used to analyze the efficiency of the hypothesized model and calculate the direct and indirect effects of factors affecting quality of work life among clinical nurses. The goodness-of-fit statistics of the final modified hypothetical model are as follows: χ²=586.03, χ²/df=4.19, GFI=.89, AGFI=.85, CFI=.91, TLI=.90, NFI=.89, and RMSEA=.08. The results revealed that organizational culture, social support, organizational health, and employee health accounted for 69% of clinical nurses' quality of work life. The major findings of this study indicate that it is essential to create a positive organizational culture and provide adequate organizational support to maintain a balance between the health of clinical nurses and the organization. Further repeated and expanded studies are needed to explore the multidimensional aspects of clinical nurses' quality of work life in Korea, including various factors, such as work environment, work stress, and burnout.

  19. Insight, self-stigma and psychosocial outcomes in Schizophrenia: a structural equation modelling approach.

    Science.gov (United States)

    Lien, Y-J; Chang, H-A; Kao, Y-C; Tzeng, N-S; Lu, C-W; Loh, C-H

    2016-12-15

    Poor insight is prevalent in patients with schizophrenia and has been associated with acute illness severity, medication non-adherence and poor treatment outcomes. Paradoxically, high insight has been associated with various undesirable outcomes, including low self-esteem, depression and low subjective quality of life (QoL) in patients with schizophrenia. Despite the growing body of studies conducted in Western countries supporting the pernicious effects of improved insight in psychosis, which bases on the level of self-stigma, the effects are unclear in non-Western societies. The current study examined the role of self-stigma in the relationship between insight and psychosocial outcomes in a Chinese population. A total of 170 outpatients with schizophrenia spectrum disorders were recruited from two general university hospitals. Sociodemographic data and clinical variables were recorded and self-report scales were employed to measure self-stigma, depression, insight, self-esteem and subjective QoL. Structural equation modelling (SEM) was used to analyse the cross-sectional data. High levels of self-stigma were reported by 39% of the participants (n = 67). The influences of insight, self-stigma, self-esteem and depression on subjective QoL were confirmed by the SEM results. Our model with the closest fit to the data (χ 2 = 33.28; df = 20; p = 0.03; χ 2/df = 1.66; CFI = 0.98; TLI = 0.97; RMSEA = 0.06) demonstrated that self-stigma might fully mediate the association of insight with low self-esteem, depression and poor subjective QoL. High insight into illness contributed to self-stigma, which caused low self-esteem and depression and, consequently, low QoL. Notably, insight did not directly affect self-esteem, depression or QoL. Furthermore, the association of insight with poor psychosocial outcomes was not moderated by self-stigma. Our findings support the mediating model of insight relevant to the poor psychosocial outcomes of individuals diagnosed with

  20. Using structural equation modeling to link human activities to wetland ecological integrity

    Science.gov (United States)

    Schweiger, E. William; Grace, James B.; Cooper, David; Bobowski, Ben; Britten, Mike

    2016-01-01

    The integrity of wetlands is of global concern. A common approach to evaluating ecological integrity involves bioassessment procedures that quantify the degree to which communities deviate from historical norms. While helpful, bioassessment provides little information about how altered conditions connect to community response. More detailed information is needed for conservation and restoration. We have illustrated an approach to addressing this challenge using structural equation modeling (SEM) and long-term monitoring data from Rocky Mountain National Park (RMNP). Wetlands in RMNP are threatened by a complex history of anthropogenic disturbance including direct alteration of hydrologic regimes; elimination of elk, wolves, and grizzly bears; reintroduction of elk (absent their primary predators); and the extirpation of beaver. More recently, nonnative moose were introduced to the region and have expanded into the park. Bioassessment suggests that up to half of the park's wetlands are not in reference condition. We developed and evaluated a general hypothesis about how human alterations influence wetland integrity and then develop a specific model using RMNP wetlands. Bioassessment revealed three bioindicators that appear to be highly sensitive to human disturbance (HD): (1) conservatism, (2) degree of invasion, and (3) cover of native forbs. SEM analyses suggest several ways human activities have impacted wetland integrity and the landscape of RMNP. First, degradation is highest where the combined effects of all types of direct HD have been the greatest (i.e., there is a general, overall effect). Second, specific HDs appear to create a “mixed-bag” of complex indirect effects, including reduced invasion and increased conservatism, but also reduced native forb cover. Some of these effects are associated with alterations to hydrologic regimes, while others are associated with altered shrub production. Third, landscape features created by historical beaver

  1. A structural equation model of the determinants of malnutrition among children in rural Kelantan, Malaysia.

    Science.gov (United States)

    Cheah, Whye Lian; Muda, Wan Abdul Manan Wan; Zamh, Zabidi-Hussin

    2010-01-01

    Many studies had shown that poor growth in children is associated with malnutrition. The underlying factors are diverse, multisectoral and interrelated, ranging from biological to social, cultural and economically related. Because the highest levels of under-nutrition worldwide are found in South Asia, it is essential that policymakers in the region understand the underlying determinants, in order to design effective public health intervention programs. This is especially so if public resources are limited. The purpose of this cross-sectional study was to examine causal relationships among the biological, behavioural and environmental factors related to malnutrition in children aged 5 years and under. The instrument used in this study was based on a previously described conceptual framework for malnutrition in children, and tested for its psycometric component, using both qualitative and quantitative methods. As well as the use of a questionnaire, anthropometric and dietary data were collected from 295 children aged 5 years and below, randomly selected from clinics in Tumpat, Kelantan. The proposed model was tested and modified using structural equation modelling (AMOS software: ADC, Chicago, IL, USA). The modified model fitted the data adequately. The results demonstrated that an environmental construct (with factors that included total household income beta = 0.68, p <0.01; total expenditure beta = 0.67, p <0.01; number of rooms in the house beta = 0.46, p <0.01; and socioeconomic status beta = 0.71, p <0.01) had a significant effect on malnutrition. Neither the biological nor behavioural constructs had significant effects. These findings provide useful insights into the importance of focusing on environmental factors as the main target when designing intervention programs. This information will be useful for the prioritization of preventive programs when resources are limited, especially in a rural setting. Future studies should focus on the issues of the

  2. Full Equations (FEQ) model for the solution of the full, dynamic equations of motion for one-dimensional unsteady flow in open channels and through control structures

    Science.gov (United States)

    Franz, Delbert D.; Melching, Charles S.

    1997-01-01

    The Full EQuations (FEQ) model is a computer program for solution of the full, dynamic equations of motion for one-dimensional unsteady flow in open channels and through control structures. A stream system that is simulated by application of FEQ is subdivided into stream reaches (branches), parts of the stream system for which complete information on flow and depth are not required (dummy branches), and level-pool reservoirs. These components are connected by special features; that is, hydraulic control structures, including junctions, bridges, culverts, dams, waterfalls, spillways, weirs, side weirs, and pumps. The principles of conservation of mass and conservation of momentum are used to calculate the flow and depth throughout the stream system resulting from known initial and boundary conditions by means of an implicit finite-difference approximation at fixed points (computational nodes). The hydraulic characteristics of (1) branches including top width, area, first moment of area with respect to the water surface, conveyance, and flux coefficients and (2) special features (relations between flow and headwater and (or) tail-water elevations, including the operation of variable-geometry structures) are stored in function tables calculated in the companion program, Full EQuations UTiLities (FEQUTL). Function tables containing other information used in unsteady-flow simulation (boundary conditions, tributary inflows or outflows, gate settings, correction factors, characteristics of dummy branches and level-pool reservoirs, and wind speed and direction) are prepared by the user as detailed in this report. In the iterative solution scheme for flow and depth throughout the stream system, an interpolation of the function tables corresponding to the computational nodes throughout the stream system is done in the model. FEQ can be applied in the simulation of a wide range of stream configurations (including loops), lateral-inflow conditions, and special features. The

  3. Structural equation modeling in epidemiology Modelagem de equações estruturais em epidemiologia

    Directory of Open Access Journals (Sweden)

    Leila Denise Alves Ferreira Amorim

    2010-12-01

    Full Text Available Structural equation modeling (SEM is an important statistical tool for evaluating complex relations in several research areas. In epidemiology, the use and discussion of SEM have been limited thus far. This article presents basic principles and concepts in SEM, including an application using epidemiological data analysis from a study on the determinants of cognitive development in young children, considering constructs related to organization of the child's home environment, parenting style, and the child's health status. The relations between the constructs and cognitive development were measured. The results showed a positive association between psychosocial stimulus at home and cognitive development in young children. The article presents the contributions by SEM to epidemiology, highlighting the need for an a priori theoretical model for improving the study of epidemiological questions from a new perspective.A modelagem de equações estruturais (MEE é uma ferramenta estatística importante para avaliar relações complexas em várias áreas do conhecimento. Em Epidemiologia sua divulgação e uso são limitados. Este artigo apresenta princípios e conceitos básicos da MEE, com exemplo de aplicação na análise de dados epidemiológicos. A análise de dados é realizada em estudo que investiga determinantes do desenvolvimento cognitivo infantil, sendo definidos construtos relacionados à organização do ambiente da criança, ao seu status de saúde, e às práticas e estilo de vida dos pais. O impacto positivo da qualidade de estimulação psicossocial do ambiente doméstico sobre o índice de desempenho cognitivo (IDC esclarece que parte do efeito da estimulação sobre o IDC deve-se ao estilo parental de interação com a criança e às características físico-ambientais do contexto familiar. As potencialidades do uso da MEE em Epidemiologia são apresentadas, enfatizando-se a definição do modelo teórico e seu uso para

  4. The Causal Relationship Between Managerial Pay and Firm Performance: a Confirmatory Study with Structural Equation Model

    Institute of Scientific and Technical Information of China (English)

    YougenLi; XipingZhao; JianfangGeng

    2004-01-01

    We use structural equation technique to test four hypothesis relationships between the managerial pay and firm performance. Data from 208 Chinese listed companies is used, the evidence supports Hypothesis 3. It opens out that ownership concentration affects firm performance indirectly through managerial pay, and illustrates managerial pay is a valid mechanism in corporate governance to motivate manager to maximize firm's performance.At the same time, we find ownership concentration is negative to managerial pay, while IPO time and registration areas are positive to managerial pay obviously. It suggests that finding a correct solution to management incentive is the key to improve firm performance.

  5. Assessing Actual Visit Behavior through Antecedents of Tourists Satisfaction among International Tourists in Jordan: A Structural Equation Modeling (SEM Approach

    Directory of Open Access Journals (Sweden)

    Ayed Moh’d Al Muala

    2011-06-01

    Full Text Available Jordan tourism industry is facing fluctuating tourist visit provoked by dissatisfaction, high visit risk, low hotel service, or negative Jordan image. This study aims to examine the relationships between the antecedents of tourist satisfaction and actual visit behavior in tourism of Jordan, and the mediating effect of tourist satisfaction (SAT in the relationship between Jordan image (JOM, service climate (SER and actual visit behavior (ACT. A total of 850 international tourists completed a survey that were conducted at southern sites in Jordan. Using structural equation modeling (SEM technique, confirmatory Factor Analysis (CFA was performed to examine the reliability and validity of the measurement, and the structural equation modeling techniques (Amos 6.0 were used to evaluate the casual model. Results of the study demonstrate the strong predictive power and explain of international tourists’ behavior in Jordan. The findings highlighted that the relationship between Jordan image and service climate are significant and positive on actual visit behavior.

  6. Environmental, psychological, and social influences on physical activity among Japanese adults: structural equation modeling analysis

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    Ishii Kaori

    2010-08-01

    Full Text Available Abstract Background An understanding of the contributing factors to be considered when examining how individuals engage in physical activity is important for promoting population-based physical activity. The environment influences long-term effects on population-based health behaviors. Personal variables, such as self-efficacy and social support, can act as mediators of the predictive relationship between the environment and physical activity. The present study examines the direct and indirect effects of environmental, psychological, and social factors on walking, moderate-intensity activity excluding walking, and vigorous-intensity activity among Japanese adults. Methods The participants included 1,928 Japanese adults aged 20-79 years. Seven sociodemographic attributes (e.g., gender, age, education level, employment status, psychological variables (self-efficacy, pros, and cons, social variables (social support, environmental variables (home fitness equipment, access to facilities, neighborhood safety, aesthetic sensibilities, and frequency of observing others exercising, and the International Physical Activity Questionnaire were assessed via an Internet-based survey. Structural equation modeling was conducted to determine associations between environmental, psychological, and social factors with physical activity. Results Environmental factors could be seen to have indirect effects on physical activity through their influence on psychological and social variables such as self-efficacy, pros and cons, and social support. The strongest indirect effects could be observed by examining the consequences of environmental factors on physical activity through cons to self-efficacy. The total effects of environmental factors on physical activity were 0.02 on walking, 0.02 on moderate-intensity activity excluding walking, and 0.05 on vigorous-intensity activity. Conclusions The present study indicates that environmental factors had indirect effects on

  7. Exact solutions of the general equilibrium shape equations in a general power model of free energy for DNA structures

    Science.gov (United States)

    Yavari, Morteza

    2014-02-01

    The aim of this paper is to generalize the results of the Feoli's formalism (A. Feoli et al., Nucl. Phys. B 705, 577 (2005)) for DNA structures. The exact solutions of the general equilibrium shape equations for a general power model of free energy are investigated using the Feoli's formalism. The free energy of B- to Z-DNA transition is also calculated in this formalism.

  8. A quantative evaluation of the reformulated 1996 path-goal theory of work unit leadership via structural equation modelling

    OpenAIRE

    Howieson, William B

    2008-01-01

    In 1996, Professor Robert J House published a reformulated Path-Goal Theory of Work Unit Leadership, based on his earlier 1971 and 1974 theories. Path-goal leadership attempts to explain the impact that leader behaviour has on subordinate motivation, satisfaction and performance. The aim of this context-specific study is to evaluate this reformulated ‘1996 Theory’ via Structural Equation Modelling with engineers from the Royal Air Force as the primary data source. This th...

  9. On the relationship between justice judgments, outcomes and identity orientations among Iranian EFL learners: A structural equation model

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    Seyyed Ayatollah Razmjoo

    2015-06-01

    Full Text Available One problem which can be observed in the field of EFL/ESL learning is that a number of English major BA and MA students are not highly committed to their major and decide not to continue their graduate studies. Sometimes even graduate students from English majors prefer to extend their education or work in an unrelated field. This might be attributed to the extent to which they perceive evaluation procedures and outcomes as fair. Considering this, the present study investigates first the relationships between justice judgments, outcomes and identity orientations. The study, then, uses structural equation modeling in order to examine whether identity orientation has any mediating effect on the relationship between justice judgment and outcomes. Participants were74 students in Department of Foreign Languages and Linguistics, Shiraz University selected based on convenience sampling. They filled out three questionnaires on distributive and procedural justice judgments, rule compliance and outcome satisfaction, and personal and social identity orientations. The collected data was then analyzed using descriptive statistics, correlation, and structural equation modeling. Based on the obtained findings, procedural justice had significant positive correlation with rule compliance and distributive justice was significantly correlated with outcome satisfaction. The generated structural equation model also indicated that justice judgments only directly affected outcomes and identity had no mediating effect on the causal relationship between the two.

  10. The Relationship between the Environmental Awareness, Environmental Attitude, Curiosity and Exploration in Highly Gifted Students: Structural Equation Modelling

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    Hakan Saricam

    2015-11-01

    Full Text Available The basic purpose of this study was to examine the relationships between environmental awareness, environmental attitude, curiosity and exploration in highly gifted students with structural equation modelling. The secondary aim was to compare highly gifted and non-gifted students’ environmental awareness, environmental attitude, curiosity and exploration levels. Participants were 311 (154 highly gifted, 157 non-gifted secondary school students in Turkey who volunteered to take part in this study. All of the participants were either 13 or 14 years old, with a mean age of 13.77 years. For gathering data, Environmental Awareness Scale, Environmental Attitude Scale, Curiosity and Exploration-II were used. While analyzing the data, Pearson correlation analysis, independent samples t test, and structural equation model were used. According to the findings, highly gifted students’ environmental awareness, environmental attitude, curiosity and exploration scores were higher than non-gifted students’. Indices of Structural Equation Modelling (SEM indicated that the increase in the curiosity and exploration scores of the highly gifted children increased the environmental awareness; in this case, the environmental attitudes were affected positively.

  11. [Empirical research of the relationship between related knowledge, attitude and behavior of hypertension patients based on the structural equation model].

    Science.gov (United States)

    Zeng, Zhaoyuanling; Wang, Xiaowan; Wang, Zengwu; Guo, Rui; Feng, Ruihua

    2017-02-28

    To analyze the relationship among hypertension-relevant knowledge, attitude and behavior and to provide evidence for prevention of hypertension.
 Methods: A total of 5 861 employees with hypertension from 10 provinces were selected, and their data were collected by uniform questionnaires. The structural equation model was established by using LISREL version 8.7. Knowledge, attitude and behavior was set as latent variables, and the observed variables corresponding to latent variables served as explicit variables. The parametric estimation of the structural equation model is based on polyserial correlation coefficients and asymptotical covariance matrix.
 Results: Knowledge directly affected attitude, and the impact coefficient was 0.84; attitude directly affect behavior, and the impact coefficient was 0.38; knowledge showed indirect effect on behavior; the structural equation model fitted the data well.
 Conclusion: Hypertension-related knowledge significantly affect attitude, while knowledge and attitude showed slight effect on behavior. There were other factors that affected the patient's behavior. It was suggested that we should fully consider the factors for behavior in health education, and adopt more appropriate measures in hypertension control.

  12. Modeling statistics and kinetics of the natural aggregation structures and processes with the solution of generalized logistic equation

    Science.gov (United States)

    Maslov, Lev A.; Chebotarev, Vladimir I.

    2017-02-01

    The generalized logistic equation is proposed to model kinetics and statistics of natural processes such as earthquakes, forest fires, floods, landslides, and many others. This equation has the form dN(A)/dA = s dot (1-N(A)) dot N(A)q dot A-α, q>0q>0 and A>0A>0 is the size of an element of a structure, and α≥0. The equation contains two exponents α and q taking into account two important properties of elements of a system: their fractal geometry, and their ability to interact either to enhance or to damp the process of aggregation. The function N(A)N(A) can be understood as an approximation to the number of elements the size of which is less than AA. The function dN(A)/dAdN(A)/dA where N(A)N(A) is the general solution of this equation for q=1 is a product of an increasing bounded function and power-law function with stretched exponential cut-off. The relation with Tsallis non-extensive statistics is demonstrated by solving the generalized logistic equation for q>0q>0. In the case 01q>1 it models sub-additive structures. The Gutenberg-Richter (G-R) formula results from interpretation of empirical data as a straight line in the area of stretched exponent with small α. The solution is applied for modeling distribution of foreshocks and aftershocks in the regions of Napa Valley 2014, and Sumatra 2004 earthquakes fitting the observed data well, both qualitatively and quantitatively.

  13. Antecedents Factors that Influence Soy Consumption: A Structural Equation Modeling Approach

    OpenAIRE

    Balasubramanian, Siva K.; Moon, Wanki; Rimal, Arbindra; Coker, Kesha

    2009-01-01

    We propose a structural model of antecedent factors that affect the frequency of soy consumption. This model, suggests that soy-general knowledge influences perceptions about nutrition concern, health benefits of soy, soy related personal beliefs and personal attitudes toward soy. Health benefits of soy, in turn, impacts soy-related personal beliefs and personal attitudes toward soy. Additionally, soy-related personal beliefs influence personal attitudes toward soy. Finally, both nutrition co...

  14. Total Productive Maintenance And Role Of Interpretive Structural Modeling And Structural Equation Modeling In Analyzing Barriers In Its Implementation A Literature Review

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    Prasanth S. Poduval

    2015-08-01

    Full Text Available Abstract - The aim of the authors is to present a review of literature of Total Productive Maintenance and the barriers in implementation of Total Productive Maintenance TPM. The paper begins with a brief description of TPM and the barriers in implementation of TPM. Interpretive Structural Modeling ISM and its role in analyzing the barriers in TPM implementation is explained in brief. Applications of ISM in analyzing issues in various fields are highlighted with special emphasis on TPM. The paper moves on to introduction to Structural Equation Modeling SEM and its role in validating ISM in analyzing barriers in implementation of TPM. The paper concludes with a gap analysis from the current literature research that can be carried out and expected outcomes from the proposed research.

  15. The importance of isomorphism for conclusions about homology: A Bayesian multilevel structural equation modeling approach with ordinal indicators

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    Nigel eGuenole

    2016-03-01

    Full Text Available We describe a Monte Carlo study examining the impact of assuming item isomorphism (i.e., equivalent construct meaning across levels of analysis on conclusions about homology (i.e., equivalent structural relations across levels of analysis under varying degrees of non-isomorphism in the context of ordinal indicator multilevel structural equation models (MSEMs. We focus on the condition where one or more loadings are higher on the between level than on the within level to show that while much past research on homology has ignored the issue of psychometric isomorphism, psychometric isomorphism is in fact critical to valid conclusions about homology. More specifically, when a measurement model with non-isomorphic items occupies an exogenous position in a multilevel structural model and the non-isomorphism of these items is not modeled, the within level exogenous latent variance is under-estimated leading to over-estimation of the within level structural coefficient, while the between level exogenous latent variance is overestimated leading to underestimation of the between structural coefficient. When a measurement model with non-isomorphic items occupies an endogenous position in a multilevel structural model and the non-isomorphism of these items is not modeled, the endogenous within level latent variance is under-estimated leading to under-estimation of the within level structural coefficient while the endogenous between level latent variance is over-estimated leading to over-estimation of the between level structural coefficient. The innovative aspect of this article is demonstrating that even minor violations of psychometric isomorphism render claims of homology untenable. We also show that posterior predictive p-values for ordinal indicator Bayesian MSEMs are insensitive to violations of isomorphism even when they lead to severely biased within and between level structural parameters. We highlight conditions where poor estimation of even

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

    Science.gov (United States)

    Guenole, Nigel

    2016-01-01

    We describe a Monte Carlo study examining the impact of assuming item isomorphism (i.e., equivalent construct meaning across levels of analysis) on conclusions about homology (i.e., equivalent structural relations across levels of analysis) under varying degrees of non-isomorphism in the context of ordinal indicator multilevel structural equation models (MSEMs). We focus on the condition where one or more loadings are higher on the between level than on the within level to show that while much past research on homology has ignored the issue of psychometric isomorphism, psychometric isomorphism is in fact critical to valid conclusions about homology. More specifically, when a measurement model with non-isomorphic items occupies an exogenous position in a multilevel structural model and the non-isomorphism of these items is not modeled, the within level exogenous latent variance is under-estimated leading to over-estimation of the within level structural coefficient, while the between level exogenous latent variance is overestimated leading to underestimation of the between structural coefficient. When a measurement model with non-isomorphic items occupies an endogenous position in a multilevel structural model and the non-isomorphism of these items is not modeled, the endogenous within level latent variance is under-estimated leading to under-estimation of the within level structural coefficient while the endogenous between level latent variance is over-estimated leading to over-estimation of the between level structural coefficient. The innovative aspect of this article is demonstrating that even minor violations of psychometric isomorphism render claims of homology untenable. We also show that posterior predictive p-values for ordinal indicator Bayesian MSEMs are insensitive to violations of isomorphism even when they lead to severely biased within and between level structural parameters. We highlight conditions where poor estimation of even correctly specified

  17. Linking structural equation modeling with Bayesian network and its application to coastal phytoplankton dynamics in the Bohai Bay

    Science.gov (United States)

    Xu, Xiao-fu; Sun, Jian; Nie, Hong-tao; Yuan, De-kui; Tao, Jian-hua

    2016-10-01

    Bayesian networks (BN) have many advantages over other methods in ecological modeling, and have become an increasingly popular modeling tool. However, BN are flawed in regard to building models based on inadequate existing knowledge. To overcome this limitation, we propose a new method that links BN with structural equation modeling (SEM). In this method, SEM is used to improve the model structure for BN. This method was used to simulate coastal phytoplankton dynamics in the Bohai Bay. We demonstrate that this hybrid approach minimizes the need for expert elicitation, generates more reasonable structures for BN models, and increases the BN model's accuracy and reliability. These results suggest that the inclusion of SEM for testing and verifying the theoretical structure during the initial construction stage improves the effectiveness of BN models, especially for complex eco-environment systems. The results also demonstrate that in the Bohai Bay, while phytoplankton biomass has the greatest influence on phytoplankton dynamics, the impact of nutrients on phytoplankton dynamics is larger than the influence of the physical environment in summer. Furthermore, although the Redfield ratio indicates that phosphorus should be the primary nutrient limiting factor, our results show that silicate plays the most important role in regulating phytoplankton dynamics in the Bohai Bay.

  18. Structural equation model of total phosphorus loads in the Red River of the North Basin, USA and Canada

    Science.gov (United States)

    Ryberg, Karen R.

    2017-01-01

    Attribution of the causes of trends in nutrient loading is often limited to correlation, qualitative reasoning, or references to the work of others. This paper represents efforts to improve causal attribution of water-quality changes. The Red River of the North basin provides a regional test case because of international interest in the reduction of total phosphorus loads and the availability of long-term total phosphorus data and ancillary geospatial data with the potential to explain changes in water quality over time. The objectives of the study are to investigate structural equation modeling methods for application to water-quality problems and to test causal hypotheses related to the drivers of total phosphorus loads over the period 1970 to 2012. Multiple working hypotheses that explain total phosphorus loads and methods for estimating missing ancillary data were developed, and water-quality related challenges to structural equation modeling (including skewed data and scaling issues) were addressed. The model indicates that increased precipitation in season 1 (November–February) or season 2 (March–June) would increase total phosphorus loads in the basin. The effect of agricultural practices on total phosphorus loads was significant, although the effect is about one-third of the effect of season 1 precipitation. The structural equation model representing loads at six sites in the basin shows that climate and agricultural practices explain almost 60% of the annual total phosphorus load in the Red River of the North basin. The modeling process and the unexplained variance highlight the need for better ancillary long-term data for causal assessments.

  19. The structure of personality disorders: comparing the DSM-IV-TR Axis II classification with the five-factor model framework using structural equation modeling.

    Science.gov (United States)

    Bastiaansen, Leen; Rossi, Gina; Schotte, Christiaan; De Fruyt, Filip

    2011-06-01

    Earlier factor analytical studies on the empirical validity of the DSM-IV-TR (American Psychological Association, 2000) Axis II classification have offered little support for the current three-cluster structure. In his large-scale meta-analysis of previously published personality disorder correlation matrices, O'Connor (2005) found four factors, corresponding to the neuroticism, extraversion, agreeableness, and conscientiousness domains of the five-factor model of personality. In the present study, this dimensional four-factor model and the categorical DSM three-cluster structure were fitted to the Assessment of DSM-IV Personality Disorders questionnaire (ADP-IV; Schotte & De Doncker, 1994) scale scores using structural equation modelling. The results strongly favored the dimensional model, which also resembled other well-founded four-factor proposals (Livesley, Jang, & Vernon, 1998; Widiger & Simonsen, 2005). Moreover, a multigroup confirmatory factor analysis showed that this model was highly invariant and thus generalizable across two large clinical (n = 1,029) and general population (n = 659) samples.

  20. Relationship between Temperament, Depression, Anxiety, and Hopelessness in Adolescents: A Structural Equation Model

    OpenAIRE

    Paolo Iliceto; Maurizio Pompili; David Lester; Xenia Gonda; Cinzia Niolu; Nicoletta Girardi; Zoltán Rihmer; Gabriella Candilera; Paolo Girardi

    2011-01-01

    The purpose of this study was to test the validity of affective temperaments for predicting psychiatric morbidity and suicide risk, using a two-factor model to explain the relationships between temperament, anxiety, depression, and hopelessness. We investigated 210 high school students, 103 males and 107 females, 18-19 years old, who were administered self-report questionnaires to assess temperament (TEMPS-A), depression (BDI-II), anxiety (STAI) and hopelessness (BHS). The final structural mo...

  1. Structural equation and log-linear modeling: a comparison of methods in the analysis of a study on caregivers' health

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    Rosenbaum Peter L

    2006-10-01

    Full Text Available Abstract Background In this paper we compare the results in an analysis of determinants of caregivers' health derived from two approaches, a structural equation model and a log-linear model, using the same data set. Methods The data were collected from a cross-sectional population-based sample of 468 families in Ontario, Canada who had a child with cerebral palsy (CP. The self-completed questionnaires and the home-based interviews used in this study included scales reflecting socio-economic status, child and caregiver characteristics, and the physical and psychological well-being of the caregivers. Both analytic models were used to evaluate the relationships between child behaviour, caregiving demands, coping factors, and the well-being of primary caregivers of children with CP. Results The results were compared, together with an assessment of the positive and negative aspects of each approach, including their practical and conceptual implications. Conclusion No important differences were found in the substantive conclusions of the two analyses. The broad confirmation of the Structural Equation Modeling (SEM results by the Log-linear Modeling (LLM provided some reassurance that the SEM had been adequately specified, and that it broadly fitted the data.

  2. Different perceptions of stress, coping styles, and general well-being among pregnant Chinese women: a structural equation modeling approach.

    Science.gov (United States)

    Lau, Ying; Tha, Pyai Htun; Wong, Daniel Fu Keung; Wang, Yuqiong; Wang, Ying; Yobas, Piyanee Klainin

    2016-02-01

    Few studies have examined different perceptions of stress or explored the positive aspects of well-being among pregnant Chinese women, so there is a need to explore these phenomena in order to fill the research gap. The aim of this study was to examine the relationships among the different perceptions of stress, coping styles, and general well-being using a structural equation modeling approach. We examined a hypothetical model among 755 pregnant Chinese women based on the integration of theoretical models. The Perceived Stress Scale (PSS), the Trait Coping Styles Questionnaire (TCSQ), and the General Well-Being Schedule (GWB) were used to measure perceived stress, coping styles, and general well-being, respectively. A structural equation model showed that positive and negative perceptions of stress significantly influenced positive and negative coping styles, respectively. Different perceptions of stress were significantly associated with general well-being, but different coping styles had no significant effects on general well-being. The model had a good fit to the data (IFI = 0.910, TLI = 0.904, CFI = 0.910, and RMSEA = 0.038). Different perception of stress was able to predict significant differences in coping styles and general well-being.

  3. A Novel Approach for Assessing the Performance of Sustainable Urbanization Based on Structural Equation Modeling: A China Case Study

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    Liudan Jiao

    2016-09-01

    Full Text Available The rapid urbanization process has brought problems to China, such as traffic congestion, air pollution, water pollution and resources scarcity. Sustainable urbanization is commonly appreciated as an effective way to promote the sustainable development. The proper understanding of the sustainable urbanization performance is critical to provide governments with support in making urban development strategies and policies for guiding the sustainable development. This paper utilizes the method of Structural equation modeling (SEM to establish an assessment model for measuring sustainable urbanization performance. Four unobserved endogenous variables, economic variable, social variable, environment variable and resource variable, and 21 observed endogenous variables comprise the SEM model. A case study of the 31 provinces in China demonstrates the validity of the SEM model and the analysis results indicated that the assessment model could help make more effective policies and strategies for improving urban sustainability by recognizing the statue of sustainable urbanization.

  4. Analysis of causal relationships by structural equation modeling to determine the factors influencing cognitive function in elderly people in Japan.

    Science.gov (United States)

    Kimura, Daisuke; Nakatani, Ken; Takeda, Tokunori; Fujita, Takashi; Sunahara, Nobuyuki; Inoue, Katsumi; Notoya, Masako

    2015-01-01

    The purpose of this study is to identify a potentiality factor that is a preventive factor for decline in cognitive function. Additionally, this study pursues to clarify the causal relationship between the each potential factor and its influence on cognitive function. Subjects were 366 elderly community residents (mean age 73.7 ± 6.4, male 51, female 315) who participated in the Taketoyo Project from 2007 to 2011. Factor analysis was conducted to identify groupings within mental, social, life, physical and cognitive functions. In order to detect clusters of 14 variables, the item scores were subjected to confirmatory factor analysis. We performed Structural Equation Modeling analysis to calculate the standardization coefficient and correlation coefficient for every factor. The cause and effect hypothesis model was used to gather two intervention theory hypotheses for dementia prevention (direct effect, indirect effect) in one system. Finally, we performed another Structural Equation Modeling analysis to calculate the standardization of the cause and effect hypothesis model. Social participation was found to be activated by the improvement of four factors, and in turn, activated "Social participation" acted on cognitive function.

  5. Sensitivity analysis for linear structural equation models, longitudinal mediation with latent growth models and blended learning in biostatistics education

    Science.gov (United States)

    Sullivan, Adam John

    In chapter 1, we consider the biases that may arise when an unmeasured confounder is omitted from a structural equation model (SEM) and sensitivity analysis techniques to correct for such biases. We give an analysis of which effects in an SEM are and are not biased by an unmeasured confounder. It is shown that a single unmeasured confounder will bias not just one but numerous effects in an SEM. We present sensitivity analysis techniques to correct for biases in total, direct, and indirect effects when using SEM analyses, and illustrate these techniques with a study of aging and cognitive function. In chapter 2, we consider longitudinal mediation with latent growth curves. We define the direct and indirect effects using counterfactuals and consider the assumptions needed for identifiability of those effects. We develop models with a binary treatment/exposure followed by a model where treatment/exposure changes with time allowing for treatment/exposure-mediator interaction. We thus formalize mediation analysis with latent growth curve models using counterfactuals, makes clear the assumptions and extends these methods to allow for exposure mediator interactions. We present and illustrate the techniques with a study on Multiple Sclerosis(MS) and depression. In chapter 3, we report on a pilot study in blended learning that took place during the Fall 2013 and Summer 2014 semesters here at Harvard. We blended the traditional BIO 200: Principles of Biostatistics and created ID 200: Principles of Biostatistics and epidemiology. We used materials from the edX course PH207x: Health in Numbers: Quantitative Methods in Clinical & Public Health Research and used. These materials were used as a video textbook in which students would watch a given number of these videos prior to class. Using surveys as well as exam data we informally assess these blended classes from the student's perspective as well as a comparison of these students with students in another course, BIO 201

  6. Relationship between Temperament, Depression, Anxiety, and Hopelessness in Adolescents: A Structural Equation Model

    Directory of Open Access Journals (Sweden)

    Paolo Iliceto

    2011-01-01

    Full Text Available The purpose of this study was to test the validity of affective temperaments for predicting psychiatric morbidity and suicide risk, using a two-factor model to explain the relationships between temperament, anxiety, depression, and hopelessness. We investigated 210 high school students, 103 males and 107 females, 18-19 years old, who were administered self-report questionnaires to assess temperament (TEMPS-A, depression (BDI-II, anxiety (STAI and hopelessness (BHS. The final structural model had a good fit with the data, with two factors significantly correlated, the first labeled unstable cyclothymic temperament including Dysthymic/Cyclothymic/Anxious temperament, Irritable temperament and Depression, and the second labeled Demoralization including Anxiety (State/Trait and Hopelessness. Depression, anxiety and hopelessness are in a complex relationship partly mediated by temperament.

  7. Exploring public bus service quality in South Africa: A structural equation modelling approach

    Directory of Open Access Journals (Sweden)

    Ayanda M. Vilakazi

    2014-03-01

    Full Text Available This study, which is a deviation from the usual practice of using SERVQUAL or an adaptedversion thereof, uses McKnight, Pagano and Paaswell’s (1986 service quality dimensions,namely reliability; extent of service; comfort; safety; and affordability (RECSA and structuralequation modelling to determine commuters’ perception of public bus service quality in amajor city in South Africa. The RECSA model was adapted and fitted to the data collectedfrom a convenience sample of bus commuters in Johannesburg, using structural equationmodelling. It was ascertained that reliability, service, comfort and safety influenced thepublic bus commuters’ perception of the overall service quality. The implications of theaforementioned findings for providers of public bus services are explained.

  8. CONCEPTUAL AND METHODOLOGICAL MISTAKES IN PSYCHOLOGY AND HEALTH: A CASE STUDY ON THE USE AND ABUSE OF STRUCTURAL EQUATION MODELLING

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    Julio Alfonso Piña López

    2016-09-01

    Full Text Available In this article, a research paper is analysed, which was justified based on the theory of developmental psychopathology, the protective factors, self-regulation, resilience, and quality of life among individuals who lived with type 2 diabetes and hypertension. Structural equation modelling (SEM was used for the data analysis. Although the authors conclude that the data are adequate to the theory tested, they commit errors of logic, concept, methodology and interpretation which, taken together, demonstrate a flagrant rupture between the theory and the data.

  9. Linking Resource-Based Strategies to Customer-Focused Performance for Professional Services: A Structural Equation Modelling Approach

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    Ming-Lu Wu

    2013-12-01

    Full Text Available This paper links professional service firms’ resource-based strategies to their customer-focused performance for formulating service quality improvement priorities. The research applies the structural equation modelling approach to survey data from Hong Kong construction consultants to test some hypotheses. The study validates the various measures of firms’ resource-based strategies and customer-focused performance and bridges the gaps in firms’ organizational learning, core competences and customer-focused performance mediated by their strategic flexibility. The research results have practical implications for professional service firms to deploy resources appropriately to first enhance different competences and then improve customerfocused performance using their different competences.

  10. Gratitude mediates the effect of emotional intelligence on subjective well-being: A structural equation modeling analysis.

    Science.gov (United States)

    Geng, Yuan

    2016-11-03

    This study investigated the relationship among emotional intelligence, gratitude, and subjective well-being in a sample of university students. A total of 365 undergraduates completed the emotional intelligence scale, the gratitude questionnaire, and the subjective well-being measures. The results of the structural equation model showed that emotional intelligence is positively associated with gratitude and subjective well-being, that gratitude is positively associated with subjective well-being, and that gratitude partially mediates the positive relationship between emotional intelligence and subjective well-being. Bootstrap test results also revealed that emotional intelligence has a significant indirect effect on subjective well-being through gratitude.

  11. Generalization of the effects of phonological training for anomia using structural equation modelling: a multiple single-case study.

    Science.gov (United States)

    Vitali, P; Tettamanti, M; Abutalebi, J; Ansaldo, A-I; Perani, D; Cappa, S F; Joanette, Y

    2010-04-01

    Structural Equation Modelling analysis of three longitudinal er-fMRI sessions was used to test the impact of phonological training and of the generalization process on the pattern of brain connectivity during overt picture naming in two chronic anomic patients. Phonological training yielded a positive effect on the trained material. Six months after the training, a generalization of the positive impact on the untrained items was also observed. Connectivity analysis showed that training and generalization effects shared paralleled cortical patterns of functional integration. These findings may represent the neurophysiological correlate of the training-induced cognitive strategies for the compensation of anomia.

  12. Relationships between negative affectivity, emotion regulation, anxiety, and depressive symptoms in adolescents as examined through structural equation modeling.

    Science.gov (United States)

    Tortella-Feliu, Miquel; Balle, Maria; Sesé, Albert

    2010-10-01

    The relationship between negative affectivity (NA) and emotion regulation (ER) in determining anxiety and depressive symptomatology was examined in a large (n=1441) sample of adolescents (12-17 years old). Two models, diverging only as to inclusion or exclusion of a path from NA to negative ER, were analyzed through structural equation modeling; the goal was to explore the mediational or non-mediational role of ER in determining anxiety symptoms. The models yielded similar adequate fit to data, indicating that both NA and negative ER contribute to anxiety symptoms which, in turn, significantly determine depressive symptomatology. The mediational model better captures the relationships revealed in the data, with NA determining negative ER to a great extent. Additionally, most individuals scoring highly in NA also tend to score highly in negative ER, indicating that adolescents with heightened NA are prone to a dysfunctional style of ER.

  13. An in-depth discussion and illustration of partial least squares structural equation modeling in health care.

    Science.gov (United States)

    Avkiran, Necmi Kemal

    2017-02-08

    Partial least squares structural equation modeling (PLS-SEM) has become more popular across many disciplines including health care. However, articles in health care often fail to discuss the choice of PLS-SEM and robustness testing is not undertaken. This article presents the steps to be followed in a thorough PLS-SEM analysis, and includes a conceptual comparison of PLS-SEM with the more traditional covariance-based structural equation modeling (CB-SEM) to enable health care researchers and policy makers make appropriate choices. PLS-SEM allows for critical exploratory research to lay the groundwork for follow-up studies using methods with stricter assumptions. The PLS-SEM analysis is illustrated in the context of residential aged care networks combining low-level and high-level care. Based on the illustrative setting, low-level care does not make a significant contribution to the overall quality of care in residential aged care networks. The article provides key references from outside the health care literature that are often overlooked by health care articles. Choosing between PLS-SEM and CB-SEM should be based on data characteristics, sample size, the types and numbers of latent constructs modelled, and the nature of the underlying theory (exploratory versus advanced). PLS-SEM can become an indispensable tool for managers, policy makers and regulators in the health care sector.

  14. Structural Equation Modeling of Classification Managers Based on the Communication Skills and Cultural Intelligence in Sport Organizations

    Directory of Open Access Journals (Sweden)

    Rasool NAZARI

    2015-03-01

    Full Text Available The purpose of this research is to develop structural equation model category managers on communication skills and cultural intelligence agencies had Isfahan Sports. Hence study was of structural equation modeling. The statistical population of this research formed the provincial sports administrators that according formal statistical was 550 people. Research sample size the sample of 207subjects was randomly selected. Cochran's sample size formula was used to determine. Measuring research and Communication Skills (0.81, Cultural Intelligence Scale (0.85 category manager's questionnaire (0.86, respectively. For analysis descriptive and inferential statistics SPSS and LISREL was used. Model results, communication skills, cultural intelligence and athletic directors classification of the fit was good (RMSEA=0.037, GFI= 0.902, AGFI= 0.910, NFT= 0.912. The prerequisite for proper planning to improve communication skills and cultural intelligence managers as influencing exercise essential while the authorial shave the right to choose directors analyst and intuitive strategies for management position shave because it looks better with the managers can be expected to exercise a clearer perspective.

  15. Psychological model of ART adherence behaviors in persons living with HIV/AIDS in Mexico: a structural equation analysis

    Science.gov (United States)

    Sagarduy, José Luis Ybarra; López, Julio Alfonso Piña; Ramírez, Mónica Teresa González; Dávila, Luis Enrique Fierros

    2017-01-01

    ABSTRACT OBJECTIVE The objective of this study has been to test the ability of variables of a psychological model to predict antiretroviral therapy medication adherence behavior. METHODS We have conducted a cross-sectional study among 172 persons living with HIV/AIDS (PLWHA), who completed four self-administered assessments: 1) the Psychological Variables and Adherence Behaviors Questionnaire, 2) the Stress-Related Situation Scale to assess the variable of Personality, 3) The Zung Depression Scale, and 4) the Duke-UNC Functional Social Support Questionnaire. Structural equation modeling was used to construct a model to predict medication adherence behaviors. RESULTS Out of all the participants, 141 (82%) have been considered 100% adherent to antiretroviral therapy. Structural equation modeling has confirmed the direct effect that personality (decision-making and tolerance of frustration) has on motives to behave, or act accordingly, which was in turn directly related to medication adherence behaviors. In addition, these behaviors have had a direct and significant effect on viral load, as well as an indirect effect on CD4 cell count. The final model demonstrates the congruence between theory and data (x 2/df. = 1.480, goodness of fit index = 0.97, adjusted goodness of fit index = 0.94, comparative fit index = 0.98, root mean square error of approximation = 0.05), accounting for 55.7% of the variance. CONCLUSIONS The results of this study support our theoretical model as a conceptual framework for the prediction of medication adherence behaviors in persons living with HIV/AIDS. Implications for designing, implementing, and evaluating intervention programs based on the model are to be discussed. PMID:28876412

  16. Structural Equation Modeling of Cultural Competence of Nurses Caring for Foreign Patients.

    Science.gov (United States)

    Ahn, Jung-Won

    2017-03-01

    This study aimed to construct and test a hypothetical model including factors related to the cultural competence of nurses caring for foreign patients. The transcultural nursing immersion experience model and anxiety/uncertainty management theory were used to verify the paths between the variables. The exogenous variables were multicultural experience, ethnocentric attitude, and organizational cultural competence support. The endogenous variables were intercultural anxiety, intercultural uncertainty, coping strategy, and cultural competence. Participants were 275 nurses working in general hospitals in Seoul and Kyung-Gi Do, Korea. Each nurse in this study had experience of caring for over 10 foreign patients. Data were collected using a structured questionnaire and analyzed with SPSS statistical software with the added AMOS module. The overall fitness indices of the hypothetical model were a good fit. Multicultural experience, ethnocentric attitude, organizational cultural competence support, and intercultural uncertainty were found to have a direct and indirect effect on the cultural competence of nurses while coping strategy only had a direct effect. Intercultural anxiety did not have a significant effect on cultural competence. This model explained 59.1% of the variance in the nurses' cultural competence when caring for foreign patients. Nurses' cultural competence can be developed by offering multicultural nursing education, increasing direct/indirect multicultural experience, and sharing problem-solving experience to promote the coping ability of nurses. Organizational support can be achieved by preparing relevant personnel and resources. Subsequently, the quality of nursing care for foreign patients' will be ultimately improved. Copyright © 2017. Published by Elsevier B.V.

  17. Brain Emotion Systems, Personality, Hopelessness, Self/Other Perception, and Gambling Cognition: A Structural Equation Model.

    Science.gov (United States)

    Iliceto, Paolo; D'Antuono, Laura; Bowden-Jones, Henrietta; Giovani, Eleni; Giacolini, Teodosio; Candilera, Gabriella; Sabatello, Ugo; Panksepp, Jaak

    2016-03-01

    The aim of this study was to explore the relations between gambling, brain emotion systems, personality, self/other perception, and hopelessness in an Italian community. Dimensions of gambling, positive and negative emotions, self/other perception, personality and hopelessness were assessed in a community sample of 235 adults aged 19-59 years. Two structural models were tested. We found a significant correlation between problem gambling and impulsivity, which in association with aggressivity and negative personality dimensions may help explain the psychopathology factor, i.e. a latent variable involving neurotic personality, hopelessness, high sensation seeking, low metacognitive responsiveness, and disorganized patterns of interpersonal relationships. These results contribute to develop a theoretical framework of gambling in relation with personality factors and provide a new approach for clinical intervention of problem gambling that relies on a solid multidimensional perspective.

  18. Multivariate determinants of self-management in Health Care: assessing Health Empowerment Model by comparison between structural equation and graphical models approaches

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    Filippo Trentini

    2015-03-01

    Full Text Available Backgroung. In public health one debated issue is related to consequences of improper self-management in health care.  Some theoretical models have been proposed in Health Communication theory which highlight how components such general literacy and specific knowledge of the disease might be very important for effective actions in healthcare system.  Methods. This  paper aims at investigating the consistency of Health Empowerment Model by means of both graphical models approach, which is a “data driven” method and a Structural Equation Modeling (SEM approach, which is instead “theory driven”, showing the different information pattern that can be revealed in a health care research context.The analyzed dataset provides data on the relationship between the Health Empowerment Model constructs and the behavioral and health status in 263 chronic low back pain (cLBP patients. We used the graphical models approach to evaluate the dependence structure in a “blind” way, thus learning the structure from the data.Results. From the estimation results dependence structure confirms links design assumed in SEM approach directly from researchers, thus validating the hypotheses which generated the Health Empowerment Model constructs.Conclusions. This models comparison helps in avoiding confirmation bias. In Structural Equation Modeling, we used SPSS AMOS 21 software. Graphical modeling algorithms were implemented in a R software environment.

  19. A Multigroup Structural Equation Modeling Approach To Test for Differences in the Educational Outcomes Process for African American Students from Different Socioeconomic Backgrounds.

    Science.gov (United States)

    Grosset, Jane M.

    This research tested a structural equation model of educational outcomes for three socioeconomic status (SES) groups of African-American students enrolled in a community college (total sample of 315). The structural model, which was based on a variant of Tinto's (1987) model, contained two exogenous constructs, educational intentions and…

  20. Nurse characteristics, leadership, safety climate, emotional labour and intention to stay for nurses: a structural equation modelling approach.

    Science.gov (United States)

    Liang, Hui-Yu; Tang, Fu-In; Wang, Tze-Fang; Lin, Kai-Ching; Yu, Shu

    2016-12-01

    The aim of this study was to propose a theoretical model and apply it to examine the structural relationships among nurse characteristics, leadership characteristics, safety climate, emotional labour and intention to stay for hospital nurses. Global nursing shortages negatively affect the quality of care. The shortages can be reduced by retaining nurses. Few studies have independently examined the relationships among leadership, safety climate, emotional labour and nurses' intention to stay; more comprehensive theoretical foundations for examining nurses' intention to stay and its related factors are lacking. Cross-sectional. A purposive sample of 414 full-time nurses was recruited from two regional hospitals in Taiwan. A structured questionnaire was used to collect data from November 2013-June 2014. Structural equation modelling was employed to test the theoretical models of the relationships among the constructs. Our data supported the theoretical model. Intention to stay was positively correlated with age and the safety climate, whereas working hours per week and emotional labour were negatively correlated. The nursing position and transformational leadership indirectly affected intention to stay; this effect was mediated separately by emotional labour and the safety climate. Our data supported the model fit. Our findings provide practical implications for healthcare organizations and administrators to increase nurses' intent to stay. Strategies including a safer climate, appropriate working hours and lower emotional labour can directly increase nurses' intent to stay. Transformational leadership did not directly influence nurses' intention to stay; however, it reduced emotional labour, thereby increasing intention to stay. © 2016 John Wiley & Sons Ltd.

  1. An exploration of socioeconomic variation in lifestyle factors and adiposity in the Ontario Food Survey through structural equation modeling

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    Mendelson Rena

    2007-03-01

    Full Text Available Abstract Title An exploration of socioeconomic variation in lifestyle factors and adiposity in the Ontario Food Survey through structural equation models. Background Socioeconomic indicators have been inversely associated with overweight and obesity, with stronger associations observed among women. The objective of the present secondary analysis was to examine the relationships among socioeconomic measures and adiposity for men and women participating in the Ontario Food Survey (OFS, and to explore lifestyle factors as potential mediators of these associations. Methods The cross-sectional 1997/98 OFS collected anthropometric measurements, a food frequency questionnaire, data on socio-demographics (age, sex, income, and education and physical activity from 620 women and 467 men, ages 18 to 75. Based on the 2003 Health Canada guidelines, waist circumference and BMI values were used to derive least risk, increased risk, and high risk adiposity groups. Structural equation modeling was conducted to examine increased risk and high risk adiposity in relation to education and income, with leisure time physical activity, fruit and vegetable intake, and smoking status included as potential mediators of these associations. Results The probability of high risk adiposity was directly associated with education (β-0.19, p Conclusion The socioeconomic context of adiposity continues to differ greatly between men and women. For women only in the OFS, fruit and vegetable intake contributed to the inverse association between education and high risk adiposity; however, additional explanatory factors are yet to be determined.

  2. Structural equation modeling and nested ANOVA: Effects of lead exposure on maternal and fetal growth in rats

    Energy Technology Data Exchange (ETDEWEB)

    Hamilton, J.D. (Rohm and Haas Company, Spring House, PA (United States)); O' Flaherty, E.J.; Shukla, R.; Gartside, P.S. (Univ. of Cincinnati, OH (United States)); Ross, R. (Univ. of Cincinnati Medical Center, Cincinnati, OH (United States))

    1994-01-01

    This study provided an assessment of the effects of lead on early growth in rats based on structural equation modeling and nested analysis of variance (ANOVA). Structural equation modeling showed that lead in drinking water (250, 500, or 1000 ppm) had a direct negative effect on body weight and tail length (i.e., growth) in female rats during the first week of exposure. During the following 2 weeks of exposure, high correlation between growth measurements taken over time resulted in reduced early postnatal growth. By the fourth week of exposure, reduced growth was not evident. Mating began after 8 weeks of exposure, and exposure continued during gestation. Decreased fetal body weight was detected when the effects of litter size, intrauterine position, and sex were controlled in a nested ANOVA. Lead exposure did not appear to affect fetal skeletal development, possibly because lead did not alter maternal serum calcium and phosphorus levels. The effect of lead on individual fetal body weight suggests that additional studies are needed to examine the effect of maternal lead exposure on fetal development and early postnatal growth. 24 refs., 4 figs., 6 tabs.

  3. [Bridge employment and retirees' personal well-being. A structural equation model with a European probabilistic sample].

    Science.gov (United States)

    Topa Cantisano, Gabriela; Depolo, Marco; Moriano León, Juan A; Morales Domínguez, José F

    2009-05-01

    The aim of this paper is twofold: first, to examine the relationships between antecedents and consequences of bridge employment activity; second, to analyze the mediator role both of quality and quantity of bridge employment activities in the relationship between antecedents and consequences. First wave panel data from the SHARE (Survey of Health, Ageing and Retirement in Europe) were obtained from 1190 men and women in Europe, using structured interviews and questionnaires. Structural equation modeling analyses, including the sample without missing values (N=650), showed that both quantity and quality of bridge employment participation are predictors of job satisfaction, life satisfaction, and quality of life in retirement. These results validate and expand the previous research on bridge employment activities and partial retirement.

  4. Effects of Socioeconomic Status and Social Support on Violence against Pregnant Women: A Structural Equation Modeling Analysis

    Science.gov (United States)

    Schraiber, Lilia Blima; Bettiol, Heloisa; Barbieri, Marco Antônio

    2017-01-01

    Few studies have used structural equation modeling to analyze the effects of variables on violence against women. The present study analyzed the effects of socioeconomic status and social support on violence against pregnant women who used prenatal services. This was a cross-sectional study based on data from the Brazilian Ribeirão Preto and São Luís birth cohort studies (BRISA). The sample of the municipality of São Luís (Maranhão/Brazil) consisted of 1,446 pregnant women interviewed in 2010 and 2011. In the proposed model, socioeconomic status was the most distal predictor, followed by social support that determined general violence, psychological violence or physical/sexual violence, which were analyzed as latent variables. Violence was measured by the World Health Organization Violence against Women (WHO VAW) instrument. The São Luis model was estimated using structural equation modeling and validated with 1,378 pregnant women from Ribeirão Preto (São Paulo/Brazil). The proposed model showed good fit for general, psychological and physical/sexual violence for the São Luís sample. Socioeconomic status had no effect on general or psychological violence (p>0.05), but pregnant women with lower socioeconomic status reported more episodes of physical/sexual violence (standardized coefficient, SC = -0.136; p = 0.021). This effect of socioeconomic status was indirect and mediated by low social support (SC = -0.075; psexual violence (psexual violence was more common for pregnant women with lower socioeconomic status and lower social support. Better social support contributed to reduction of all types of violence. Results were nearly the same for the validation sample of Ribeirão Preto except that SES was not associated with physical/sexual violence. PMID:28107428

  5. Effects of Socioeconomic Status and Social Support on Violence against Pregnant Women: A Structural Equation Modeling Analysis.

    Science.gov (United States)

    Ribeiro, Marizélia Rodrigues Costa; Silva, Antônio Augusto Moura da; Alves, Maria Teresa Seabra Soares de Britto E; Batista, Rosângela Fernandes Lucena; Ribeiro, Cecília Cláudia Costa; Schraiber, Lilia Blima; Bettiol, Heloisa; Barbieri, Marco Antônio

    2017-01-01

    Few studies have used structural equation modeling to analyze the effects of variables on violence against women. The present study analyzed the effects of socioeconomic status and social support on violence against pregnant women who used prenatal services. This was a cross-sectional study based on data from the Brazilian Ribeirão Preto and São Luís birth cohort studies (BRISA). The sample of the municipality of São Luís (Maranhão/Brazil) consisted of 1,446 pregnant women interviewed in 2010 and 2011. In the proposed model, socioeconomic status was the most distal predictor, followed by social support that determined general violence, psychological violence or physical/sexual violence, which were analyzed as latent variables. Violence was measured by the World Health Organization Violence against Women (WHO VAW) instrument. The São Luis model was estimated using structural equation modeling and validated with 1,378 pregnant women from Ribeirão Preto (São Paulo/Brazil). The proposed model showed good fit for general, psychological and physical/sexual violence for the São Luís sample. Socioeconomic status had no effect on general or psychological violence (p>0.05), but pregnant women with lower socioeconomic status reported more episodes of physical/sexual violence (standardized coefficient, SC = -0.136; p = 0.021). This effect of socioeconomic status was indirect and mediated by low social support (SC = -0.075; pviolence (pviolence indistinctly affected pregnant women of different socioeconomic status. Physical/sexual violence was more common for pregnant women with lower socioeconomic status and lower social support. Better social support contributed to reduction of all types of violence. Results were nearly the same for the validation sample of Ribeirão Preto except that SES was not associated with physical/sexual violence.

  6. Exploratory structural equation modeling, bifactor models, and standard confirmatory factor analysis models: application to the BASC-2 Behavioral and Emotional Screening System Teacher Form.

    Science.gov (United States)

    Wiesner, Margit; Schanding, G Thomas

    2013-12-01

    Several psychological assessment instruments are based on the assumption of a general construct that is composed of multiple interrelated domains. Standard confirmatory factor analysis is often not well suited for examining the factor structure of such scales. This study used data from 1885 elementary school students (mean age=8.77 years, SD=1.47 years) to examine the factor structure of the Behavioral Assessment System for Children, Second Edition (BASC-2) Behavioral and Emotional Screening System (BESS) Teacher Form that was designed to assess general risk for emotional/behavioral difficulty among children. The modeling sequence included the relatively new exploratory structural equation modeling (ESEM) approach and bifactor models in addition to more standard techniques. Findings revealed that the factor structure of the BASC-2 BESS Teacher Form is multidimensional. Both ESEM and bifactor models showed good fit to the data. Bifactor models were preferred on conceptual grounds. Findings illuminate the hypothesis-generating power of ESEM and suggest that it might not be optimal for instruments designed to assess a predominant general factor underlying the data.

  7. Doubly-Latent Models of School Contextual Effects: Integrating Multilevel and Structural Equation Approaches to Control Measurement and Sampling Error.

    Science.gov (United States)

    Marsh, Herbert W; Lüdtke, Oliver; Robitzsch, Alexander; Trautwein, Ulrich; Asparouhov, Tihomir; Muthén, Bengt; Nagengast, Benjamin

    2009-11-30

    This article is a methodological-substantive synergy. Methodologically, we demonstrate latent-variable contextual models that integrate structural equation models (with multiple indicators) and multilevel models. These models simultaneously control for and unconfound measurement error due to sampling of items at the individual (L1) and group (L2) levels and sampling error due the sampling of persons in the aggregation of L1 characteristics to form L2 constructs. We consider a set of models that are latent or manifest in relation to sampling items (measurement error) and sampling of persons (sampling error) and discuss when different models might be most useful. We demonstrate the flexibility of these 4 core models by extending them to include random slopes, latent (single-level or cross-level) interactions, and latent quadratic effects. Substantively we use these models to test the big-fish-little-pond effect (BFLPE), showing that individual student levels of academic self-concept (L1-ASC) are positively associated with individual level achievement (L1-ACH) and negatively associated with school-average achievement (L2-ACH)-a finding with important policy implications for the way schools are structured. Extending tests of the BFLPE in new directions, we show that the nonlinear effects of the L1-ACH (a latent quadratic effect) and the interaction between gender and L1-ACH (an L1 × L1 latent interaction) are not significant. Although random-slope models show no significant school-to-school variation in relations between L1-ACH and L1-ASC, the negative effects of L2-ACH (the BFLPE) do vary somewhat with individual L1-ACH. We conclude with implications for diverse applications of the set of latent contextual models, including recommendations about their implementation, effect size estimates (and confidence intervals) appropriate to multilevel models, and directions for further research in contextual effect analysis.

  8. Structural equation modeling for decomposing rank-dependent indicators of socioeconomic inequality of health: an empirical study.

    Science.gov (United States)

    Kessels, Roselinde; Erreygers, Guido

    2016-12-01

    We present a flexible structural equation modeling (SEM) framework for the regression-based decomposition of rank-dependent indicators of socioeconomic inequality of health and compare it with simple ordinary least squares (OLS) regression. The SEM framework forms the basis for a proper use of the most prominent one- and two-dimensional decompositions and provides an argument for using the bivariate multiple regression model for two-dimensional decomposition. Within the SEM framework, the two-dimensional decomposition integrates the feedback mechanism between health and socioeconomic status and allows for different sets of determinants of these variables. We illustrate the SEM approach and its outperformance of OLS using data from the 2011 Ethiopian Demographic and Health Survey.

  9. Managing Transportation Megaproject Schedule Risks Using Structural Equation Modelling: A Case Study of Shanghai Hongqiao Integrated Transport Hub in China

    Directory of Open Access Journals (Sweden)

    Peng Wei

    2016-01-01

    Full Text Available Tight schedules, multifunctional scopes, and colossal sizes usually characterize transportation megaprojects as challenging tasks for completion. In order to address these situations, a schedule risk management method was developed in this paper based on the structural equation model. In the proposed method, risk identification, evaluation and response were arranged as a sequence, and the expert elicitation technique was adopted in order to quantify the schedule risk status. To demonstrate the applicability of the proposed model, a megaproject case in China, the Shanghai Hongqiao Integrated Transport Hub (SHITH, was chosen. Information within the expanded risk register was collected including the probability and consequence of risk events, the complexity of risk responsible owners, the reaction time, and the time lasting for risk countermeasures. Final risk control results showed that the method could not only address the schedule risks correlations effectively, but also maintained the simplicity for construction management practices.

  10. Analyzing the Influence of Internal Marketing on Organizational Performance in Travel Agencies of Tehran Using Structural Equation Modeling

    Directory of Open Access Journals (Sweden)

    Yaghoub Hossainee

    2012-06-01

    Full Text Available Employees are one of the most critical elements of service organizations. They play an important role in delivering service to customers. Implementing an internal marketing plan leads to training, motivating and directing personnel and their higher satisfaction. Therefore, they can be able to provide higher quality of services to customers. They ultimately enhance performance in service organizations. This subject is critically important and therefore, it this research an attempt has been made to determine main elements of internal marketing and to investigate its influence on organizational performance. For this purpose, a questionnaire has been developed and distributed to 72 managers and employees of travel agencies. The collected data has been analyzed using Structural Equation Modeling and Amos software. In this research, internal marketing is the independent variable and organizational performance is the dependent variable. Findings of research confirm the conceptual model. Findings indicate that internal marketing has direct and positive influence on organizational performance.

  11. Analyzing the Influence of Internal Marketing on Organizational Performance in Ttravel Agencies of Tehran Using Structural Equation Modeling

    Directory of Open Access Journals (Sweden)

    Seyed Yaghoub Hosseini

    2012-01-01

    Full Text Available Employees are one of the most critical elements of service organizations. They play an important role in delivering service to customers. Implementing an internal marketing plan leads to training, motivating and directing personnel and their higher satisfaction. Therefore, they can be able to provide higher quality of services to customers. They ultimately enhance performance in service organizations. This subject is critically important and therefore, it this research an attempt has been made to determine main elements of internal marketing and to investigate its influence on organizational performance. For this purpose, a questionnaire has been developed and distributed to 72 managers and employees of travel agencies. The collected data has been analyzed using Structural Equation Modeling and Amos software. In this research, internal marketing is the independent variable and organizational performance is the dependent variable. Findings of research confirm the conceptual model. Findings indicate that internal marketing has direct and positive influence on organizational performance.

  12. Two-Equation Turbulence Model

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    Vijay K. Garg

    1998-01-01

    reason for the discrepancy on the pressure surface could be the presence of unsteady effects due to stator-rotor interaction in the experiments which are not modeled in the present computations. Prediction using the two-equation model is in general poorer than that using the zero-equation model, while the former requires at least 40% more computational resources.

  13. A Commentary on the Relationship between Model Fit and Saturated Path Models in Structural Equation Modeling Applications

    Science.gov (United States)

    Raykov, Tenko; Lee, Chun-Lung; Marcoulides, George A.; Chang, Chi

    2013-01-01

    The relationship between saturated path-analysis models and their fit to data is revisited. It is demonstrated that a saturated model need not fit perfectly or even well a given data set when fit to the raw data is examined, a criterion currently frequently overlooked by researchers utilizing path analysis modeling techniques. The potential of…

  14. Examining the Relationships among Antecedents of Guests’ Behavioural Intentions in Ghana’s Hospitality Industry: A Structural Equation Modelling Approach

    Directory of Open Access Journals (Sweden)

    Simon Gyasi Nimako

    2013-04-01

    Full Text Available This study empirically examines the critical antecedents of behavioural intentions and the structural interrelationships that exist among the antecedents in the hotel industry in Ghana. The study was a cross-sectional survey of 700 respondents using structured questionnaire personally administered. A usable 359 questionnaire were obtained, representing 51.3% response rate and analysed using Structural Equation Modelling approach. The findings indicate that the proposed model has high goodness-of-fit indices and explains 89.5 and 91% of the two behavioural intention variables loyalty and Positive Word of Mouth Communication (PWOMC respectively. It also found that loyalty could be influenced through PWOMC, customer satisfaction, perceived service quality, perceived value and perceived quality of ambient factors, whereas PWOMC was influenced by satisfaction, perceived value and perceived quality of Ambient factors. Theoretically, the study fills the dearth of conceptual models in understanding the critical determinants of BI in the hotel sector in developing country context. It also provides important implications for marketing management in hotel industry. Limitations of the study are noted and recommendations for future research have been suggested. This study contributes to the body of knowledge in the area of consumer loyalty in the hospitality industry.

  15. Effects of environmental levels of cadmium, lead and mercury on human renal function evaluated by structural equation modeling.

    Science.gov (United States)

    Trzeciakowski, Jerome P; Gardiner, Lesley; Parrish, Alan R

    2014-07-03

    A relationship between exposure to heavy metals, including lead and cadmium, and renal dysfunction has long been suggested. However, modeling of the potential additive, or synergistic, impact of metals on renal dysfunction has proven to be challenging. In these studies, we used structural equation modeling (SEM), to investigate the relationship between heavy metal burden (serum and urine levels of lead, cadmium and mercury) and renal function using data from the NHANES database. We were able to generate a model with goodness of fit indices consistent with a well-fitting model. This model demonstrated that lead and cadmium had a negative relationship with renal function, while mercury did not contribute to renal dysfunction. Interestingly, a linear relationship between lead and loss of renal function was observed, while the maximal impact of cadmium occurred at or above serum cadmium levels of 0.8 μg/L. The interaction of lead and cadmium in loss of renal function was also observed in the model. These data highlight the use of SEM to model interaction between environmental contaminants and pathophysiology, which has important implications in mechanistic and regulatory toxicology.

  16. Examining the Support Peer Supporters Provide Using Structural Equation Modeling: Nondirective and Directive Support in Diabetes Management.

    Science.gov (United States)

    Kowitt, Sarah D; Ayala, Guadalupe X; Cherrington, Andrea L; Horton, Lucy A; Safford, Monika M; Soto, Sandra; Tang, Tricia S; Fisher, Edwin B

    2017-04-17

    Little research has examined the characteristics of peer support. Pertinent to such examination may be characteristics such as the distinction between nondirective support (accepting recipients' feelings and cooperative with their plans) and directive (prescribing "correct" choices and feelings). In a peer support program for individuals with diabetes, this study examined (a) whether the distinction between nondirective and directive support was reflected in participants' ratings of support provided by peer supporters and (b) how nondirective and directive support were related to depressive symptoms, diabetes distress, and Hemoglobin A1c (HbA1c). Three hundred fourteen participants with type 2 diabetes provided data on depressive symptoms, diabetes distress, and HbA1c before and after a diabetes management intervention delivered by peer supporters. At post-intervention, participants reported how the support provided by peer supporters was nondirective or directive. Confirmatory factor analysis (CFA), correlation analyses, and structural equation modeling examined the relationships among reports of nondirective and directive support, depressive symptoms, diabetes distress, and measured HbA1c. CFA confirmed the factor structure distinguishing between nondirective and directive support in participants' reports of support delivered by peer supporters. Controlling for demographic factors, baseline clinical values, and site, structural equation models indicated that at post-intervention, participants' reports of nondirective support were significantly associated with lower, while reports of directive support were significantly associated with greater depressive symptoms, altogether (with control variables) accounting for 51% of the variance in depressive symptoms. Peer supporters' nondirective support was associated with lower, but directive support was associated with greater depressive symptoms.

  17. The application of a social cognition model in explaining fruit intake in Austrian, Norwegian and Spanish schoolchildren using structural equation modelling

    Directory of Open Access Journals (Sweden)

    Pérez-Rodrigo Carmen

    2007-11-01

    Full Text Available Abstract Background The aim of this paper was to test the goodness of fit of the Attitude – Social influence – self-Efficacy (ASE model in explaining schoolchildren's intentions to eat fruit and their actual fruit intake in Austria, Norway and Spain; to assess how well the model could explain the observed variance in intention to eat fruit and in reported fruit intake and to investigate whether the same model would fit data from all three countries. Methods Samples consisted of schoolchildren from three of the countries participating in the cross-sectional part of the Pro Children project. Sample size varied from 991 in Austria to 1297 in Spain. Mean age ranged from 11.3 to 11.4 years. The initial model was designed using items and constructs from the Pro Children study. Factor analysis was conducted to test the structure of the measures in the model. The Norwegian sample was used to test the latent variable structure, to make a preliminary assessment of model fit, and to modify the model to increase goodness of fit with the data. The original and modified models were then applied to the Austrian and Spanish samples. All model analyses were carried out using structural equation modelling techniques. Results The ASE-model fitted the Norwegian and Spanish data well. For Austria, a slightly more complex model was needed. For this reason multi-sample analysis to test equality in factor structure and loadings across countries could not be used. The models explained between 51% and 69% of the variance in intention to eat fruit, and 27% to 38% of the variance in reported fruit intake. Conclusion Structural equation modelling showed that a rather parsimonious model was useful in explaining the variation in fruit intake of 11-year-old schoolchildren in Norway and Spain. For Austria, more modifications were needed to fit the data.

  18. Investigating the Relationships among Stressors, Stress Level, and Mental Symptoms for Infertile Patients: A Structural Equation Modeling Approach.

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    Jong-Yi Wang

    Full Text Available Patients with infertility are a high risk group in depression and anxiety. However, an existing theoretically and empirically validated model of stressors, stress, and mental symptoms specific for infertile patients is still a void. This study aimed to determine the related factors and their relational structures that affect the level of depressive and anxiety symptoms among infertile patients.A cross-sectional sample of 400 infertility outpatients seeking reproduction treatments in three teaching hospitals across Taiwan participated in the structured questionnaire survey in 2011. The hypothesized model comprising 10 latent variables was tested by Structural Equation Modeling using AMOS 17.Goodness-of-fit indexes, including χ2/DF = 1.871, PGFI = 0.746, PNFI = 0.764, and others, confirmed the modified model fit the data well. Marital stressor, importance of children, guilt-and-blame, and social stressor showed a direct effect on perceived stress. Instead of being a factor of stress, social support was directly and positively related to self-esteem. Perceived stress and self-esteem were the two major mediators for the relationships between stressors and mental symptoms. Increase in social support and self-esteem led to decrease in mental symptoms among the infertile patients.The relational structures were identified and named as the Stressors Stress Symptoms Model, clinically applied to predict anxiety and depression from various stressors. Assessing sources and level of infertility-related stress and implementing culturally-sensitive counseling with an emphasis on positive personal value may assist in preventing the severity of depression and anxiety.

  19. Modified Heisenberg Ferromagnet Model and Integrable Equation

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    We investigate some integrable modified Heisenberg ferromagnet models by using the prolongation structure theory. Through associating them with the motion of curve in Minkowski space, the corresponding coupled integrable equations are presented.

  20. Latent variable models an introduction to factor, path, and structural equation analysis

    CERN Document Server

    Loehlin, John C

    2004-01-01

    This fourth edition introduces multiple-latent variable models by utilizing path diagrams to explain the underlying relationships in the models. The book is intended for advanced students and researchers in the areas of social, educational, clinical, ind

  1. APLIKASI STRUCTURAL EQUATION MODEL (SEM DALAM PENENTUAN ALTERNATIF PENGELOLAAN LINGKUNGAN INDUSTRI KOMPONEN ALAT BERAT BERBASIS PARTISIPASI DAN KEMITRAAN MASYARAKAT

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    Budi Setyo Utomo

    2012-07-01

    Full Text Available As a company engaged in the industrial sector by producing certain components and localized in an industrial area, there will be an impact on the environment. These impacts can be positive in the form of employment, reducing dependence on imported heavy equipment, increase in foreign exchange due to reduced imports and increased exports, increased government revenue from taxes, public facilities improvement and supporting infrastructure, and opening up opportunities for other related industries. These impacts can also be negative in the form of environmental degradation such as noise disturbance, dust, and micro climate change, and changes in social and cultural conditions surrounding the industry. Data analysis was performed descriptively and with the Structural Equation Model (SEM. SEM is a multivariate statistical technique which is a combination of factor analysis and regression analysis (correlation, which aims to test the connections between existing variables in a model, whether it is between the indicator with the construct, or the connections between constructs. SEM model consists of two parts, which is the latent variable model and the observed variable model. In contrast to ordinary regression linking the causality between the observed variables, it is also possible in SEM to identify the causality between latent variables. The results of SEM analysis showed that the developed model has a fairly high level of validity that is shown by the minimum fit chi-square value of 93.15 (P = 0.00029. Based on said model, it shows that the company's performance in waste management is largely determined by employee integrity and objectivity of the new employees followed later by the independence of the employees in waste management. The most important factor that determines the employee integrity in waste management in the model is honesty, individual wisdom, and a sense of responsibility. The most important factor in the employee objectivity

  2. A study of Korean students' creativity in science using structural equation modeling

    Science.gov (United States)

    Jo, Son Mi

    creativity. The strength of relationships between scientific proficiency and scientific creativity (estimate parameter=0.43) and creative competence and scientific creativity (estimate parameter=0.17) are similar [chi2.05(1)=0.670, P>.05]. In specific analysis of structural model, I found that creative competence and scientific proficiency play a role of partial mediators among three components (general creativity, scientific proficiency, and scientific creativity). The moderate effects of intrinsic motivation and context component were investigated, but the moderation effects were not found.

  3. Modelling conjugation with stochastic differential equations.

    Science.gov (United States)

    Philipsen, K R; Christiansen, L E; Hasman, H; Madsen, H

    2010-03-07

    Conjugation is an important mechanism involved in the transfer of resistance between bacteria. In this article a stochastic differential equation based model consisting of a continuous time state equation and a discrete time measurement equation is introduced to model growth and conjugation of two Enterococcus faecium strains in a rich exhaustible media. The model contains a new expression for a substrate dependent conjugation rate. A maximum likelihood based method is used to estimate the model parameters. Different models including different noise structure for the system and observations are compared using a likelihood-ratio test and Akaike's information criterion. Experiments indicating conjugation on the agar plates selecting for transconjugants motivates the introduction of an extended model, for which conjugation on the agar plate is described in the measurement equation. This model is compared to the model without plate conjugation. The modelling approach described in this article can be applied generally when modelling dynamical systems.

  4. The Relationships between Individualism, Nationalism, Ethnocentrism, and Authoritarianism in Flanders: A Continuous Time-Structural Equation Modeling Approach.

    Science.gov (United States)

    Angraini, Yenni; Toharudin, Toni; Folmer, Henk; Oud, Johan H L

    2014-01-01

    This article analyzes the relationships among nationalism (N), individualism (I), ethnocentrism (E), and authoritarianism (A) in continuous time (CT), estimated as a structural equation model. The analysis is based on the General Election Study for Flanders, Belgium, for 1991, 1995, and 1999. We find reciprocal effects between A and E and between E and I as well as a unidirectional effect from A on I. We furthermore find relatively small, but significant, effects from both I and E on N but no effect from A on N or from N on any of the other variables. Because of its central role in the N-I-E-A complex, mitigation of authoritarianism has the largest potential to reduce the spread of nationalism, ethnocentrism, and racism in Flanders.

  5. Structural equation modelling of lower back pain due to whole body vibration exposure in the construction industry.

    Science.gov (United States)

    Vitharana, Vitharanage Hashini Paramitha; Chinda, Thanwadee

    2017-08-10

    Whole body vibration (WBV) exposure is a health hazard among workers, causing lower back pain (LBP) in the construction industry. This study examines key factors affecting LBP due to WBV exposure using the exploratory factor analysis and structural equation modelling. The results confirm five key factors, which are equipment, job-related, organizational, personal, and social- context, with their 17 associated items. The organizational factor is found the most important factor, as it influences the other four factors. The results also show that appropriate seat type, specific training program, job rotation, workers' satisfaction, and workers' physical condition are crucial in reducing LBP due to WBV exposure. Moreover, provision of new machines without proper training and good working condition might not help reduce LBP due to WBV exposure. The results help the construction companies to better understand key factors affecting LBP due to WBV exposure, and plan for a better health improvement program.

  6. Using bifactor exploratory structural equation modeling to examine global and specific factors in measures of sports coaches’ interpersonal styles

    Directory of Open Access Journals (Sweden)

    Andreas eStenling

    2015-09-01

    Full Text Available In the present work we investigated distinct sources of construct-relevant psychometric multidimensionality in two sport-specific measures of coaches’ need-supportive (ISS-C and controlling interpersonal (CCBS styles. A recently proposed bifactor exploratory structural equation modeling (ESEM framework was employed to achieve this aim. In Study 1, using a sample of floorball players, the results indicated that the ISS-C can be considered as a unidimensional measure, with one global factor explaining most of the variance in the items. In Study 2, using a sample of male ice hockey players, the results indicated that the items in the CCBS are represented by both a general factor and specific factors, but the subscales differ with regard to the amount of variance in the items accounted for by the general and specific factors. These results add further insight into the psychometric properties of these two measures and the dimensionality of these two constructs.

  7. Work-life balance culture, work-home interaction, and emotional exhaustion: a structural equation modeling approach.

    Science.gov (United States)

    Nitzsche, Anika; Pfaff, Holger; Jung, Julia; Driller, Elke

    2013-01-01

    To examine the relationships among employees' emotional exhaustion, positive and negative work-home interaction, and perceived work-life balance culture in companies. Data for this study were collected through online surveys of employees from companies in the micro- and nanotechnology sectors (N = 509). A structural equation modeling analysis was performed. A company culture perceived by employees as supportive of their work-life balance was found to have both a direct negative effect on emotional exhaustion and an indirect negative effect meditated by negative work-home interaction. In addition, whereas negative work-home interaction associated positively with emotional exhaustion, positive work-home interaction had no significant effect. The direct and indirect relationship between work-life balance culture and emotional exhaustion has practical implications for health promotion in companies.

  8. Psychological Empowerment of the Devotees by Use of Structural Equations Modeling Case study: All Devotees of Ilam

    Directory of Open Access Journals (Sweden)

    Seid Mehdi Veiseh

    2014-06-01

    Full Text Available Psychological empowerment refers to the process of increase of internal motivation proportional to the performance of delivered duties, including recognition aspects such as being affective, worthiness, meaningfulness and right of choice. This study is Objective to investigate the relationship between psychological empowerment of the devotees and the variables work life quality, organizational justice, social support and social health. Methodology research: This is a descriptive – correlation study in which the structural equation modeling is used. The populations include all devotees of Ilam who were selected by use of Cochrane's formula. From the results, it became clear that psychological empowerment of the devotees is directly affected by the factors such as social health, social support, work life quality and organizational justice. Moreover, the variable work life quality has more influence on the psychological empowerment of the devotees.

  9. Understanding the relationships between self-esteem, experiential avoidance, and paranoia: structural equation modelling and experience sampling studies.

    Science.gov (United States)

    Udachina, Alisa; Thewissen, Viviane; Myin-Germeys, Inez; Fitzpatrick, Sam; O'kane, Aisling; Bentall, Richard P

    2009-09-01

    Hypothesized relationships between experiential avoidance (EA), self-esteem, and paranoia were tested using structural equation modeling in a sample of student participants (N = 427). EA in everyday life was also investigated using the Experience Sampling Method in a subsample of students scoring high (N = 17) and low (N = 15) on paranoia. Results showed that paranoid students had lower self-esteem and reported higher levels of EA than nonparanoid participants. The interactive influence of EA and stress predicted negative self-esteem: EA was particularly damaging at high levels of stress. Greater EA and higher social stress independently predicted lower positive self-esteem. Low positive self-esteem predicted engagement in EA. A direct association between EA and paranoia was also found. These results suggest that similar mechanisms may underlie EA and thought suppression. Although people may employ EA to regulate self-esteem, this strategy is maladaptive as it damages self-esteem, incurs cognitive costs, and fosters paranoid thinking.

  10. 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.

  11. Patient Safety and Satisfaction Drivers in Emergency Departments Re-visited - An Empirical Analysis using Structural Equation Modeling

    DEFF Research Database (Denmark)

    Sørup, Christian Michel; Jacobsen, Peter

    2014-01-01

    How can emergency department (ED) decision makers contribute to increase patient satisfaction rates? This question has been thoroughly investigated in many hospital departments but not so much in the ED, which has led to a number of untested hypotheses. Maximising value-added activities seen from...... a patient’s perspective has become an essential outcome in health care, meaning that the untested hypotheses are in need of quantitative testing. This study proposes an integrated framework in which four latent constructs reflecting principal aspects of patient care are tested. The four constructs...... are entitled safety and satisfaction, waiting time, information delivery, and infrastructure accordingly. As an empirical foundation, a recently published comprehensive survey in 11 Danish EDs is analysed in depth using structural equation modeling (SEM). Consulting the proposed framework, ED decision makers...

  12. Examining the Relations among Student Motivation, Engagement, and Retention in a MOOC: A Structural Equation Modeling Approach

    Directory of Open Access Journals (Sweden)

    Yao Xiong

    2015-09-01

    Full Text Available Students who are enrolled in MOOCs tend to have different motivational patterns than fee-paying college students. A majority of MOOC students demonstrate characteristics akin more to "tourists" than formal learners. As a consequence, MOOC students’ completion rate is usually very low. The current study examines the relations among student motivation, engagement, and retention using structural equation modeling and data from a Penn State University MOOC. Three distinct types of motivation are examined: intrinsic motivation, extrinsic motivation, and social motivation. Two main hypotheses are tested: (a motivation predicts student course engagement; and (b student engagement predicts their retention in the course. The results show that motivation is significantly predictive of student course engagement. Furthermore, engagement is a strong predictor of retention. The findings suggest that promoting student motivation and monitoring individual students’ online activities might improve course retention

  13. Mercury cycling in aquatic ecosystems and trophic state-related variables--implications from structural equation modeling.

    Science.gov (United States)

    Pollman, Curtis D

    2014-11-15

    Structural equation modeling (SEM) provides a framework that can more properly handle complex variable interactions inherent in mercury cycling and its bioaccumulation compared to more traditional regression-based methods. SEM was applied to regional data sets for three different types of aquatic ecosystems within Florida, USA--lakes, streams, and the Everglades--to evaluate the underlying nature (i.e., indirect and direct) of the relationships between fish mercury concentrations and trophic state related variables such as nutrients, dissolved organic carbon (DOC), sulfate, and alkalinity. The modeling results indicated some differences in key variable relationships--for example, the effect of nutrients on fish mercury in lakes and streams was uniformly negative through direct and indirect pathways consistent with biodilution or eutrophication-associated effects on food web structure. Somewhat surprisingly, however, was that total phosphorus did not serve as a meaningful variable in the Everglades model, apparently because its effects were masked or secondary to the effects of DOC. What is perhaps a more important result were two key similarities across the three systems. First, the modeling clearly indicates that the dominant influence on fish tissue mercury concentrations in all three systems is related to variations in the methylmercury signal. Second, the modeling demonstrated that the effect of DOC on fish mercury concentrations was exerted through multiple and antagonistic pathways, including facilitated transport of total mercury and methylmercury, enhanced rates of methylation, and limitations imposed on bioavailability. Indeed, while the individual DOC pathways in the models were all highly significant (generally pmodel was greatly reduced or insignificant. These results can help explain contradictory results obtained previously by other researchers in other systems, and illustrate the importance of SEM as a modeling tool when studying systems with complex

  14. System Characteristics, Satisfaction and E-Learning Usage: A Structural Equation Model (SEM)

    Science.gov (United States)

    Ramayah, T.; Lee, Jason Wai Chow

    2012-01-01

    With the advent of the Internet, more and more public universities in Malaysia are putting in effort to introduce e-learning in their respective universities. Using a structured questionnaire derived from the literature, data was collected from 250 undergraduate students from a public university in Penang, Malaysia. Data was analyzed using AMOS…

  15. Structural Equation Model of Health Promoting Behaviors for Health Information Seekers with Mobile.

    Science.gov (United States)

    Choi, Hanna; Kim, Jeongeun; Byun, Ahjung

    2016-01-01

    This study was conducted on verifying whether variables such as prior health related behaviors, health literacy, interpersonal influence, perceived ease of use and usefulness of health information, and behavioral intention could predict actual health promoting behaviors of consumers using health information with mobile in the future. The research model was based on Technology Acceptance Model. Data were collected from 199 mobile health information seekers. Participants' actual health promoting behaviors were checked after 3 months from pre-data collection. The final modified model had good fit indices.

  16. Using structural equation modeling to construct calibration equations relating PM2.5 mass concentration samplers to the federal reference method sampler

    Science.gov (United States)

    Bilonick, Richard A.; Connell, Daniel P.; Talbott, Evelyn O.; Rager, Judith R.; Xue, Tao

    2015-02-01

    The objective of this study was to remove systematic bias among fine particulate matter (PM2.5) mass concentration measurements made by different types of samplers used in the Pittsburgh Aerosol Research and Inhalation Epidemiology Study (PARIES). PARIES is a retrospective epidemiology study that aims to provide a comprehensive analysis of the associations between air quality and human health effects in the Pittsburgh, Pennsylvania, region from 1999 to 2008. Calibration was needed in order to minimize the amount of systematic error in PM2.5 exposure estimation as a result of including data from 97 different PM2.5 samplers at 47 monitoring sites. Ordinary regression often has been used for calibrating air quality measurements from pairs of measurement devices; however, this is only appropriate when one of the two devices (the "independent" variable) is free from random error, which is rarely the case. A group of methods known as "errors-in-variables" (e.g., Deming regression, reduced major axis regression) has been developed to handle calibration between two devices when both are subject to random error, but these methods require information on the relative sizes of the random errors for each device, which typically cannot be obtained from the observed data. When data from more than two devices (or repeats of the same device) are available, the additional information is not used to inform the calibration. A more general approach that often has been overlooked is the use of a measurement error structural equation model (SEM) that allows the simultaneous comparison of three or more devices (or repeats). The theoretical underpinnings of all of these approaches to calibration are described, and the pros and cons of each are discussed. In particular, it is shown that both ordinary regression (when used for calibration) and Deming regression are particular examples of SEMs but with substantial deficiencies. To illustrate the use of SEMs, the 7865 daily average PM2.5 mass

  17. Is there a role of depressive symptoms in the fear-avoidance model? A structural equation approach.

    Science.gov (United States)

    Seekatz, Bettina; Meng, Karin; Bengel, Juergen; Faller, Hermann

    2016-09-01

    The fear-avoidance (FA) model has gained widespread acceptance as a conceptual framework for investigating psychological factors such as FA beliefs and avoidance behavior, which contribute to chronic back pain and reduced functioning. Depressive symptoms are supposed to be related to FA beliefs and to foster avoidance behavior. This study aims to investigate the multivariate assumptions of the FA model with a focus on the role of depressive symptoms. A total of N = 360 patients with chronic nonspecific low back pain at admission of inpatient orthopedic rehabilitation participated in the survey. Measures included a numeric pain rating scale, Fear-Avoidance Beliefs Questionnaire, Pain Anxiety Symptoms Scale, Hannover Functional Ability Questionnaire and Patient Health Questionnaire. Using structural equation modeling (SEM), we construed a basic FA model and subsequently extended it by adding symptoms of depression as a covariate. The results of SEM indicated a good model fit for a basic FA model (χ²(263) = 431.069, p < .001, RMSEA = .042, CFI = .964, WRMR = .986). They confirmed the hypothesized relations and supported single mediations of the relationship between pain and functioning by FA beliefs and avoidance behavior. A second model including symptoms of depression as additional covariate (χ²(511) = 722.761, p < .001, RMSEA = .034, CFI = .956, WRMR = .949) showed a high impact of depressive symptoms on all FA model variables leading to a decrease of the FA mediations. The findings provide empirical support for the multivariate FA model and underline the importance of considering depressive symptoms in a multiple-target approach to understand the mechanisms of chronic pain.

  18. Bayesian structural equations modeling for ordinal response data with missing responses and missing covariates

    CSIR Research Space (South Africa)

    Kim, S

    2009-01-01

    Full Text Available 6.01 Difierent background 8.86 Pay satisfaction 1.25 Supervisor support 7.27 Employee development 1.86 Customer satisfaction 6.83 Innovation 2.94 Employee satisfaction 1.43 Manager goals 5.28 Quality 1.38 Respect 1.48 Retention 0.83 Con ict... for by the facility efiect variability, in the latter the variability is accounted for by the structural dependency as well as the facility efiect. The structural part of the ordinal response SEM is given by ·ij = ¡·ij + »ij; (3.7) where »ij » N (0; diag( 2·1...

  19. Filipino Nursing Students' Behavioral Intentions toward Geriatric Care: A Structural Equation Model (SEM)

    Science.gov (United States)

    de Guzman, Allan B.; Jimenez, Benito Christian B.; Jocson, Kathlyn P.; Junio, Aileen R.; Junio, Drazen E.; Jurado, Jasper Benjamin N.; Justiniano, Angela Bianca F.

    2013-01-01

    Anchored on the key constucts of Ajzen's Theory of Planned Behavior (1985), this paper seeks to test a model that explores the influence of knowledge, attitude, and caring behavior on nursing students' behavioral intention toward geriatric care. A five-part survey-questionnaire was administered to 839 third and fourth year nursing students from a…

  20. A Structural Equation Model of the Writing Process in Typically-Developing Sixth Grade Children

    Science.gov (United States)

    Koutsoftas, Anthony D.; Gray, Shelley

    2013-01-01

    The purpose of this study was to evaluate how sixth grade children planned, translated, and revised written narrative stories using a task reflecting current instructional and assessment practices. A modified version of the Hayes and Flower (1980) writing process model was used as the theoretical framework for the study. Two hundred one…

  1. Occupational Well-Being of School Staff Members: A Structural Equation Model

    Science.gov (United States)

    Saaranen, Terhi; Tossavainen, Kerttu; Turunen, Hannele; Kiviniemi, Vesa; Vertio, Harri

    2007-01-01

    This study aimed to develop a theoretical basis for the promotion of school staff's occupational well-being. The "Content Model for the Promotion of School Community Staff's Occupational Well-being" describes the four aspects of the promotion of occupational well-being ("working conditions", "worker and work", "working community" and "professional…

  2. Specification Searches in Multilevel Structural Equation Modeling: A Monte Carlo Investigation

    Science.gov (United States)

    Peugh, James L.; Enders, Craig K.

    2010-01-01

    Cluster sampling results in response variable variation both among respondents (i.e., within-cluster or Level 1) and among clusters (i.e., between-cluster or Level 2). Properly modeling within- and between-cluster variation could be of substantive interest in numerous settings, but applied researchers typically test only within-cluster (i.e.,…

  3. Filipino Nursing Students' Behavioral Intentions toward Geriatric Care: A Structural Equation Model (SEM)

    Science.gov (United States)

    de Guzman, Allan B.; Jimenez, Benito Christian B.; Jocson, Kathlyn P.; Junio, Aileen R.; Junio, Drazen E.; Jurado, Jasper Benjamin N.; Justiniano, Angela Bianca F.

    2013-01-01

    Anchored on the key constucts of Ajzen's Theory of Planned Behavior (1985), this paper seeks to test a model that explores the influence of knowledge, attitude, and caring behavior on nursing students' behavioral intention toward geriatric care. A five-part survey-questionnaire was administered to 839 third and fourth year nursing students from a…

  4. Determinants of Students' Outcome: A Full-Fledged Structural Equation Modelling Approach

    Science.gov (United States)

    Musah, Mohammed Borhandden; Ali, Hairuddin Bin Mohd; Al-Hudawi, Shafeeq Hussain Vazhathodi; Tahir, Lokman Mohd; Daud, Khadijah Binti; Hamdan, Abdul Rahim

    2015-01-01

    The vibrant demand for academic excellence in the twenty-first century has brought diverse determinants of students' outcome into play. However, few studies have validated the instruments and examined the mediating effect between exogenous and endogenous variables of the student outcome model. This study, therefore, investigates the psychometric…

  5. A Structural Equation Model Explaining 8th Grade Students' Mathematics Achievements

    Science.gov (United States)

    Yurt, Eyüp; Sünbül, Ali Murat

    2014-01-01

    The purpose of this study is to investigate, via a model, the explanatory and predictive relationships among the following variables: Mathematical Problem Solving and Reasoning Skills, Sources of Mathematics Self-Efficacy, Spatial Ability, and Mathematics Achievements of Secondary School 8th Grade Students. The sample group of the study, itself…

  6. Determinants of Students' Outcome: A Full-Fledged Structural Equation Modelling Approach

    Science.gov (United States)

    Musah, Mohammed Borhandden; Ali, Hairuddin Bin Mohd; Al-Hudawi, Shafeeq Hussain Vazhathodi; Tahir, Lokman Mohd; Daud, Khadijah Binti; Hamdan, Abdul Rahim

    2015-01-01

    The vibrant demand for academic excellence in the twenty-first century has brought diverse determinants of students' outcome into play. However, few studies have validated the instruments and examined the mediating effect between exogenous and endogenous variables of the student outcome model. This study, therefore, investigates the psychometric…

  7. Adding Missing-Data-Relevant Variables to FIML-Based Structural Equation Models

    Science.gov (United States)

    Graham, John W.

    2003-01-01

    Conventional wisdom in missing data research dictates adding variables to the missing data model when those variables are predictive of (a) missingness and (b) the variables containing missingness. However, it has recently been shown that adding variables that are correlated with variables containing missingness, whether or not they are related to…

  8. Effects of Missing Data Methods in Structural Equation Modeling with Nonnormal Longitudinal Data

    Science.gov (United States)

    Shin, Tacksoo; Davison, Mark L.; Long, Jeffrey D.

    2009-01-01

    The purpose of this study is to investigate the effects of missing data techniques in longitudinal studies under diverse conditions. A Monte Carlo simulation examined the performance of 3 missing data methods in latent growth modeling: listwise deletion (LD), maximum likelihood estimation using the expectation and maximization algorithm with a…

  9. The Self-Esteem, Perceived Social Support and Hopelessness in Adolescents: The Structural Equation Modeling

    Science.gov (United States)

    Savi Cakar, Firdevs; Karatas, Zeynep

    2012-01-01

    In this study, a developed model to explain a causal relationship between adolescent's self-esteem, perceived social support and hopelessness is tested. The purpose of the study is to explore the relationship between self-esteem, perceived social support and hopelessness in adolescents. A total of 257 adolescents, including 143 female and 114…

  10. Bridging Design and Behavioral Research With Variance-Based Structural Equation Modeling

    NARCIS (Netherlands)

    Henseler, Jörg

    2017-01-01

    Advertising research is a scientific discipline that studies artifacts (e.g., various forms of marketing communication) as well as natural phenomena (e.g., consumer behavior). Empirical advertising research therefore requires methods that can model design constructs as well as behavioral constructs,

  11. Explaining the Intention to Use Technology among University Students: A Structural Equation Modeling Approach

    Science.gov (United States)

    Teo, Timothy; Zhou, Mingming

    2014-01-01

    The aim of this study is to examine the factors that an influence higher education students' intention to use technology. Using an extended technology acceptance model as a research framework, a sample of 314 university students were surveyed on their responses to seven constructs hypothesized to explain their intention to use technology.…

  12. Psychological pathway to suicidal ideation among men who have sex with men in Shanghai, China: A structural equation model.

    Science.gov (United States)

    Li, Rui; Cai, Yong; Wang, Ying; Gan, Feng; Shi, Rong

    2016-12-01

    We aimed to explore the relationships and develop an inter-theoretical model among psychological variables in the progression to suicidal ideation among men who have sex with men (MSM). A cross-sectional study was conducted among 547 MSM in four districts in Shanghai from March to May in 2014. Socio-demographic, psychological, and behavioral information of the participants was collected. A structural equation model (SEM)-Path Analysis was constructed to interpret the intricate relationships among various psychological variables. Suicidal ideation among MSM during the past year was 10.6%. The developed model agreed well with existing suicide models and had a good fit to the data (χ(2)/df = 2.497, comparative fit index = 0.983, root mean squared error of approximation = 0.052). Suicidal ideation was predicted by perceived defeat and entrapment (β = 0.21, p types of temperament might be predisposed to a higher perception of defeat and entrapment. Perceived social support can effectively alleviate the negative appraisals and emotions and lower the risk for suicidal ideation among MSM. Copyright © 2016 Elsevier Ltd. All rights reserved.

  13. Effect of practical training on the learning motivation profile of Japanese pharmacy students using structural equation modeling.

    Science.gov (United States)

    Yamamura, Shigeo; Takehira, Rieko

    2017-01-01

    To establish a model of Japanese pharmacy students' learning motivation profile and investigate the effects of pharmaceutical practical training programs on their learning motivation. The Science Motivation Questionnaire II was administered to pharmacy students in their 4th (before practical training), 5th (before practical training at clinical sites), and 6th (after all practical training) years of study at Josai International University in April, 2016. Factor analysis and multiple-group structural equation modeling were conducted for data analysis. A total of 165 students participated. The learning motivation profile was modeled with 4 factors (intrinsic, career, self-determination, and grade motivation), and the most effective learning motivation was grade motivation. In the multiple-group analysis, the fit of the model with the data was acceptable, and the estimated mean value of the factor of 'self-determination' in the learning motivation profile increased after the practical training programs (P= 0.048, Cohen's d= 0.43). Practical training programs in a 6-year course were effective for increasing learning motivation, based on 'self-determination' among Japanese pharmacy students. The results suggest that practical training programs are meaningful not only for providing clinical experience but also for raising learning motivation.

  14. Effect of practical training on the learning motivation profile of Japanese pharmacy students using structural equation modeling

    Science.gov (United States)

    2017-01-01

    Purpose To establish a model of Japanese pharmacy students’ learning motivation profile and investigate the effects of pharmaceutical practical training programs on their learning motivation. Methods The Science Motivation Questionnaire II was administered to pharmacy students in their 4th (before practical training), 5th (before practical training at clinical sites), and 6th (after all practical training) years of study at Josai International University in April, 2016. Factor analysis and multiple-group structural equation modeling were conducted for data analysis. Results A total of 165 students participated. The learning motivation profile was modeled with 4 factors (intrinsic, career, self-determination, and grade motivation), and the most effective learning motivation was grade motivation. In the multiple-group analysis, the fit of the model with the data was acceptable, and the estimated mean value of the factor of ‘self-determination’ in the learning motivation profile increased after the practical training programs (P= 0.048, Cohen’s d= 0.43). Conclusion Practical training programs in a 6-year course were effective for increasing learning motivation, based on ‘self-determination’ among Japanese pharmacy students. The results suggest that practical training programs are meaningful not only for providing clinical experience but also for raising learning motivation. PMID:28167812

  15. Effect of practical training on the learning motivation profile of Japanese pharmacy students using structural equation modeling

    Directory of Open Access Journals (Sweden)

    Shigeo Yamamura

    2017-02-01

    Full Text Available Purpose To establish a model of Japanese pharmacy students’ learning motivation profile and investigate the effects of pharmaceutical practical training programs on their learning motivation. Methods The Science Motivation Questionnaire II was administered to pharmacy students in their 4th (before practical training, 5th (before practical training at clinical sites, and 6th (after all practical training years of study at Josai International University in April, 2016. Factor analysis and multiple-group structural equation modeling were conducted for data analysis. Results A total of 165 students participated. The learning motivation profile was modeled with 4 factors (intrinsic, career, self-determination, and grade motivation, and the most effective learning motivation was grade motivation. In the multiple-group analysis, the fit of the model with the data was acceptable, and the estimated mean value of the factor of ‘self-determination’ in the learning motivation profile increased after the practical training programs (P= 0.048, Cohen’s d= 0.43. Conclusion Practical training programs in a 6-year course were effective for increasing learning motivation, based on ‘self-determination’ among Japanese pharmacy students. The results suggest that practical training programs are meaningful not only for providing clinical experience but also for raising learning motivation.

  16. Pathways of inhalation exposure to manganese in children living near a ferromanganese refinery: A structural equation modeling approach.

    Science.gov (United States)

    Fulk, Florence; Succop, Paul; Hilbert, Timothy J; Beidler, Caroline; Brown, David; Reponen, Tiina; Haynes, Erin N

    2017-02-01

    Manganese (Mn) is both essential element and neurotoxicant. Exposure to Mn can occur from various sources and routes. Structural equation modeling was used to examine routes of exposure to Mn among children residing near a ferromanganese refinery in Marietta, Ohio. An inhalation pathway model to ambient air Mn was hypothesized. Data for model evaluation were obtained from participants in the Communities Actively Researching Exposure Study (CARES). These data were collected in 2009 and included levels of Mn in residential soil and dust, levels of Mn in children's hair, information on the amount of time the child spent outside, heat and air conditioning in the home and level of parent education. Hair Mn concentration was the primary endogenous variable used to assess the theoretical inhalation exposure pathways. The model indicated that household dust Mn was a significant contributor to child hair Mn (0.37). Annual ambient air Mn concentration (0.26), time children spent outside (0.24) and soil Mn (0.24) significantly contributed to the amount of Mn in household dust. These results provide a potential framework for understanding the inhalation exposure pathway for children exposed to ambient air Mn who live in proximity to an industrial emission source.

  17. Investigation of the role of personal factors on work injury in underground mines using structural equation modeling

    Institute of Scientific and Technical Information of China (English)

    P.S. Paul

    2013-01-01

    Work injuries in mines are complex and generally characterized by several factors starting from personal to technical and technical to social characteristics. In this paper, investigation was made through the application of structural equation modeling to study the nature of relationships between the influencing/associating personal factors and work injury and their sequential relationships leading towards work injury occurrences in underground coal mines. Six variables namely, rebelliousness, negative affectivity, job boredom, job dissatisfaction and work injury were considered in this study. Instruments were developed to quantify them through a questionnaire survey. Underground mine work-ers were randomly selected for the survey. Responses from 300 participants were used for the analysis. The structural model of LISREL was used to estimate the interrelationships amongst the variables. The case study results show that negative affectivity and job boredom induce more job dissatisfaction to the workers whereas risk taking attitude of the individual is positively influenced by job dissatisfaction as well as by rebelliousness characteristics of the individual. Finally, risk taking and job dissatisfaction are having positive significant direct relationship with work injury. The findings of this study clearly reveal that rebelliousness, negative affectivity and job boredom are the three key personal factors influencing work related injuries in mines that need to be addressed properly through effective safety programs.

  18. Growth Curve and Structural Equation Modeling : Topics from the Indian Statistical Institute

    CERN Document Server

    2015-01-01

    This book describes some recent trends in GCM research on different subject areas, both theoretical and applied. This includes tools and possibilities for further work through new techniques and modification of existing ones. A growth curve is an empirical model of the evolution of a quantity over time. Growth curves in longitudinal studies are used in disciplines including biology, statistics, population studies, economics, biological sciences, sociology, nano-biotechnology, and fluid mechanics. The volume includes original studies, theoretical findings and case studies from a wide range of applied work. This volume builds on presentations from a GCM workshop held at the Indian Statistical Institute, Giridih, January 18-19, 2014. This book follows the volume Advances in Growth Curve Models, published by Springer in 2013. The results have meaningful application in health care, prediction of crop yield, child nutrition, poverty measurements, estimation of growth rate, and other research areas.

  19. [Structural equation modeling on contraception behavior of unmarried men and women in Korea: gender difference].

    Science.gov (United States)

    Hwang, Shin Woo; Chung, Chae Weon

    2014-04-01

    The purpose of this study was to test and validate a model to predict contraception behavior in unmarried men and women. Data were collected from a questionnaire survey of 180 unmarried men and 186 unmarried women 20 years of age or over who had sexual relationships in the past 6 months. Participants were from Seoul, Kyunggi, Daegu, and Busan and data collection was done from February 19 to April 16, 2013. Model fit indices for the hypotheoretical model fitted to the recommended levels. Out of 15 paths, 11 were statistically significant in both. Predictors of contraception behavior in unmarried men and women were intention to use contraception and self-efficacy for contraception. Exposure to sexual content was directly significant to the intention in men only. Self-efficacy for contraception was affected by perceived threat of pregnancy and gender role attitude. In women, the two predictors were also significant except for the effect of exposure to sexual contents. Results indicate that an intervention program which increases self-efficacy in unmarried men and women contributes to effective contraception behavior. In addition, proper sexual education programs using positive aspect of mass media can help develop active participation for contraception behavior.

  20. Structural equation modelling of determinants of customer satisfaction of mobile network providers: Case of Kolkata, India

    Directory of Open Access Journals (Sweden)

    Shibashish Chakraborty

    2014-12-01

    Full Text Available The Indian market of mobile network providers is growing rapidly. India is the second largest market of mobile network providers in the world and there is intense competition among existing players. In such a competitive market, customer satisfaction becomes a key issue. The objective of this paper is to develop a customer satisfaction model of mobile network providers in Kolkata. The results indicate that generic requirements (an aggregation of output quality and perceived value, flexibility, and price are the determinants of customer satisfaction. This study offers insights for mobile network providers to understand the determinants of customer satisfaction.

  1. The paths leading from attachment to ageism: a structural equation model approach.

    Science.gov (United States)

    Bodner, Ehud; Cohen-Fridel, Sara

    2014-01-01

    The study introduces a model in which attachment patterns serve as predictors, empathy and fear of death as mediators, and ageism as the predicted variable. Data were collected from young adults (N = 440). Anxious attachment was directly and positively correlated with ageism, and also indirectly and positively by the mediator "fear of death." Avoidant attachment was indirectly and negatively correlated with ageism by the mediator "empathy". It is suggested that interventions for reducing ageist attitudes among younger adults would focus on existential fears, as well as on empathic ability, according to the attachment tendencies of these individuals.

  2. Students' Attitude in a Web-enhanced Hybrid Course: A Structural Equation Modeling Inquiry

    Directory of Open Access Journals (Sweden)

    Cheng-Chang Sam Pan

    2003-12-01

    Full Text Available The present study focuses on five latent factors affecting students use of WebCT in a Web-enhanced hybrid undergraduate course at a southeastern university in the United States. An online questionnaire is used to measure a hypothetic model composed of two exogenous variables (i.e., subjective norm and computer self-efficacy, three endogenous variables (i.e., perceived ease of use, perceived usefulness, and attitude toward WebCT use, one dependent variable (i.e., actual system use, and eleven demographic items. PROC CALIS is used to analyze the data collected. Results suggest the technology acceptance model may not be applicable to the higher education setting. However, student attitude toward WebCT instruction remains a significant determinant to WebCT use on a non-voluntary basis. Educational achievement (i.e., student final grades is regressed on the attitude factor as an outcome variable.Suggestions for practitioners and researchers in the field are mentioned.

  3. Structural equation modeling of latent growth curves of weight gain among treated tuberculosis patients.

    Directory of Open Access Journals (Sweden)

    Mahalingam Vasantha

    Full Text Available Tuberculosis still remains a major public health problem even though it is treatable and curable. Weight gain measurement during anti tuberculosis (TB treatment period is an important component to assess the progress of TB patients. In this study, Latent Growth Models (LGMs were implemented in a longitudinal design to predict the change in weight of TB patients who were given three different regimens under randomized controlled clinical trial for anti-TB treatment. Linear and Quadratic LGMs were fitted using Mplus software. The age, sex and treatment response of the TB patients were used as time invariant independent variables of the growth trajectories. The quadratic trend was found to be better in explaining the changes in weight without grouping than the quadratic model for three group comparisons. A significant increase in the change of weight over time was identified while a significant quadratic effect indicated that weights were sustained over time. The growth rate was similar in both the groups. The treatment response had significant association with the growth rate of weight scores of the patients.

  4. Antecedents of software-as-a-service (SaaS adoption: a structural equation model

    Directory of Open Access Journals (Sweden)

    Mutlaq B. Alotaibi

    2016-07-01

    Full Text Available With the rapid growth in the use of the internet, software-as-a-service (SaaS provides unique opportunities that facilitate innovation without upfront investments in technological infrastructure and expertise. Despite its widespread diffusion and economic benefits, attitudes toward SaaS adoption are of paramount importance. This study investigates and models the perception and belief factors that affect the acceptance and use of SaaS. In particular, it examines whether the unified theory of acceptance and use of technology (UTAUT explains consumer decisions related to the adoption of SaaS. The UTAUT was revised to fit the context of SaaS, by not only incorporating quality of service as a key determinant of behavioral intention, but also by modelling education as a moderator. The study reports a survey of seven hundred and eighty-five (n=785 respondents collected by means of an online questionnaire. Results herein indicates that the acceptance of SaaS relates to several belief factors: performance expectancy, effort expectancy, social influence, facilitating conditions and quality of service. Empirical data support most of the UTAUT relationships.

  5. Variance decomposition of MRI-based covariance maps using genetically informative samples and structural equation modeling.

    Science.gov (United States)

    Schmitt, J Eric; Lenroot, Rhoshel K; Ordaz, Sarah E; Wallace, Gregory L; Lerch, Jason P; Evans, Alan C; Prom, Elizabeth C; Kendler, Kenneth S; Neale, Michael C; Giedd, Jay N

    2009-08-01

    The role of genetics in driving intracortical relationships is an important question that has rarely been studied in humans. In particular, there are no extant high-resolution imaging studies on genetic covariance. In this article, we describe a novel method that combines classical quantitative genetic methodologies for variance decomposition with recently developed semi-multivariate algorithms for high-resolution measurement of phenotypic covariance. Using these tools, we produced correlational maps of genetic and environmental (i.e. nongenetic) relationships between several regions of interest and the cortical surface in a large pediatric sample of 600 twins, siblings, and singletons. These analyses demonstrated high, fairly uniform, statistically significant genetic correlations between the entire cortex and global mean cortical thickness. In agreement with prior reports on phenotypic covariance using similar methods, we found that mean cortical thickness was most strongly correlated with association cortices. However, the present study suggests that genetics plays a large role in global brain patterning of cortical thickness in this manner. Further, using specific gyri with known high heritabilities as seed regions, we found a consistent pattern of high bilateral genetic correlations between structural homologues, with environmental correlations more restricted to the same hemisphere as the seed region, suggesting that interhemispheric covariance is largely genetically mediated. These findings are consistent with the limited existing knowledge on the genetics of cortical variability as well as our prior multivariate studies on cortical gyri.

  6. Analysis of the Quality of Service and Student Satisfaction at the School of Economics, University of Cartagena, Using a Structural Equation Model

    Directory of Open Access Journals (Sweden)

    Juan Carlos Vergara Schmalbach

    2011-05-01

    Full Text Available Structural equation models have been widely used to analyze the quality of service in various organizations, demonstrating their adaptability and efficacy in determining the variables that affect customer satisfaction. This article proposes the use of a structural equation model to determine the quality of service offered by the different academic units of the School of Economics, University of Cartagena, combining Oh (1999 model with the original instrument of Parasuraman, Valarie, and Berry Zeithalm, presented in 1985. The result is a general diagnosis of the variables that exert the most influence on students’ satisfaction, and that motivate them to recommend their institution to others.

  7. Factorial Invariance within Longitudinal Structural Equation Models: Measuring the Same Construct across Time

    Science.gov (United States)

    Widaman, Keith F.; Ferrer, Emilio; Conger, Rand D.

    2009-01-01

    Charting change in behavior as a function of age and investigating longitudinal relations among constructs are primary goals of developmental research. Traditionally, researchers rely on a single measure (e.g., scale score) for a given construct for each person at each occasion of measurement, assuming that measure reflects the same construct at each occasion. With multiple indicators of a latent construct at each time of measurement, the researcher can evaluate whether factorial invariance holds. If factorial invariance constraints are satisfied, latent variable scores at each time of measurement are on the same metric and stronger conclusions are warranted. In this paper we discuss factorial invariance in longitudinal studies, contrasting analytic approaches and highlighting strengths of the multiple-indicator approach to modeling developmental processes. PMID:20369028

  8. Structural equation model of intellectual change and continuity and predictors of intelligence in older men.

    Science.gov (United States)

    Gold, D P; Andres, D; Etezadi, J; Arbuckle, T; Schwartzman, A; Chaikelson, J

    1995-06-01

    This study examined the effects of abilities as a young adult, an engaged lifestyle, personality, age, and health on continuity and change in intellectual abilities from early to late adulthood. A battery of measures, including a verbal and nonverbal intelligence test, was given to 326 Canadian army veterans. Archival data provided World War Two enlistment scores on the same intelligence test for this sample: Results indicated relative stability of intellectual scores across 40 years, with increases in vocabulary and decreases in arithmetic, verbal analogies, and nonverbal skills. Young adult intelligence was the most important determinant of older adult performance. Predictors for verbal intelligence were consistent with an engagement model of intellectual maintenance but also indicated the importance of introversion-extraversion and age. Nonverbal intelligence in late life was predicted by young adult nonverbal scores, age, health, and introversion-extraversion.

  9. VALIDATING QUALITY PROCESS MANAGEMENT INSTRUMENT FOR HIGHER EDUCATION USING STRUCTURAL EQUATION MODELLING

    Directory of Open Access Journals (Sweden)

    David Jimoh Kayode

    2016-06-01

    Full Text Available This study attempts to validate process management scale using rigorous validation procedures. An adapted questionnaire comprising 77 items was administered to faculty members in two public universities in Nigeria. The data gathered were analyzed using exploratory factor analysis and confirmatory factor analysis with SPSS 20.0 and SmartPLS 3.1.2 respectively. The findings of this study shows that process management is a third order reflective model with multidimensional constructs. The two dimension of process management administrative process and academic process has four and five dimensions respectively. The process management scale will therefore facilitate the identifications of elements that influence the effectiveness of higher education. The practical implications and methodological limitations are discussed.

  10. Evaluating Structural Equation Models for Categorical Outcomes: A New Test Statistic and a Practical Challenge of Interpretation.

    Science.gov (United States)

    Monroe, Scott; Cai, Li

    2015-01-01

    This research is concerned with two topics in assessing model fit for categorical data analysis. The first topic involves the application of a limited-information overall test, introduced in the item response theory literature, to structural equation modeling (SEM) of categorical outcome variables. Most popular SEM test statistics assess how well the model reproduces estimated polychoric correlations. In contrast, limited-information test statistics assess how well the underlying categorical data are reproduced. Here, the recently introduced C2 statistic of Cai and Monroe (2014) is applied. The second topic concerns how the root mean square error of approximation (RMSEA) fit index can be affected by the number of categories in the outcome variable. This relationship creates challenges for interpreting RMSEA. While the two topics initially appear unrelated, they may conveniently be studied in tandem since RMSEA is based on an overall test statistic, such as C2. The results are illustrated with an empirical application to data from a large-scale educational survey.

  11. A structural equation modeling approach for the adoption of cloud computing to enhance the Malaysian healthcare sector.

    Science.gov (United States)

    Ratnam, Kalai Anand; Dominic, P D D; Ramayah, T

    2014-08-01

    The investments and costs of infrastructure, communication, medical-related equipments, and software within the global healthcare ecosystem portray a rather significant increase. The emergence of this proliferation is then expected to grow. As a result, information and cross-system communication became challenging due to the detached independent systems and subsystems which are not connected. The overall model fit expending over a sample size of 320 were tested with structural equation modelling (SEM) using AMOS 20.0 as the modelling tool. SPSS 20.0 is used to analyse the descriptive statistics and dimension reliability. Results of the study show that system utilisation and system impact dimension influences the overall level of services of the healthcare providers. In addition to that, the findings also suggest that systems integration and security plays a pivotal role for IT resources in healthcare organisations. Through this study, a basis for investigation on the need to improvise the Malaysian healthcare ecosystem and the introduction of a cloud computing platform to host the national healthcare information exchange has been successfully established.

  12. A Structural Equation Modeling on Factors of How Experienced Teachers Affect the Students’ Science and Mathematics Achievements

    Directory of Open Access Journals (Sweden)

    Serhat Kocakaya

    2014-01-01

    Full Text Available The main purpose of this study was to propose a model for how elementary school students’ science and mathematics achievements in their schools and in Level Determination Exam (SBS depend on the number of teachers and expert teachers in their schools. The sample of the study was 5672 elementary students for the purpose of the study, the number of teachers and expert teachers who worked in sample schools has been defined as independent variables, and students’ science and mathematics achievements in their schools and in SBS exam have been defined as dependent variables. The data obtained from school administrations were analyzed using structural equation modeling to analyze relations among students’ science and mathematics grades in their schools and science and mathematics achievements in SBS exam and the number of teachers and expert teachers in their school. As a result of the analysis, it has been observed that established model has acceptable fit indices and an increasing number of teachers and expert teachers have positive effects on students' science and mathematics achievements.

  13. Predicting organic food consumption: A meta-analytic structural equation model based on the theory of planned behavior.

    Science.gov (United States)

    Scalco, Andrea; Noventa, Stefano; Sartori, Riccardo; Ceschi, Andrea

    2017-05-01

    During the last decade, the purchase of organic food within a sustainable consumption context has gained momentum. Consequently, the amount of research in the field has increased, leading in some cases to discrepancies regarding both methods and results. The present review examines those works that applied the theory of planned behavior (TPB; Ajzen, 1991) as a theoretical framework in order to understand and predict consumers' motivation to buy organic food. A meta-analysis has been conducted to assess the strength of the relationships between attitude, subjective norms, perceived behavioral control, and intention, as well as between intention and behavior. Results confirm the major role played by individual attitude in shaping buying intention, followed by subjective norms and perceived behavioral control. Intention-behavior shows a large effect size, few studies however explicitly reported such an association. Furthermore, starting from a pooled correlation matrix, a meta-analytic structural equation model has been applied to jointly evaluate the strength of the relationships among the factors of the original model. Results suggest the robustness of the TPB model. In addition, mediation analysis indicates a potential direct effect from subjective norms to individual attitude in the present context. Finally, some issues regarding methodological aspects of the application of the TPB within the context of organic food are discussed for further research developments.

  14. An extension of the theory of planned behavior to predict pedestrians' violating crossing behavior using structural equation modeling.

    Science.gov (United States)

    Zhou, Hongmei; Romero, Stephanie Ballon; Qin, Xiao

    2016-10-01

    This paper aimed to examine pedestrians' self-reported violating crossing behavior intentions by applying the theory of planned behavior (TPB). We studied the behavior intentions regarding instrumental attitude, subjective norm, perceived behavioral control, the three basic components of TPB, and extended the theory by adding new factors including descriptive norm, perceived risk and conformity tendency to evaluate their respective impacts on pedestrians' behavior intentions. A questionnaire presented with a scenario that pedestrians crossed the road violating the pedestrian lights at an intersection was designed, and the survey was conducted in Dalian, China. Based on the 260 complete and valid responses, reliability and validity of the data for each question was evaluated. The data were then analyzed by using the structural equation modeling (SEM). The results showed that people had a negative attitude toward the behavior of violating road-crossing rules; they perceived social influences from their family and friends; and they believed that this kind of risky behavior would potentially harm them in a traffic accident. The results also showed that instrumental attitude and subjective norm were significant in the basic TPB model. After adding descriptive norm, subjective norm was no more significant. Other models showed that conformity tendency was a strong predictor, indicating that the presence of other pedestrians would influence behavioral intention. The findings could help to design more effective interventions and safety campaigns, such as changing people's attitude toward this violation behavior, correcting the social norms, increasing their safety awareness, etc. in order to reduce pedestrians' road crossing violations.

  15. The organization of irrational beliefs in posttraumatic stress symptomology: testing the predictions of REBT theory using structural equation modelling.

    Science.gov (United States)

    Hyland, Philip; Shevlin, Mark; Adamson, Gary; Boduszek, Daniel

    2014-01-01

    This study directly tests a central prediction of rational emotive behaviour therapy (REBT) that has received little empirical attention regarding the core and intermediate beliefs in the development of posttraumatic stress symptoms. A theoretically consistent REBT model of posttraumatic stress disorder (PTSD) was examined using structural equation modelling techniques among a sample of 313 trauma-exposed military and law enforcement personnel. The REBT model of PTSD provided a good fit of the data, χ(2) = 599.173, df = 356, p < .001; standardized root mean square residual = .05 (confidence interval = .04-.05); standardized root mean square residual = .04; comparative fit index = .95; Tucker Lewis index = .95. Results demonstrated that demandingness beliefs indirectly affected the various symptom groups of PTSD through a set of secondary irrational beliefs that include catastrophizing, low frustration tolerance, and depreciation beliefs. Results were consistent with the predictions of REBT theory and provides strong empirical support that the cognitive variables described by REBT theory are critical cognitive constructs in the prediction of PTSD symptomology. © 2013 Wiley Periodicals, Inc.

  16. Structure analysis of solution to equations of quasi 3-D accretion disk model

    Institute of Scientific and Technical Information of China (English)

    WU; Mei

    2001-01-01

    [1]Frank, J., King, A., Raine, K., Accretion Power in Astrophysics, Cambridge: Cambridge University Press, 1992.[2]Lu Jufu, Abramowicz, M. A., Bimodel characteristic of accrection of black hole, Acta Astrophysica Sinica, 1988, 8(1): 1—13.[3]Shakura, N. I., Sunyaev, R. A., Black holes in binary systems: Observational appearance, A& A, 1973, 24: 337—355.[4]Spruit, H., Matsuda, T., Inoue, M. et al., Spiral shocks and accretion in discs, MNRAS, 1987, 229: 517—527.[5]Yang, R. X., Kafatos, M., Shock study in fully relativistic isothermal flows, 2, A& A, 1995, 295: 238—244.[6]Kafatos, M., Yang, R. X., Transonic inviscid disc flows in the schwarzschild metric-I, MNRAS, 1994, 268 (4): 925—937.[7]Fortner, B., Lamb, F. K., Miller, G. S., Origin of ‘normal-branch’ quasiperiodic oscillations in low-mass X-ray binary systems, Nature, 1989, 342 (14): 775—777.[8]Narayan, R., Kato, S., Honma, F., Global structure and dynamics of advection-dominated accretion flows around black holes, ApJ, 1997, 476: 49—60.[9]Chakrabarti, S., Titarchuk, L. G., Spectral properties of accretion disks around galactic and extragalactic black holes, ApJ, 1995, 455: 623—639.[10]Landu, L. D., Lifshitz, E. M., Fluid Mechanics, Bristol: f. W. Arrowsmith Ltd., 1959, 514—515.

  17. Structural equation modeling assessing relationship between mathematics beliefs, teachers' attitudes and teaching practices among novice teachers in Malaysia

    Science.gov (United States)

    Borhan, Noziati; Zakaria, Effandi

    2017-05-01

    This quantitative study was conducted to investigate the perception level of novice teachers about mathematics belief, teachers' attitude towards mathematics and teaching practices of mathematics in the classroom. In addition, it also aims to identify whether there is a correspondence model with the data obtained and to identify the relationship between the variables of beliefs, attitudes and practices among novice teachers in Malaysia. A total of 263 primary novice teachers throughout the country were involved in this study were selected randomly. Respondents are required to provide a response to the questionnaire of 66 items related to mathematics beliefs, attitudes and practices of the teaching mathematics. There are ten sub-factors which have been established in this instrument for three major constructs using a Likert scale rating of five points. The items of the constructs undergo the exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) procedure involve of unidimensionality test, convergent validity, construct validity and discriminant validity. Descriptive statistics were used to describe the frequency, percentage, the mean and standard deviation for completing some research questions that have been expressed. As for inferential statistical analysis, the researchers used structural equation modeling (SEM) to answer the question of correspondents model and the relationship between these three variables. The results of the study were found that there exist a correspondence measurement and structural model with the data obtained. While the relationship between variable found that mathematics beliefs have a significant influence on teachers' attitudes towards mathematics as well as the relationship between the attitudes with teaching practices. Meanwhile, mathematics belief had no significant relationship with mathematics teaching practices among novice teachers in Malaysia.

  18. Networks involved in olfaction and their dynamics using independent component analysis and unified structural equation modeling.

    Science.gov (United States)

    Karunanayaka, Prasanna; Eslinger, Paul J; Wang, Jian-Li; Weitekamp, Christopher W; Molitoris, Sarah; Gates, Kathleen M; Molenaar, Peter C M; Yang, Qing X

    2014-05-01

    The study of human olfaction is complicated by the myriad of processing demands in conscious perceptual and emotional experiences of odors. Combining functional magnetic resonance imaging with convergent multivariate network analyses, we examined the spatiotemporal behavior of olfactory-generated blood-oxygenated-level-dependent signal in healthy adults. The experimental functional magnetic resonance imaging (fMRI) paradigm was found to offset the limitations of olfactory habituation effects and permitted the identification of five functional networks. Analysis delineated separable neuronal circuits that were spatially centered in the primary olfactory cortex, striatum, dorsolateral prefrontal cortex, rostral prefrontal cortex/anterior cingulate, and parietal-occipital junction. We hypothesize that these functional networks subserve primary perceptual, affective/motivational, and higher order olfactory-related cognitive processes. Results provided direct evidence for the existence of parallel networks with top-down modulation for olfactory processing and clearly distinguished brain activations that were sniffing-related versus odor-related. A comprehensive neurocognitive model for olfaction is presented that may be applied to broader translational studies of olfactory function, aging, and neurological disease.

  19. [Workplace social capital and intention to stay among Chinese nurses: a structural equation model].

    Science.gov (United States)

    Gao, J L; Zhu, M Y; An, N; Fu, H

    2017-02-20

    Objective: To explore a model that workplace social capital is associated with intention to stay (ITS) in the nursing profession and that this association is partially mediated by organizational commitment, job satisfaction, and job stress among Chinese nurses. Methods: A cross-sectional, observationalstudy was conducted in Shanghai, China between September and December 2014. Two thousandforty-two nurses from 23 healthcare organizations were recruited for the current study using a two-stage sampling process.Intention to stay, workplace social capital, job satisfaction, organizational commitment, and job stress was measured by validated scale. Measured variable path analysis (MVPA) was used to test their hypothesized relationships. Results: There were significant positive direct effects from workplace social capital (β=0.11, Psocial capital had significant positive direct effects on organizational commitment (β=0.65, Psocial capital to ITS was 0.55. Job satisfaction was positively associated with organizational commitment (r=0.47, Psocial capital may lead to higher ITS in nursing primarily by increasing commitment to the nursing occupation and their job satisfaction and by reducing their sense of job stress.

  20. Work-Family Conflict Among Newly Licensed Registered Nurses: A Structural Equation Model of Antecedents and Outcomes.

    Science.gov (United States)

    Unruh, Lynn Y; Raffenaud, Amanda; Fottler, Myron

    2016-01-01

    Conflict between work and family is a human resource management issue that is particularly relevant for nurses. Nursing is a demanding profession, and a high proportion of nurses are women, who tend to have greater family responsibilities than men. Little is known regarding work-family conflict among nurses, and even less is known about how this affects newly licensed registered nurses (NLRNs), who can be stressed from their new jobs and careers. This study empirically tests a model of antecedents and outcomes of work-family and family-work conflict among a sample of NLRNs. We developed a model of the relationships between personal and work environment characteristics, work-family and family-work conflicts, job satisfaction, and intent to leave the job and profession. We used structural equation modeling (Amos, IBM SPSS) to test the model with data from.a survey of NLRNs. We examined a number of latent variables, as well as direct and mediating relationships. The measurement models for all latent variables were validated. The final model indicated that age, health, and family responsibilities are antecedents of family-work conflict; job demands lead to work-family conflict; family-work conflict contributes to job difficulties, which lowers job satisfaction, which, in turn, increases the intent to leave the job and profession; and work-family conflict increases the intent to leave the job and profession (but does not directly affect job satisfaction). Policies to help NLRNs with family responsibilities could reduce family-work conflict, which might reduce job difficulties and improve satisfaction and retention. In addition, policies to reduce job demands could reduce work-family conflict and improve retention.