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Advanced Structural Equation Modeling

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Basic And Advanced Bayesian Structural Equation Modeling

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Author : Sik-Yum Lee
language : en
Publisher: John Wiley & Sons
Release Date : 2012-07-05

Basic And Advanced Bayesian Structural Equation Modeling written by Sik-Yum Lee and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-07-05 with Mathematics categories.

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 introduced, whilst SEM with a nonparametric structural equation to assess unspecified functional relationships among latent variables are also explored. Statistical methodologies are developed using the Bayesian approach giving reliable results for small samples and allowing the use of prior information leading to better statistical results. Estimates of the parameters and model comparison statistics are obtained via powerful Markov Chain Monte Carlo methods in statistical computing. Introduces the Bayesian approach to SEMs, including discussion on the selection of prior distributions, and data augmentation. Demonstrates how to utilize the recent powerful tools in statistical computing including, but not limited to, the Gibbs sampler, the Metropolis-Hasting algorithm, and path sampling for producing various statistical results such as Bayesian estimates and Bayesian model comparison statistics in the analysis of basic and advanced SEMs. Discusses the Bayes factor, Deviance Information Criterion (DIC), and $L_\nu$-measure for Bayesian model comparison. Introduces a number of important generalizations of SEMs, including multilevel and mixture SEMs, latent curve models and longitudinal SEMs, semiparametric SEMs and those with various types of discrete data, and nonparametric structural equations. Illustrates how to use the freely available software WinBUGS to produce the results. Provides numerous real examples for illustrating the theoretical concepts and computational procedures that are presented throughout the book. Researchers and advanced level students in statistics, biostatistics, public health, business, education, psychology and social science will benefit from this book.

Applied Structural Equation Modeling Using Amos

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Author : Joel E. Collier
language : en
Publisher: Routledge
Release Date : 2020-06-02

Applied Structural Equation Modeling Using Amos written by Joel E. Collier and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-02 with categories.

This is an essential how-to guide on the application of structural equation modeling (SEM) techniques with the AMOS software, focusing on the practical applications of both simple and advanced topics. Written in an easy-to-understand conversational style, the book covers everything from data collection and screening to confirmatory factor analysis, structural model analysis, mediation, moderation, and more advanced topics such as mixture modeling, censored date, and non-recursive models. Through step-by-step instructions, screen shots, and suggested guidelines for reporting, Collier cuts through abstract definitional perspectives to give insight on how to actually run analysis. Unlike other SEM books, the examples used will often start in SPSS and then transition to AMOS so that the reader can have full confidence in running the analysis from beginning to end. Best practices are also included on topics like how to determine if your SEM model is formative or reflective, making it not just an explanation of SEM topics, but a guide for researchers on how to develop a strong methodology while studying their respective phenomenon of interest. With a focus on practical applications of both basic and advanced topics, and with detailed work-through examples throughout, this book is ideal for experienced researchers and beginners across the behavioral and social sciences.

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.

Advanced Issues In Partial Least Squares Structural Equation Modeling

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Author : Joseph F. Hair, Jr.
language : en
Publisher: SAGE Publications
Release Date : 2023-08-21

Advanced Issues In Partial Least Squares Structural Equation Modeling written by Joseph F. Hair, Jr. and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-21 with Business & Economics categories.

The Second Edition of Advanced Issues in Partial Least Squares Structural Equation Modeling offers a straightforward and practical guide to PLS-SEM for users ready to go further than the basics of A Primer on Partial Least Squares Structural Equation Modeling, Third Edition. Even in this advanced guide, the authors have limited the emphasis on equations, formulas, and Greek symbols, and instead rely on detailed explanations of the fundamentals of PLS-SEM and provide general guidelines for understanding and evaluating the results of applying the method. A single study on corporate reputation features as an example throughout the book, along with a single software package (SmartPLS 4.0) to provide a seamless learning experience. The approach of this book is based on the authors’ many years of conducting research and teaching methodology courses, including developing the SmartPLS software. The preparation of the book, especially this new edition, is based on the authors’ desire to communicate the PLS-SEM method to a much broader audience from management and marketing to engineering, geography, medicine, political and environmental sciences, psychology, and beyond. The Second Edition includes a new chapter on the necessary condition analysis (NCA) and covers the most recent developments in PLS-SEM, with detailed guidelines for estimating and validating higher-order constructs and nonlinear effects as well as more insights on multigroup and latent class analyses using FIMIX-PLS and PLS-POS. The book is aimed at researchers and practitioners who seek to gain comprehensive knowledge of more advanced PLS-SEM methods.

Longitudinal Structural Equation Modeling

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Author : Jason T. Newsom
language : en
Publisher: Routledge
Release Date : 2015-06-19

Longitudinal Structural Equation Modeling written by Jason T. Newsom and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-19 with Psychology categories.

This comprehensive resource reviews structural equation modeling (SEM) strategies for longitudinal data to help readers see which modeling options are available for which hypotheses. The author demonstrates how SEM is related to other longitudinal data techniques throughout. By exploring connections between models, readers gain a better understanding of when to choose one analysis over another. The book explores basic models to sophisticated ones including the statistical and conceptual underpinnings that are the building blocks of the analyses. Accessibly written, research examples from the behavioral and social sciences and results interpretations are provided throughout. The emphasis is on concepts and practical guidance for applied research rather than on mathematical proofs. New terms are highlighted and defined in the glossary. Figures are included for every model along with detailed discussions of model specification and implementation issues. Each chapter also includes examples of each model type, comment sections that provide practical guidance, model extensions, and recommended readings. Highlights include: Covers the major SEM approaches to longitudinal analysis in one resource. Explores connections between longitudinal SEM models to enhance integration. Numerous examples that help readers match research questions to appropriate analyses and interpret results. Reviews practical issues related to model specification and estimation to reinforce connections. Analyzes continuous and discrete (binary and ordinal) variables throughout for breadth not found in other sources. Reviews key SEM concepts for those who need a refresher (Ch. 1). Emphasizes how to apply and interpret each model through realistic data examples. Provides the book’s data sets at www.longitudinalsem.com along with the Mplus and R-lavaan syntax used to generate the results. Introduces the LISREL notation system used throughout (Appendix A). The chapters can be read out of order but it is best to read chapters 1 – 4 first because most of the later chapters refer back to them. The book opens with a review of latent variables and analysis of binary and ordinal variables. Chapter 2 applies this information to assessing longitudinal measurement invariance. SEM tests of dependent means and proportions over time points are explored in Chapter 3, and stability and change, difference scores, and lagged regression are covered in Chapter 4. The remaining chapters are each devoted to one major type of longitudinal SEM -- repeated measures analysis models, full cross-lagged panel models and simplex models, modeling stability with state-trait models, linear and nonlinear growth curve models, latent difference score models, latent transition analysis, time series analysis, survival analysis, and attrition. Missing data is discussed in the context of many of the preceding models in Chapter 13. Ideal for graduate courses on longitudinal (data) analysis, advanced SEM, longitudinal SEM, and/or advanced data (quantitative) analysis taught in the behavioral, social, and health sciences, this text also appeals to researchers in these fields. Intended for those without an extensive math background, prerequisites include familiarity with basic SEM. Matrix algebra is avoided in all but a few places.

Structural Equation Modeling

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Author : Jichuan Wang
language : en
Publisher: John Wiley & Sons
Release Date : 2019-09-17

Structural Equation Modeling written by Jichuan Wang and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-17 with Mathematics categories.

Presents a useful guide for applications of SEM whilst systematically demonstrating various SEM models using Mplus Focusing on the conceptual and practical aspects of Structural Equation Modeling (SEM), this book demonstrates basic concepts and examples of various SEM models, along with updates on many advanced methods, including confirmatory factor analysis (CFA) with categorical items, bifactor model, Bayesian CFA model, item response theory (IRT) model, graded response model (GRM), multiple imputation (MI) of missing values, plausible values of latent variables, moderated mediation model, Bayesian SEM, latent growth modeling (LGM) with individually varying times of observations, dynamic structural equation modeling (DSEM), residual dynamic structural equation modeling (RDSEM), testing measurement invariance of instrument with categorical variables, longitudinal latent class analysis (LLCA), latent transition analysis (LTA), growth mixture modeling (GMM) with covariates and distal outcome, manual implementation of the BCH method and the three-step method for mixture modeling, Monte Carlo simulation power analysis for various SEM models, and estimate sample size for latent class analysis (LCA) model. The statistical modeling program Mplus Version 8.2 is featured with all models updated. It provides researchers with a flexible tool that allows them to analyze data with an easy-to-use interface and graphical displays of data and analysis results. Intended as both a teaching resource and a reference guide, and written in non-mathematical terms, Structural Equation Modeling: Applications Using Mplus, 2nd edition provides step-by-step instructions of model specification, estimation, evaluation, and modification. Chapters cover: Confirmatory Factor Analysis (CFA); Structural Equation Models (SEM); SEM for Longitudinal Data; Multi-Group Models; Mixture Models; and Power Analysis and Sample Size Estimate for SEM. Presents a useful reference guide for applications of SEM while systematically demonstrating various advanced SEM models Discusses and demonstrates various SEM models using both cross-sectional and longitudinal data with both continuous and categorical outcomes Provides step-by-step instructions of model specification and estimation, as well as detailed interpretation of Mplus results using real data sets Introduces different methods for sample size estimate and statistical power analysis for SEM Structural Equation Modeling is an excellent book for researchers and graduate students of SEM who want to understand the theory and learn how to build their own SEM models using Mplus.

Advanced Structural Equation Modeling

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Author : George A. Marcoulides
language : en
Publisher: Psychology Press
Release Date : 2013-10-31

Structural Equation Modeling

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Author : Jichuan Wang
language : en
Publisher: John Wiley & Sons
Release Date : 2012-07-31

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 flexible tool to analyze their data with an easy-to-use interface and graphical displays of data and analysis results. Key features: Presents a useful reference guide for applications of SEM whilst systematically demonstrating various advanced SEM models, such as multi-group and mixture models using Mplus. Discusses and demonstrates various SEM models using both cross-sectional and longitudinal data with both continuous and categorical outcomes. Provides step-by-step instructions of model specification and estimation, as well as detail interpretation of Mplus results. Explores different methods for sample size estimate and statistical power analysis for SEM. By following the examples provided in this book, readers will be able to build their own SEM models using Mplus. Teachers, graduate students, and researchers in social sciences and health studies will also benefit from this book.

Structural Equation Modeling

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Author : Rick H. Hoyle
language : en
Publisher: SAGE
Release Date : 1995-02-28

Structural Equation Modeling written by Rick H. Hoyle and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995-02-28 with Psychology categories.

Practical and up-to-date, Structural Equation Modeling includes chapters on major aspects of the structural equation modeling approach to research design and data analysis. Written by internationally recognized leaders in structural equation modeling, this book targets graduate students and seasoned researchers in the social and behavioral sciences who wish to understand the basic concepts and issues associated with the structural equation modeling approach and applications to research problems. Though technically sound, the chapters are primarily nontechnical in content and stylemaking the volume an excellent introduction to the structural equation modeling approach for readers studied in traditional inferential statistics. Early chapters are devoted to fundamental concepts such as estimation, fit, assumptions, power, and inference. Later chapters address such practical issues as the use of computer programs for applying the approach to research questions in the social and behavioral sciences.

Structural Equation Modeling With Mplus

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Author : Barbara M. Byrne
language : en
Publisher: Routledge
Release Date : 2013-06-17

Structural Equation Modeling With Mplus written by Barbara M. Byrne and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-17 with Psychology categories.

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 explanation and interpretation of all Mplus input and output files important caveats pertinent to the SEM application under study a description of the data and reference upon which the model was based the corresponding data and syntax files available under "Supplementary Material" below The first two chapters introduce the fundamental concepts of SEM and important basics of the Mplus program. The remaining chapters focus on SEM applications and include a variety of SEM models presented within the context of three sections: Single-group analyses, Multiple-group analyses, and other important topics, the latter of which includes the multitrait-multimethod, latent growth curve, and multilevel models. Intended for researchers, practitioners, and students who use SEM and Mplus, this book is an ideal resource for graduate level courses on SEM taught in psychology, education, business, and other social and health sciences and/or as a supplement for courses on applied statistics, multivariate statistics, intermediate or advanced statistics, and/or research design. Appropriate for those with limited exposure to SEM or Mplus, a prerequisite of basic statistics through regression analysis is recommended.

Advanced Structural Equation Modeling

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