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Author: Otis Dudley Duncan
Publisher: Elsevier
ISBN: 148329532X
Category : Mathematics
Languages : en
Pages : 193
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Book Description
Introduction to Structural Equation Models prepares the reader to understand the recent sociological literature on the use of structural equation models in research, and discusses methodological questions pertaining to such models. The material in first seven chapters is almost entirely standard, with the remaining four introducing progressively more open-ended issues, seducing the reader into beginning to think for himself about the properties of models or even to suggest problems that may intrigue the advanced student.
Author: Otis Dudley Duncan
Publisher: Elsevier
ISBN: 148329532X
Category : Mathematics
Languages : en
Pages : 193
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Book Description
Introduction to Structural Equation Models prepares the reader to understand the recent sociological literature on the use of structural equation models in research, and discusses methodological questions pertaining to such models. The material in first seven chapters is almost entirely standard, with the remaining four introducing progressively more open-ended issues, seducing the reader into beginning to think for himself about the properties of models or even to suggest problems that may intrigue the advanced student.
Author: Joseph F. Hair Jr.
Publisher: Springer Nature
ISBN: 3030805190
Category : Business & Economics
Languages : en
Pages : 208
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Book Description
Partial least squares structural equation modeling (PLS-SEM) has become a standard approach for analyzing complex inter-relationships between observed and latent variables. Researchers appreciate the many advantages of PLS-SEM such as the possibility to estimate very complex models and the method’s flexibility in terms of data requirements and measurement specification. This practical open access guide provides a step-by-step treatment of the major choices in analyzing PLS path models using R, a free software environment for statistical computing, which runs on Windows, macOS, and UNIX computer platforms. Adopting the R software’s SEMinR package, which brings a friendly syntax to creating and estimating structural equation models, each chapter offers a concise overview of relevant topics and metrics, followed by an in-depth description of a case study. Simple instructions give readers the “how-tos” of using SEMinR to obtain solutions and document their results. Rules of thumb in every chapter provide guidance on best practices in the application and interpretation of PLS-SEM.
Author: Rick H. Hoyle
Publisher: Guilford Publications
ISBN: 1462544649
Category : Business & Economics
Languages : en
Pages : 801
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Book Description
"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"--
Author: Rex B. Kline
Publisher: Guilford Publications
ISBN: 1462523005
Category : Social Science
Languages : en
Pages : 554
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Book Description
This book has been replaced by Principles and Practice of Structural Equation Modeling, Fifth Edition, ISBN 978-1-4625-5191-0.
Author: Niels Blunch
Publisher: SAGE
ISBN: 1446204790
Category : Social Science
Languages : en
Pages : 281
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Book Description
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.
Author: Ralph O. Mueller
Publisher: Springer Science & Business Media
ISBN: 1461239745
Category : Social Science
Languages : en
Pages : 252
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Book Description
During the last two decades, structural equation modeling (SEM) has emerged as a powerful multivariate data analysis tool in social science research settings, especially in the fields of sociology, psychology, and education. Although its roots can be traced back to the first half of this century, when Spearman (1904) developed factor analysis and Wright (1934) introduced path analysis, it was not until the 1970s that the works by Karl Joreskog and his associates (e. g. , Joreskog, 1977; Joreskog and Van Thillo, 1973) began to make general SEM techniques accessible to the social and behavioral science research communities. Today, with the development and increasing avail ability of SEM computer programs, SEM has become a well-established and respected data analysis method, incorporating many of the traditional analysis techniques as special cases. State-of-the-art SEM software packages such as LISREL (Joreskog and Sorbom, 1993a,b) and EQS (Bentler, 1993; Bentler and Wu, 1993) handle a variety of ordinary least squares regression designs as well as complex structural equation models involving variables with arbitrary distributions. Unfortunately, many students and researchers hesitate to use SEM methods, perhaps due to the somewhat complex underlying statistical repre sentation and theory. In my opinion, social science students and researchers can benefit greatly from acquiring knowledge and skills in SEM since the methods-applied appropriately-can provide a bridge between the theo retical and empirical aspects of behavioral research.
Author: Niels Blunch
Publisher: SAGE
ISBN: 1446271846
Category : Reference
Languages : en
Pages : 314
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Book Description
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
Author: Geoffrey M. Maruyama
Publisher: SAGE Publications
ISBN: 150632035X
Category : Social Science
Languages : en
Pages : 328
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Book Description
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.
Author: Kenneth A. Bollen
Publisher: John Wiley & Sons
ISBN: 111861903X
Category : Mathematics
Languages : en
Pages : 528
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Book Description
Analysis of Ordinal Categorical Data Alan Agresti Statistical Science Now has its first coordinated manual of methods for analyzing ordered categorical data. This book discusses specialized models that, unlike standard methods underlying nominal categorical data, efficiently use the information on ordering. It begins with an introduction to basic descriptive and inferential methods for categorical data, and then gives thorough coverage of the most current developments, such as loglinear and logit models for ordinal data. Special emphasis is placed on interpretation and application of methods and contains an integrated comparison of the available strategies for analyzing ordinal data. This is a case study work with illuminating examples taken from across the wide spectrum of ordinal categorical applications. 1984 (0 471-89055-3) 287 pp. Regression Diagnostics Identifying Influential Data and Sources of Collinearity David A. Belsley, Edwin Kuh and Roy E. Welsch This book provides the practicing statistician and econometrician with new tools for assessing the quality and reliability of regression estimates. Diagnostic techniques are developed that aid in the systematic location of data points that are either unusual or inordinately influential; measure the presence and intensity of collinear relations among the regression data and help to identify the variables involved in each; and pinpoint the estimated coefficients that are potentially most adversely affected. The primary emphasis of these contributions is on diagnostics, but suggestions for remedial action are given and illustrated. 1980 (0 471-05856-4) 292 pp. Applied Regression Analysis Second Edition Norman Draper and Harry Smith Featuring a significant expansion of material reflecting recent advances, here is a complete and up-to-date introduction to the fundamentals of regression analysis, focusing on understanding the latest concepts and applications of these methods. The authors thoroughly explore the fitting and checking of both linear and nonlinear regression models, using small or large data sets and pocket or high-speed computing equipment. Features added to this Second Edition include the practical implications of linear regression; the Durbin-Watson test for serial correlation; families of transformations; inverse, ridge, latent root and robust regression; and nonlinear growth models. Includes many new exercises and worked examples. 1981 (0 471-02995-5) 709 pp.
Author: Jörg Henseler
Publisher: Guilford Publications
ISBN: 1462545610
Category : Social Science
Languages : en
Pages : 387
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Book Description
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.
