Understanding Structural Equation Modeling
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Understanding Structural Equation Modeling
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Author : J.P. Verma
language : en
Publisher: Springer Nature
Release Date : 2023-10-06
Understanding Structural Equation Modeling written by J.P. Verma and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-06 with Mathematics categories.
This book presents a comprehensive overview of Structural Equation Modeling and how it can be applied to address research issues in different disciplines. The authors employ a ‘simple to complex’ approach. The book reviews topics such as variance, covariance, correlation, multiple regression, mediation, moderation, path analysis, and confirmatory factor analysis. The authors then discuss the initial steps for performing structural equation modeling, including model specification, model identification, model estimation, model testing, and model modification. The book includes an introduction to the IBM SPSS and IBM SPSS Amos software. The authors the explain how this software can be utilized for developing measurement, structural models, and SEM models. The book provides conceptual clarity in understanding the models and discusses practical approaches to solving them. The authors also highlight how these techniques can be applied to various disciplines, including psychology, education, sociology, business, medicine, political science, and biological sciences.
Approaches To Understanding Structural Equation Models
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Author : Phillip Wood
language : en
Publisher:
Release Date : 2020-05-22
Approaches To Understanding Structural Equation Models written by Phillip Wood and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-22 with categories.
This book describes how to specify, evaluate, and compare Structural Equation Models (SEMs). Central ideas of SEM's are presented via scatterplots, path diagrams, equations, vector diagrams, and matrix algebra. A key theme running through the book is that one should not only specify one model for the data, but also think critically about the models a reasonable skeptic might offer as a counterargument. Topics and examples cover regression and anova as SEM's, confirmatory factor analysis, various growth curve models, multi-group models, measurement models, and exploratory factor models. Particular attention is given to assumption checking, identification, measurement assumption, and rotation techniques. Examples of analyses done in Amos, Lavaan, Mplus, and Onyx are presented. An appendix of matrix algebra ideas relevant to SEM specification is included. I expect the material covered exceeds what a one semester introduction to SEM could cover, but readers can select chapters relevant to their particular research needs. I will add material to this if there is interest.
Understanding Structural Equation Models
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Author : Phillip K. Wood
language : en
Publisher: CRC Press
Release Date : 2025-12-29
Understanding Structural Equation Models written by Phillip K. Wood and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-12-29 with Mathematics categories.
The field of structural equation models (SEMs) is rapidly expanding. A researcher who wants to select and apply SEMs to their data faces several challenges: (1) They can often become extremely complex, with many parameters to estimate. Small samples or those with relatively few variables often cannot support this complexity reliably, leading to under-identified models, poor power, or unstable estimates; (2) Researchers must choose an appropriate measurement model, and these choices are not often well understood in advance; (3) No single “correct” SEM exists, although “better” ones do, and the existence of competing plausible alternatives is often overlooked; and (4) Critical examination of model assumptions involving the linearity of parameters and the existence of influential or outlying observations is often overlooked. This book provides an overview of SEMs as a flexible, skeptical, and iterative scientific process. Key Features: Emphasis on multiverse analysis, right-sizing statistical models to data, and the generation of plausible skeptical alternatives Robust assumption checking (LOESS regression, regression and SEM diagnostics) Detailed, visual coverage of a variety of path diagrams, their links to matrix-based specifications, and data exploration using heat-map visualization and tests of dimensionality A variety of SEMs including mediational models, psychometrics (e.g., parallel, tau-equivalent, congeneric measurement), growth curve models, exploratory factor analysis, multigroup, categorical, and exploratory structural equation modeling This text is designed for graduate students, early-career researchers, and advanced undergraduates who wish to move beyond plug-and-play SEMs to a deeper, more philosophical and data-conscious understanding. Its careful balance of theory, worked examples, and emphasis on skepticism will help its audience build confidence in using SEMs flexibly and responsibly for a broad range of social and behavioral science research.
A Beginner S Guide To Structural Equation Modeling
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Author : Randall E. Schumacker
language : en
Publisher: Routledge
Release Date : 2015-12-22
A Beginner S Guide To Structural Equation Modeling written by Randall E. Schumacker and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-22 with Psychology categories.
Noted for its crystal clear explanations, this book is considered the most comprehensive introductory text to structural equation modeling (SEM). Noted for its thorough review of basic concepts and a wide variety of models, this book better prepares readers to apply SEM to a variety of research questions. Programming details and the use of algebra are kept to a minimum to help readers easily grasp the concepts so they can conduct their own analysis and critique related research. Featuring a greater emphasis on statistical power and model validation than other texts, each chapter features key concepts, examples from various disciplines, tables and figures, a summary, and exercises. Highlights of the extensively revised 4th edition include: -Uses different SEM software (not just Lisrel) including Amos, EQS, LISREL, Mplus, and R to demonstrate applications. -Detailed introduction to the statistical methods related to SEM including correlation, regression, and factor analysis to maximize understanding (Chs. 1 – 6). -The 5 step approach to modeling data (specification, identification, estimation, testing, and modification) is now covered in more detail and prior to the modeling chapters to provide a more coherent view of how to create models and interpret results (ch. 7). -More discussion of hypothesis testing, power, sampling, effect sizes, and model fit, critical topics for beginning modelers (ch. 7). - Each model chapter now focuses on one technique to enhance understanding by providing more description, assumptions, and interpretation of results, and an exercise related to analysis and output (Chs. 8 -15). -The use of SPSS AMOS diagrams to describe the theoretical models. -The key features of each of the software packages (Ch. 1). -Guidelines for reporting SEM research (Ch. 16). -www.routledge.com/9781138811935 which provides access to data sets that can be used with any program, links to other SEM examples, related readings, and journal articles, and more. Reorganized, the new edition begins with a more detailed introduction to SEM including the various software packages available, followed by chapters on data entry and editing, and correlation which is critical to understanding how missing data, non-normality, measurement, and restriction of range in scores affects SEM analysis. Multiple regression, path, and factor models are then reviewed and exploratory and confirmatory factor analysis is introduced. These chapters demonstrate how observed variables share variance in defining a latent variables and introduce how measurement error can be removed from observed variables. Chapter 7 details the 5 SEM modeling steps including model specification, identification, estimation, testing, and modification along with a discussion of hypothesis testing and the related issues of power, and sample and effect sizes.Chapters 8 to 15 provide comprehensive introductions to different SEM models including Multiple Group, Second-Order CFA, Dynamic Factor, Multiple-Indicator Multiple-Cause, Mixed Variable and Mixture, Multi-Level, Latent Growth, and SEM Interaction Models. Each of the 5 SEM modeling steps is explained for each model along with an application. Chapter exercises provide practice with and enhance understanding of the analysis of each model. The book concludes with a review of SEM guidelines for reporting research. Designed for introductory graduate courses in structural equation modeling, factor analysis, advanced, multivariate, or applied statistics, quantitative techniques, or statistics II taught in psychology, education, business, and the social and healthcare sciences, this practical book also appeals to researchers in these disciplines. Prerequisites include an introduction to intermediate statistics that covers correlation and regression principles.
A Beginner S Guide To Structural Equation Modeling
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Author : Randall E. Schumacker
language : en
Publisher: Psychology Press
Release Date : 2004-06-24
A Beginner S Guide To Structural Equation Modeling written by Randall E. Schumacker and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-06-24 with Psychology categories.
The second edition features: a CD with all of the book's Amos, EQS, and LISREL programs and data sets; new chapters on importing data issues related to data editing and on how to report research; an updated introduction to matrix notation and programs that illustrate how to compute these calculations; many more computer program examples and chapter exercises; and increased coverage of factors that affect correlation, the 4-step approach to SEM and hypothesis testing, significance, power, and sample size issues. The new edition's expanded use of applications make this book ideal for advanced students and researchers in psychology, education, business, health care, political science, sociology, and biology. A basic understanding of correlation is assumed and an understanding of the matrices used in SEM models is encouraged.
Advanced Structural Equation Modeling
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Author : George A. Marcoulides
language : en
Publisher: Psychology Press
Release Date : 2013-10-31
Advanced Structural Equation Modeling written by George A. Marcoulides and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-10-31 with Psychology categories.
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.
A Primer On Partial Least Squares Structural Equation Modeling Pls Sem
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Author : Joseph F. Hair
language : en
Publisher: SAGE
Release Date : 2014
A Primer On Partial Least Squares Structural Equation Modeling Pls Sem written by Joseph F. Hair and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with Business & Economics categories.
A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), by Hair, Hult, Ringle, and Sarstedt, provides a concise yet very practical guide to understanding and using PLS structural equation modeling (PLS-SEM). PLS-SEM is evolving as a statistical modeling technique and its use has increased exponentially in recent years within a variety of disciplines, due to the recognition that PLS-SEM's distinctive methodological features make it a viable alternative to the more popular covariance-based SEM approach. This text—the only comprehensive book available to explain the fundamental aspects of the method—includes extensive examples on SmartPLS software, and is accompanied by multiple data sets that are available for download from the accompanying website (www.pls-sem.com).
A Beginner S Guide To Structural Equation Modeling
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Author : Randall E. Schumacker
language : en
Publisher: Routledge
Release Date : 2012-10-12
A Beginner S Guide To Structural Equation Modeling written by Randall E. Schumacker and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-10-12 with Mathematics categories.
This textbook presents a basic introduction to structural equation modeling (SEM) and focuses on the conceptual steps to be taken in analysing conceptual models.
Structural Equation Modelling
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Author : Jitesh J. Thakkar
language : en
Publisher: Springer Nature
Release Date : 2020-03-13
Structural Equation Modelling written by Jitesh J. Thakkar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-13 with Technology & Engineering categories.
Structural Equation Modeling provides a conceptual and mathematical understanding of structural equation modelling, helping readers across disciplines understand how to test or validate theoretical models, and build relationships between observed variables. In addition to a providing a background understanding of the concepts, it provides step-by-step illustrative applications with AMOS, SPSS and R software programmes. This volume will serve as a useful reference for academic and industry researchers in the fields of engineering, management, psychology, sociology, human resources, and humanities.
Approaches To Understanding Structural Models
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Author : Phillip Karl Wood
language : en
Publisher:
Release Date : 2019-01-12
Approaches To Understanding Structural Models written by Phillip Karl Wood and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-12 with Psychology categories.
This is a book format for lecture notes I developed for my classes in structural equation modeling. It describes how to specify, evaluate, and compare Structural Equation Models (SEMs). Central ideas of SEM's are presented via scatterplots, path diagrams, Equations, vector diagrams, and matrix algebra. It emphasizes that one not only specify one model, but think critically about other counterarguments a reasonable skeptic might offer for a proposed model. Numerous examples are present which illustrate confirmatory factor models, various growth curve models, multi-group models, measurment models, and exploratory factor models. Assumption checking, estimation, and rotation techniques are also discussed. Examples of analyses done in Amos, Lavaan, Mplus, and Onyx are presented. An appendix of matrix algebra ideas relevant to SEM specification is presented as well. I expect the material covered exceeds what a one semester introduction to SEM could cover, but readers can select chapters relevant to their particular research needs.I expect I will flesh out the exploratory factor analysis discussion in a subsequent version and plan to include chapters on Bayesian estimation and model comparison as well, but the present manuscript would probably be a good starting point for many.