Multilevel Structural Equation Modeling

Multilevel Structural Equation Modeling

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  • Author: Bruno Castanho Silva
  • Publisher: SAGE Publications
  • ISBN: 1544323034
  • Category : Social Science
  • Languages : en
  • Pages : 127

Multilevel Structural Equation Modeling serves as a minimally technical overview of multilevel structural equation modeling (MSEM) for applied researchers and advanced graduate students in the social sciences. As the first book of its kind, this title is an accessible, hands-on introduction for beginners of the topic. The authors predict a growth in this area, fueled by both data availability and also the availability of new and improved software to run these models. The applied approach, combined with a graphical presentation style and minimal reliance on complex matrix algebra guarantee that this volume will be useful to social science graduate students wanting to utilize such models.


Growth Modeling

Growth Modeling

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  • Author: Kevin J. Grimm
  • Publisher: Guilford Publications
  • ISBN: 1462526063
  • Category : Social Science
  • Languages : en
  • Pages : 558

Growth models are among the core methods for analyzing how and when people change. Discussing both structural equation and multilevel modeling approaches, this book leads readers step by step through applying each model to longitudinal data to answer particular research questions. It demonstrates cutting-edge ways to describe linear and nonlinear change patterns, examine within-person and between-person differences in change, study change in latent variables, identify leading and lagging indicators of change, evaluate co-occurring patterns of change across multiple variables, and more. User-friendly features include real data examples, code (for Mplus or NLMIXED in SAS, and OpenMx or nlme in R), discussion of the output, and interpretation of each model's results. User-Friendly Features *Real, worked-through longitudinal data examples serving as illustrations in each chapter. *Script boxes that provide code for fitting the models to example data and facilitate application to the reader's own data. *"Important Considerations" sections offering caveats, warnings, and recommendations for the use of specific models. *Companion website supplying datasets and syntax for the book's examples, along with additional code in SAS/R for linear mixed-effects modeling.


An Introduction to Multilevel Modeling Techniques

An Introduction to Multilevel Modeling Techniques

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  • Author: Ronald H. Heck
  • Publisher: Psychology Press
  • ISBN: 1135678316
  • Category : Computers
  • Languages : en
  • Pages : 233

This book provides a broad overview of basic multilevel modeling issues and illustrates techniques building analyses around several organizational data sets. Although the focus is primarily on educational and organizational settings, the examples will help the reader discover other applications for these techniques. Two basic classes of multilevel models are developed: multilevel regression models and multilevel models for covariance structures--are used to develop the rationale behind these models and provide an introduction to the design and analysis of research studies using two multilevel analytic techniques--hierarchical linear modeling and structural equation modeling.


Generalized Latent Variable Modeling

Generalized Latent Variable Modeling

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  • Author: Anders Skrondal
  • Publisher: CRC Press
  • ISBN: 0203489438
  • Category : Mathematics
  • Languages : en
  • Pages : 528

This book unifies and extends latent variable models, including multilevel or generalized linear mixed models, longitudinal or panel models, item response or factor models, latent class or finite mixture models, and structural equation models. Following a gentle introduction to latent variable modeling, the authors clearly explain and contrast a wi


Structural Equation Modeling

Structural Equation Modeling

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  • Author: David Kaplan
  • Publisher: SAGE Publications
  • ISBN: 148334259X
  • Category : Social Science
  • Languages : en
  • Pages : 306

Using detailed, empirical examples, Structural Equation Modeling, Second Edition, presents a thorough and sophisticated treatment of the foundations of structural equation modeling (SEM). It also demonstrates how SEM can provide a unique lens on the problems social and behavioral scientists face. Intended Audience While the book assumes some knowledge and background in statistics, it guides readers through the foundations and critical assumptions of SEM in an easy-to-understand manner.


Structural Equation Modeling with Mplus

Structural Equation Modeling with Mplus

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  • Author: Barbara M. Byrne
  • Publisher: Routledge
  • ISBN: 1136663460
  • Category : Psychology
  • Languages : en
  • Pages : 431

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.


Longitudinal Structural Equation Modeling

Longitudinal Structural Equation Modeling

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  • Author: Todd D. Little
  • Publisher: Guilford Publications
  • ISBN: 1462553141
  • Category : Business & Economics
  • Languages : en
  • Pages : 642

Beloved for its engaging, conversational style, this valuable book is now in a fully updated second edition that presents the latest developments in longitudinal structural equation modeling (SEM) and new chapters on missing data, the random intercepts cross-lagged panel model (RI-CLPM), longitudinal mixture modeling, and Bayesian SEM. Emphasizing a decision-making approach, leading methodologist Todd D. Little describes the steps of modeling a longitudinal change process. He explains the big picture and technical how-tos of using longitudinal confirmatory factor analysis, longitudinal panel models, and hybrid models for analyzing within-person change. User-friendly features include equation boxes that translate all the elements in every equation, tips on what does and doesn't work, end-of-chapter glossaries, and annotated suggestions for further reading. The companion website provides data sets for the examples--including studies of bullying and victimization, adolescents' emotions, and healthy aging--along with syntax and output, chapter quizzes, and the book’s figures. New to This Edition: *Chapter on missing data, with a spotlight on planned missing data designs and the R-based package PcAux. *Chapter on longitudinal mixture modeling, with Whitney Moore. *Chapter on the random intercept cross-lagged panel model (RI-CLPM), with Danny Osborne. *Chapter on Bayesian SEM, with Mauricio Garnier. *Revised throughout with new developments and discussions, such as how to test models of experimental effects.


Handbook of Structural Equation Modeling

Handbook of Structural Equation Modeling

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  • Author: Rick H. Hoyle
  • Publisher: Guilford Publications
  • ISBN: 1462544649
  • Category : Business & Economics
  • Languages : en
  • Pages : 801

"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"--


The SAGE Handbook of Innovation in Social Research Methods

The SAGE Handbook of Innovation in Social Research Methods

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  • Author: Malcolm Williams
  • Publisher: SAGE Publications
  • ISBN: 1412946484
  • Category : Social Science
  • Languages : en
  • Pages : 665

Social research is a bourgeoning field. Of course it has many traditions and approaches, but there is a high premium upon thinking differently and thinking anew because social life is never static or wholly predictable. The Handbook, edited by internationally recognized scholars, provides a comprehensive, pitch-perfect critical assessment of the field. The main features of the Handbook are: Clear organization into 4 parts dealing with The Social Context of Research; Design and Data Collection; Integrating The Analysis of New Data Types; Sampling, Inference and Measurement Clear, cutting edge chapters on Objectivity; Causation; Organizing Social Research; Correspondence Analysis; Grounded Theory; Conversational Surveys; Mixed Methods; Meta-Analysis; Optimal Matching Analysis; GIS Analysis; Quantitative Narrative Analysis; Longitudinal Studies; SEM; MLM; Qualitative Comparative Analysis; Respondent Driven Sampling Brings together a glittering assembly of the key figures working in the field of research methods Demonstrates the continuities and productive tensions between classical traditions and real world research. The result is a superbly organized text which will be required reading for anyone interested in the routes and future of social research. It is an unparalleled teaching resource and a 'must have' for serious social researchers.


Using Mplus for Structural Equation Modeling

Using Mplus for Structural Equation Modeling

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  • Author: E. Kevin Kelloway
  • Publisher: SAGE Publications
  • ISBN: 1483313441
  • Category : Social Science
  • Languages : en
  • Pages : 249

Ideal for researchers and graduate students in the social sciences who require knowledge of structural equation modeling techniques to answer substantive research questions, Using Mplus for Structural Equation Modeling provides a reader-friendly introduction to the major types of structural equation models implemented in the Mplus framework. This practical book, which updates author E. Kevin Kelloway’s 1998 book Using LISREL for Structural Equation Modeling, retains the successful five-step process employed in the earlier book, with a thorough update for use in the Mplus environment. Kelloway provides an overview of structural equation modeling techniques in Mplus, including the estimation of confirmatory factor analysis and observed variable path analysis. He also covers multilevel modeling for hypothesis testing in real life settings and offers an introduction to the extended capabilities of Mplus, such as exploratory structural equation modeling and estimation and testing of mediated relationships. A sample application with the source code, printout, and results is presented for each type of analysis. ”An excellent book on the ins and outs of using Mplus, as well as the practice of structural equation modeling in applied research.” —Kevin J. Grimm, University of California, Davis