When you looking for structural equation modeling, you must consider not only the quality but also price and customer reviews. But among hundreds of product with different price range, choosing suitable structural equation modeling is not an easy task. In this post, we show you how to find the right structural equation modeling along with our top-rated reviews. Please check out our suggestions to find the best structural equation modeling for you.
Reviews
1. A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM)
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Sage PubnsDescription
A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) by Joseph F. Hair, Jr., G. Tomas M. Hult, Christian Ringle, and Marko Sarstedt is a practical guide that provides concise instructions on how to use partial least squares structural equation modeling (PLS-SEM), an evolving statistical technique, to conduct research and obtain solutions. Featuring the latest research, new examples using the SmartPLS software, and expanded discussions throughout, the Second Edition is designed to be easily understood by those with limited statistical and mathematical training who want to pursue research opportunities in new ways.2. Principles and Practice of Structural Equation Modeling, Fourth Edition (Methodology in the Social Sciences)
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Principles and Practice of Structural Equation Modeling Methodology in the Social SciencesDescription
New to This Edition
*Extensively revised to cover important new topics: Pearl's graphing theory and the 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 examples of troublesome data, demonstrating how to handle typical problems in analyses.
*Topic boxes on specialized issues, such as causes of nonpositive definite correlations.
*Boxed rules to remember.
*Website promoting a learn-by-doing approach, including syntax and data files for six widely used SEM computer tools.
3. Structural Equation Modeling with Mplus: Basic Concepts, Applications, and Programming (Multivariate Applications Series)
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Structural Equation Modeling With Mplus Basic Concepts Applications and ProgrammingDescription
Modeled after Barbara Byrnes 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 at http://www.psypress.com/sem-with-mplus/datasets .
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.
4. Discovering Structural Equation Modeling Using Stata: Revised Edition
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Stata PressDescription
Discovering Structural Equation Modeling Using Stata, Revised Edition is devoted to Statas sem command and all it can do. Learn about its capabilities in the context of confirmatory factor analysis, path analysis, structural equation modeling, longitudinal models, and multiple-group analysis. Each model is presented along with the necessary Stata code, which is parsimonious, powerful, and can be modified to fit a wide variety of models. The datasets used are downloadable, offering a hands-on approach to learning.
A particularly exciting feature of Stata is the SEM Builder. This graphical interface for structural equation modeling allows you to draw publication-quality path diagrams and fit the models without writing any programming code. When you fit a model with the SEM Builder, Stata automatically generates the complete code that you can save for future use. Use of this unique tool is extensively covered in an appendix and brief examples appear throughout the text.
5. A Beginner's Guide to Structural Equation Modeling: Fourth Edition
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Taylor FrancisDescription
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.
6. Structural Equation Modeling With AMOS: Basic Concepts, Applications, and Programming, Third Edition (Multivariate Applications Series)
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Structural Equation Modeling With AMOS Basic Concepts Applications and Programming Third Edition Multivariate Applications SeriesDescription
This bestselling text provides a practical guide to structural equation modeling (SEM) using the Amos Graphical approach. Using clear, everyday language, the text is ideal for those with little to no exposure to either SEM or Amos. The author reviews SEM applications based on actual data taken from her own research. Each chapter "walks" readers through the steps involved (specification, estimation, evaluation, and post hoc modification) in testing a variety of SEM models. Accompanying each application is: an explanation of the issues addressed and a schematic presentation of hypothesized model structure; Amos input and output with interpretations; use of the Amos toolbar icons and pull-down menus; and data upon which the model application was based, together with updated references pertinent to the SEM model tested.
Thoroughly updated throughout, the new edition features:
- All new screen shots featuring Amos Version 23.
- Descriptions and illustrations of Amos new Tables View format which enables the specification of a structural model in spreadsheet form.
- Key concepts and/or techniques that introduce each chapter.
- Alternative approaches to model analyses when enabled by Amos thereby allowing users to determine the method best suited to their data.
- Provides analysis of the same model based on continuous and categorical data (Ch. 5) thereby enabling readers to observe two ways of specifying and testing the same model as well as compare results.
- All applications based on the Amos graphical mode interface accompanied by more "how to" coverage of graphical techniques unique to Amos.
- More explanation of key procedures and analyses that address questions posed by readers
- All application data files are available at www.routledge.com/9781138797031.
The two introductory chapters in Section 1 review the fundamental concepts of SEM methodology and a general overview of the Amos program. Section 2 provides single-group analyses applications including two first-order confirmatory factor analytic (CFA) models, one second-order CFA model, and one full latent variable model. Section 3 presents multiple-group analyses applications with two rooted in the analysis of covariance structures and one in the analysis of mean and covariance structures. Two models that are increasingly popular with SEM practitioners, construct validity and testing change over time using the latent growth curve, are presented in Section 4. The book concludes with a review of the use of bootstrapping to address non-normal data and a review of missing (or incomplete) data in Section 5.
An ideal supplement for graduate level courses in psychology, education, business, and social and health sciences that cover the fundamentals of SEM with a focus on Amos, this practical text continues to be a favorite of both researchers and practitioners. A prerequisite of basic statistics through regression analysis is recommended but no exposure to either SEM or Amos is required.
7. Structural Equation Modeling: Concepts, Issues, and Applications
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Used Book in Good ConditionDescription
This largely nontechnical volume reviews some of the major issues facing researchers who wish to use structural equation modeling. Individual chapters present recent developments on specification, estimation and testing, statistical power, software comparisons and analyzing multitrait/multimethod data. Numerous examples of applications are given and attention is paid to the underlying philosophy of structural equation modeling and to writing up results from structural equation modeling analyses.
