Download or read book Structural Equation Modeling for Health and Medicine written by Douglas D. Gunzler and published by CRC Press. This book was released on 2021-03-29 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: Structural equation modeling (SEM) is a very general and flexible multivariate technique that allows relationships among variables to be examined. The roots of SEM are in the social sciences. In writing this textbook, the authors look to make SEM accessible to a wider audience of researchers across many disciplines, addressing issues unique to health and medicine. SEM is often used in practice to model and test hypothesized causal relationships among observed and latent (unobserved) variables, including in analysis across time and groups. It can be viewed as the merging of a conceptual model, path diagram, confirmatory factor analysis, and path analysis. In this textbook the authors also discuss techniques, such as mixture modeling, that expand the capacity of SEM using a combination of both continuous and categorical latent variables. Features: Basic, intermediate, and advanced SEM topics Detailed applications, particularly relevant for health and medical scientists Topics and examples that are pertinent to both new and experienced SEM researchers Substantive issues in health and medicine in the context of SEM Both methodological and applied examples Numerous figures and diagrams to illustrate the examples As SEM experts situated among clinicians and multidisciplinary researchers in medical settings, the authors provide a broad, current, on the ground understanding of the issues faced by clinical and health services researchers and decision scientists. This book gives health and medical researchers the tools to apply SEM approaches to study complex relationships between clinical measurements, individual and community-level characteristics, and patient-reported scales.

Download or read book Basics of Structural Equation Modeling written by Geoffrey M. Maruyama and published by SAGE Publications. This book was released on 1997-09-22 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Longitudinal Structural Equation Modeling written by Todd D. Little and published by Guilford Publications. This book was released on 2023-12-27 with total page 642 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Structural Equation Modeling for Health and Medicine written by Douglas D. Gunzler and published by CRC Press. This book was released on 2021-04-12 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: Structural equation modeling (SEM) is a very general and flexible multivariate technique that allows relationships among variables to be examined. The roots of SEM are in the social sciences. In writing this textbook, the authors look to make SEM accessible to a wider audience of researchers across many disciplines, addressing issues unique to health and medicine. SEM is often used in practice to model and test hypothesized causal relationships among observed and latent (unobserved) variables, including in analysis across time and groups. It can be viewed as the merging of a conceptual model, path diagram, confirmatory factor analysis, and path analysis. In this textbook the authors also discuss techniques, such as mixture modeling, that expand the capacity of SEM using a combination of both continuous and categorical latent variables. Features: Basic, intermediate, and advanced SEM topics Detailed applications, particularly relevant for health and medical scientists Topics and examples that are pertinent to both new and experienced SEM researchers Substantive issues in health and medicine in the context of SEM Both methodological and applied examples Numerous figures and diagrams to illustrate the examples As SEM experts situated among clinicians and multidisciplinary researchers in medical settings, the authors provide a broad, current, on the ground understanding of the issues faced by clinical and health services researchers and decision scientists. This book gives health and medical researchers the tools to apply SEM approaches to study complex relationships between clinical measurements, individual and community-level characteristics, and patient-reported scales.

Download or read book Composite Based Structural Equation Modeling written by Jörg Henseler and published by Guilford Publications. This book was released on 2020-12-24 with total page 387 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents powerful tools for integrating interrelated composites--such as capabilities, policies, treatments, indices, and systems--into structural equation modeling (SEM). Jörg Henseler introduces the types of research questions that can be addressed with composite-based SEM and explores the differences between composite- and factor-based SEM, variance- and covariance-based SEM, and emergent and latent variables. Using rich illustrations and walked-through data sets, the book covers how to specify, identify, estimate, and assess composite models using partial least squares path modeling, maximum likelihood, and other estimators, as well as how to interpret findings and report the results. Advanced topics include confirmatory composite analysis, mediation analysis, second-order constructs, interaction effects, and importance–performance analysis. Most chapters conclude with software tutorials for ADANCO and the R package cSEM. The companion website includes data files and syntax for the book's examples, along with presentation slides.

Download or read book Handbook of Structural Equation Modeling written by Rick H. Hoyle and published by Guilford Publications. This book was released on 2023-02-17 with total page 801 pages. Available in PDF, EPUB and Kindle. Book excerpt: "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"--

Download or read book Structural Equation Modeling with Mplus written by Barbara M. Byrne and published by Routledge. This book was released on 2013-06-17 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Principles and Practice of Structural Equation Modeling written by Rex B. Kline and published by Guilford Publications. This book was released on 2015-10-08 with total page 554 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book has been replaced by Principles and Practice of Structural Equation Modeling, Fifth Edition, ISBN 978-1-4625-5191-0.

Download or read book Introduction to Structural Equation Modeling Using IBM SPSS Statistics and Amos written by Niels Blunch and published by SAGE. This book was released on 2012-11-09 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive Second Edition offers readers a complete guide to carrying out research projects involving structural equation modeling (SEM). Updated to include extensive analysis of AMOS′ graphical interface, a new chapter on latent curve models and detailed explanations of the structural equation modeling process, this second edition is the ideal guide for those new to the field. The book includes: Learning objectives, key concepts and questions for further discussion in each chapter. Helpful diagrams and screenshots to expand on concepts covered in the texts. Real life examples from a variety of disciplines to show how SEM is applied in real research contexts. Exercises for each chapter on an accompanying companion website. A new glossary. Assuming no previous experience of the subject, and a minimum of mathematical knowledge, this is the ideal guide for those new to SEM and an invaluable companion for students taking introductory SEM courses in any discipline. Niels J. Blunch was formerly in the Department of Marketing and Statistics at the University of Aarhus, Denmark

Download or read book Structural Equation Modeling of Health Belief Model Influences on Exercise Behavior Among Medical Center Employees written by Charles Michael Cychosz and published by . This book was released on 1994 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Structural Equation Modeling written by David Kaplan and published by SAGE Publications. This book was released on 2008-07-23 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Structural Equation Modeling written by Sik-Yum Lee and published by John Wiley & Sons. This book was released on 2007-04-04 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: ***Winner of the 2008 Ziegel Prize for outstanding new book of the year*** Structural equation modeling (SEM) is a powerful multivariate method allowing the evaluation of a series of simultaneous hypotheses about the impacts of latent and manifest variables on other variables, taking measurement errors into account. As SEMs have grown in popularity in recent years, new models and statistical methods have been developed for more accurate analysis of more complex data. A Bayesian approach to SEMs allows the use of prior information resulting in improved parameter estimates, latent variable estimates, and statistics for model comparison, as well as offering more reliable results for smaller samples. Structural Equation Modeling introduces the Bayesian approach to SEMs, including the selection of prior distributions and data augmentation, and offers an overview of the subject’s recent advances. Demonstrates how to utilize powerful statistical computing tools, including the Gibbs sampler, the Metropolis-Hasting algorithm, bridge sampling and path sampling to obtain the Bayesian results. Discusses the Bayes factor and Deviance Information Criterion (DIC) for model comparison. Includes coverage of complex models, including SEMs with ordered categorical variables, and dichotomous variables, nonlinear SEMs, two-level SEMs, multisample SEMs, mixtures of SEMs, SEMs with missing data, SEMs with variables from an exponential family of distributions, and some of their combinations. Illustrates the methodology through simulation studies and examples with real data from business management, education, psychology, public health and sociology. Demonstrates the application of the freely available software WinBUGS via a supplementary website featuring computer code and data sets. Structural Equation Modeling: A Bayesian Approach is a multi-disciplinary text ideal for researchers and students in many areas, including: statistics, biostatistics, business, education, medicine, psychology, public health and social science.

Download or read book A First Course in Structural Equation Modeling written by Tenko Raykov and published by Routledge. This book was released on 2012-08-21 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, authors Tenko Raykov and George A. Marcoulides introduce students to the basics of structural equation modeling (SEM) through a conceptual, nonmathematical approach. For ease of understanding, the few mathematical formulas presented are used in a conceptual or illustrative nature, rather than a computational one. Featuring examples from EQS, LISREL, and Mplus, A First Course in Structural Equation Modeling is an excellent beginner’s guide to learning how to set up input files to fit the most commonly used types of structural equation models with these programs. The basic ideas and methods for conducting SEM are independent of any particular software. Highlights of the Second Edition include: • Review of latent change (growth) analysis models at an introductory level • Coverage of the popular Mplus program • Updated examples of LISREL and EQS • Downloadable resources that contains all of the text’s LISREL, EQS, and Mplus examples. A First Course in Structural Equation Modeling is intended as an introductory book for students and researchers in psychology, education, business, medicine, and other applied social, behavioral, and health sciences with limited or no previous exposure to SEM. A prerequisite of basic statistics through regression analysis is recommended. The book frequently draws parallels between SEM and regression, making this prior knowledge helpful.

Download or read book Introduction to Structural Equation Modelling Using SPSS and Amos written by Niels Blunch and published by SAGE. This book was released on 2012-06-21 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Structural Equation Modelling using SPSS and AMOS is a complete guide to carrying out your own structural equation modelling project. Assuming no previous experience of the subject, and a minimum of mathematical knowledge, this is the ideal guide for those new to structural equation modelling (SEM). Each chapter begins with learning objectives, and ends with a list of the new concepts introduced and questions to open up further discussion. Exercises for each chapter, incuding the necessary data, can be downloaded from the book′s website. Helpful real life examples are included throughout, drawing from a wide range of disciplines including psychology, political science, marketing and health. Introduction to Structural Equation Modelling using SPSS and AMOS provides engaging and accessible coverage of all the basics necessary for using SEM, making it an invaluable companion for students taking introductory SEM courses in any discipline.

Download or read book Structural Equation Modeling for Social and Personality Psychology written by Rick H Hoyle and published by SAGE. This book was released on 2011-02-15 with total page 121 pages. Available in PDF, EPUB and Kindle. Book excerpt: Structural Equation Modeling offers a nontechnical presentation of SEM with an emphasis on applications in social and personality psychology. The presentation begins with a discussion of the relation between SEM and statistical strategies widely used in social and personality psychology such as analysis of variance, multiple regression analysis, and factor analysis. This introduction is followed by a nontechnical presentation of the terminology, notation, and steps followed in a typical application of SEM. The reminder of the volume offers a practically-oriented presentation of specific applications using examples typical of social and personality psychology and offering advice for dealing with relevant issues such as missing data, choice of software, and best practices for interpreting and reporting results. The SAGE Library in Social and Personality Psychology Methods provides students and researchers with an understanding of the methods and techniques essential to conducting cutting-edge research. Each volume within the Library explains a specific topic and has been written by an active scholar (or scholars) with expertise in that particular methodological domain. Assuming no prior knowledge of the topic, the volumes are clear and accessible for all readers. In each volume, a topic is introduced, applications are discussed, and readers are led step by step through worked examples. In addition, advice about how to interpret and prepare results for publication are presented.

Download or read book Structural Equation Modeling of the Medical Outcome Study Short Form 36 SF 36 written by Pamala Jean Reed and published by . This book was released on 1997 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: The factorial validity of the SF-36 was evaluated using confirmatory factor analysis (CFA) methods, structural equation modeling (SEM), and multigroup structural equation modeling (MSEM). First, the measurement and structural model of the hypothesized SF-36 was explicated. Second, the model was tested for the validity of a second-order factorial structure, upon evidence of model misfit, determined the best-fitting model, and tested the validity of the best-fitting model on a second random sample from the same population. Third, the best-fitting model was tested for invariance of the factorial structure across race, age, and educational subgroups using MSEM.

Download or read book Longitudinal Structural Equation Modeling written by Jason T. Newsom and published by Routledge. This book was released on 2015-06-19 with total page 657 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.