Structural Equation Modeling for Health and Medicine

Structural Equation Modeling for Health and Medicine

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  • Author: Douglas D. Gunzler
  • Publisher: CRC Press
  • ISBN: 1351329715
  • Category : Mathematics
  • Languages : en
  • Pages : 318

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.


Structural Equation Modeling for Health and Medicine

Structural Equation Modeling for Health and Medicine

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  • Author: Douglas D. Gunzler
  • Publisher: CRC Press
  • ISBN: 1351329723
  • Category : Mathematics
  • Languages : en
  • Pages : 299

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.


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"--


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 : 432

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.


Basics of Structural Equation Modeling

Basics of Structural Equation Modeling

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  • Author: Geoffrey M. Maruyama
  • Publisher: SAGE Publications
  • ISBN: 150632035X
  • Category : Social Science
  • Languages : en
  • Pages : 328

With the availability of software programs, such as LISREL, EQS, and AMOS, modeling (SEM) techniques have become a popular tool for formalized presentation of the hypothesized relationships underlying correlational research and test for the plausibility of hypothesizing for a particular data set. Through the use of careful narrative explanation, Maruyama's text describes the logic underlying 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. In addition, Maruyama provides carefully constructed exercises both within and


Principles and Practice of Structural Equation Modeling

Principles and Practice of Structural Equation Modeling

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  • Author: Rex B. Kline
  • Publisher: Guilford Publications
  • ISBN: 1462523005
  • Category : Social Science
  • Languages : en
  • Pages : 554

This book has been replaced by Principles and Practice of Structural Equation Modeling, Fifth Edition, ISBN 978-1-4625-5191-0.


Composite-Based Structural Equation Modeling

Composite-Based Structural Equation Modeling

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  • Author: Jörg Henseler
  • Publisher: Guilford Publications
  • ISBN: 1462545610
  • Category : Social Science
  • Languages : en
  • Pages : 387

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.


A First Course in Structural Equation Modeling

A First Course in Structural Equation Modeling

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  • Author: Tenko Raykov
  • Publisher: Routledge
  • ISBN: 1135600767
  • Category : Business & Economics
  • Languages : en
  • Pages : 248

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.


Evidence-Based Health Care Management

Evidence-Based Health Care Management

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  • Author: Thomas T.H. Wan
  • Publisher: Springer Science & Business Media
  • ISBN: 1461507952
  • Category : Business & Economics
  • Languages : en
  • Pages : 240

Evidence-Based Health Care Management introduces the principles and methods for drawing sound causal inferences in research on health services management. The emphasis is on the application of structural equation modeling techniques and other analytical methods to develop causal models in health care management. Topics include causality, theoretical model building, and model verification. Multivariate modeling approaches and their applications in health care management are illustrated. The primary goals of the book are to present advanced principles of health services management research and to familiarize students with the multivariate analytic methods and procedures now in use in scientific research on health care management. The hope is to help health care managers become better equipped to use causal modeling techniques for problem solving and decision making. Evidence-based knowledge is derived from scientific replication and verification of facts. Used consistently and appropriately, it enables a health care manager to improve organizational performance. Causal inference in health care management is a highly feasible approach to establishing evidence-based knowledge that can help navigate an organization to high performance. This book introduces the principles and methods for drawing causal inferences in research on health services management.