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      An overview of structural equation modeling: its beginnings, historical development, usefulness and controversies in the social sciences.

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      Springer Science and Business Media LLC
      Structural equation modeling, Development and usefulness of SEM, Controversies of SEM, Areas of applications in social science research

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          Abstract

          This paper is a tribute to researchers who have significantly contributed to improving and advancing structural equation modeling (SEM). It is, therefore, a brief overview of SEM and presents its beginnings, historical development, its usefulness in the social sciences and the statistical and philosophical (theoretical) controversies which have often appeared in the literature pertaining to SEM. Having described the essence of SEM in the context of causal analysis, the author discusses the years of the development of structural modeling as the consequence of many researchers' systematically growing needs (in particular in the social sciences) who strove to effectively understand the structure and interactions of latent phenomena. The early beginnings of SEM models were related to the work of Spearman and Wright, and to that of other prominent researchers who contributed to SEM development. The importance and predominance of theoretical assumptions over technical issues for the successful construction of SEM models are also described. Then, controversies regarding the use of SEM in the social sciences are presented. Finally, the opportunities and threats of this type of analytical strategy as well as selected areas of SEM applications in the social sciences are discussed.

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            A New Incremental Fit Index for General Structural Equation Models

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              Structural Equation Modeling with AMOS : Basic Concepts, Applications, and Programming

              <p>This bestselling text provides a practical guide to the basic concepts of structural equation modeling (SEM) and the AMOS program (Versions 17 & 18). The author reviews SEM applications based on actual data taken from her research. Noted for its non-mathematical language, this book is written for the novice SEM user. With each chapter, the author "walks" the reader through all steps involved in testing the SEM model including: </p><ul><p><li>an explanation of the issues addressed </li><p></p><p><li>an illustration of the hypothesized and posthoc models tested </li><p></p><p><li>AMOS input and output with accompanying interpretation and explanation</li><p></p><p><li>The function of the AMOS toolbar icons and their related pull-down menus</li><p></p><p><li>The data and published reference upon which the model was based.</li><p></p></ul><p></p><p>With over 50% new material, highlights of the new edition include:</p><ul><p><li>All new screen shots featuring Version 17 of the AMOS program </li><p></p><p><li>All data files now available at www.psypress.com/sem-with-amos </li><p></p><p><li>Application of a multitrait-mulitimethod model, latent growth curve model, and second-order model based on categorical data</li><p></p><p><li>All applications based on the most commonly used graphical interface</li><p></p><p><li>The automated multi-group approach to testing for equivalence</li><p></p></ul><p></p><p>The book opens with an introduction to the fundamental concepts of SEM and the basics of the AMOS program. The next 3 sections present applications that focus on single-group, multiple-group, and multitrait-mutimethod and latent growth curve models. The book concludes with a discussion about non-normal and missing (incomplete) data and two applications capable of addressing these issues. </p><p></p><p>Intended for researchers, practitioners, and students who use SEM and AMOS in their work, this book is an ideal resource for graduate level courses on SEM taught in departments of psychology, education, business, and other social and health sciences and/or as a supplement in courses on applied statistics, multivariate statistics, statistics II, intermediate or advanced statistics, and/or research design. Appropriate for those with limited or no previous exposure to SEM, a prerequisite of basic statistics through regression analysis is recommended. </p>
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                Author and article information

                Journal
                29416184
                5794813
                10.1007/s11135-017-0469-8

                Structural equation modeling,Development and usefulness of SEM,Controversies of SEM,Areas of applications in social science research

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