Application Of Structural Equation Modeling In Educational Research And Practice
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Application Of Structural Equation Modeling In Educational Research And Practice
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Author : Myint Swe Khine
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-10-30
Application Of Structural Equation Modeling In Educational Research And Practice written by Myint Swe Khine and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-10-30 with Education categories.
Structural Equation Modeling (SEM) is a statistical approach to testing hypothesis about the relationships among observed and latent variables. The use of SEM in research has increased in psychology, sociology, and economics in recent years. In particular educational researchers try to obtain the complete image of the process of education through the measurement of personality differences, learning environment, motivation levels and host of other variables that affect the teaching and learning process. With the use of survey instruments and interviews with students, teachers and other stakeholders as a lens, educators can assess and gain valuable information about the social ecology of the classrooms that could help in improving the instructional approach, classroom management and the learning organizations. A considerable number of research have been conducted to identify the factors and interactions between students’ characteristics, personal preferences, affective traits, study skills, and various other factors that could help in better educational performance. In recent years, educational researchers use Structural Equation Modeling (SEM) as a statistical technique to explore the complex and dynamic nature of interactions in educational research and practice. SEM is becoming a powerful analytical tool and making methodological advances in multivariate analysis. This book presents the collective works on concepts, methodologies and applications of SEM in educational research and practice. The anthology of current research described in this book will be a valuable resource for the next generation educational practitioners.
Structural Equation Modeling In Educational Research
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Author :
language : en
Publisher: BRILL
Release Date : 2009-01-01
Structural Equation Modeling In Educational Research written by and has been published by BRILL this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-01-01 with Education categories.
Over the years, researchers have developed statistical methods to help them investigate and interpret issues of interest in many discipline areas. These methods range from descriptive to inferential to multivariate statistics. As the psychometrics measures in education become more complex, vigorous and robust methods were needed in order to represent research data efficiently. One such method is Structural Equation Modeling (SEM). SEM is a statistical technique that allows the simultaneous analysis of a series of structural equations. It also allows a dependent variable in one equation to become an independent variable in another equation. It is a comprehensive statistical approach to testing hypotheses about relations among observed and latent variables. SEM is commonly known as causal modeling, or path analysis, which hypothesizes causal relationships among variables and tests the causal models with a linear equation system. As educational research questions become more complex, they need to be evaluated with more sophisticated tools. The pervasive use of SEM in the literature has shown that SEM has a potential to be of assistance to modern educational researchers. This book will bring together prominent educators and researchers from around the world to share their contemporary research on structural equation modeling in educational settings. The chapters provide information on recent trends and developments and effective applications of the different models to answer various educational research questions. This book is a critical and specialized source that describes recent advances in SEM in international academia.
Structural Equation Modeling With Amos
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Author : Barbara M. Byrne
language : en
Publisher: Psychology Press
Release Date : 2001-04-01
Structural Equation Modeling With Amos written by Barbara M. Byrne and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-04-01 with Psychology categories.
A non-mathematical intro to basic concepts underlying SEM with AMOS applications. An ideal companion to the AMOS manual and any stats book incorporating SEM.
Principles And Practice Of Structural Equation Modeling Fourth Edition
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Author : Rex B. Kline
language : en
Publisher: Guilford Publications
Release Date : 2015-11-03
Principles And Practice Of Structural Equation Modeling Fourth Edition written by Rex B. Kline and has been published by Guilford Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-03 with Social Science categories.
New to This Edition *Extensively revised to cover important new topics: Pearl' s graphing theory and SCM, causal inference frameworks, conditional process modeling, path models for longitudinal data, item response theory, and more. *Chapters on best practices in all stages of SEM, measurement invariance in confirmatory factor analysis, and significance testing issues and bootstrapping. *Expanded coverage of psychometrics. *Additional computer tools: online files for all detailed examples, previously provided in EQS, LISREL, and Mplus, are now also given in Amos, Stata, and R (lavaan). *Reorganized to cover the specification, identification, and analysis of observed variable models separately from latent variable models. Pedagogical Features *Exercises with answers, plus end-of-chapter annotated lists of further reading. *Real examplesof troublesome data, demonstrating how to handle typical problems in analyses.
Structural Equation Modeling
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Author : Gregory R. Hancock
language : en
Publisher: IAP
Release Date : 2013-03-01
Structural Equation Modeling written by Gregory R. Hancock and has been published by IAP this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-01 with Education categories.
Sponsored by the American Educational Research Association's Special Interest Group for Educational Statisticians This volume is the second edition of Hancock and Mueller’s highly-successful 2006 volume, with all of the original chapters updated as well as four new chapters. The second edition, like the first, is intended to serve as a didactically-oriented resource for graduate students and research professionals, covering a broad range of advanced topics often not discussed in introductory courses on structural equation modeling (SEM). Such topics are important in furthering the understanding of foundations and assumptions underlying SEM as well as in exploring SEM, as a potential tool to address new types of research questions that might not have arisen during a first course. Chapters focus on the clear explanation and application of topics, rather than on analytical derivations, and contain materials from popular SEM software.
Best Practices In Quantitative Methods
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Author : Jason W. Osborne
language : en
Publisher: SAGE
Release Date : 2008
Best Practices In Quantitative Methods written by Jason W. Osborne and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Language Arts & Disciplines categories.
The contributors to Best Practices in Quantitative Methods envision quantitative methods in the 21st century, identify the best practices, and, where possible, demonstrate the superiority of their recommendations empirically. Editor Jason W. Osborne designed this book with the goal of providing readers with the most effective, evidence-based, modern quantitative methods and quantitative data analysis across the social and behavioral sciences. The text is divided into five main sections covering select best practices in Measurement, Research Design, Basics of Data Analysis, Quantitative Methods, and Advanced Quantitative Methods. Each chapter contains a current and expansive review of the literature, a case for best practices in terms of method, outcomes, inferences, etc., and broad-ranging examples along with any empirical evidence to show why certain techniques are better. Key Features: Describes important implicit knowledge to readers: The chapters in this volume explain the important details of seemingly mundane aspects of quantitative research, making them accessible to readers and demonstrating why it is important to pay attention to these details. Compares and contrasts analytic techniques: The book examines instances where there are multiple options for doing things, and make recommendations as to what is the "best" choice—or choices, as what is best often depends on the circumstances. Offers new procedures to update and explicate traditional techniques: The featured scholars present and explain new options for data analysis, discussing the advantages and disadvantages of the new procedures in depth, describing how to perform them, and demonstrating their use. Intended Audience: Representing the vanguard of research methods for the 21st century, this book is an invaluable resource for graduate students and researchers who want a comprehensive, authoritative resource for practical and sound advice from leading experts in quantitative methods.
Quality Research In Literacy And Science Education
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Author : Mack C. Shelley
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-12-30
Quality Research In Literacy And Science Education written by Mack C. Shelley and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-12-30 with Education categories.
Statistical models attempt to describe and quantify relationships between variables. In the models presented in this chapter, there is a response variable (sometimes called dependent variable) and at least one predictor variable (sometimes called independent or explanatory variable). When investigating a possible cause-and-effect type of relationship, the response variable is the putative effect and the predictors are the hypothesized causes. Typically, there is a main predictor variable of interest; other predictors in the model are called covariates. Unknown covariates or other independent variables not controlled in an experiment or analysis can affect the dependent or outcome variable and mislead the conclusions made from the inquiry (Bock, Velleman, & De Veaux, 2009). A p value (p) measures the statistical significance of the observed relationship; given the model, p is the probability that a relationship is seen by mere chance. The smaller the p value, the more confident we can be that the pattern seen in the data 2 is not random. In the type of models examined here, the R measures the prop- tion of the variation in the response variable that is explained by the predictors 2 specified in the model; if R is close to 1, then almost all the variation in the response variable has been explained. This measure is also known as the multiple correlation coefficient. Statistical studies can be grouped into two types: experimental and observational.
Basics Of Structural Equation Modeling
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Author : Geoffrey M. Maruyama
language : en
Publisher: SAGE Publications
Release Date : 1997-09-22
Basics Of Structural Equation Modeling written by Geoffrey M. Maruyama and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997-09-22 with Social Science categories.
With the availability of software programs such as LISREL, EQS, and AMOS modeling techniques have become a popular tool for formalized presentation of the hypothesized relationships underlying correlational research and for testing the plausibility of hypothesizing for a particular data set. The popularity of these techniques, however, has often led to misunderstandings of them, particularly by students being exposed to them for the first time. Through the use of careful narrative explanation, Basics of Structural Equation Modeling describes the logic underlying structural equation modeling (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 the various methodologies for analyzing structural equation data.
Handbook Of Structural Equation Modeling
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Author : Rick H. Hoyle
language : en
Publisher: Guilford Publications
Release Date : 2023-02-17
Handbook Of Structural Equation Modeling written by Rick H. Hoyle and has been published by Guilford Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-17 with Business & Economics categories.
"This accessible volume presents both the mechanics of structural equation modeling (SEM) and specific SEM strategies and applications. The editor, along with an international group of 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, including new and emerging topics in SEM. Each chapter provides conceptually oriented descriptions, fully explicated analyses, and engaging examples that reveal modeling possibilities for use with readers' data. Many of the chapters also include access to data and syntax files at the companion website, allowing readers to try their hands at reproducing the authors' results"--