Handbook of Structural Equation Modeling

The first comprehensive structural equation modeling (SEM) handbook, this accessible volume presents both the mechanics of 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.

Rick Hoyle is Professor of Psychology and Neuroscience at Duke University, where he serves as Associate Director of the Center for Child and Family Policy and Director of the Methodology and Statistics Core in the Transdisciplinary Prevention Research Center. He is a Fellow of the Association for Psychological Science, the American Psychological Association, and the Society for Experimental Social Psychology. He has written extensively on SEM and other statistical and methodological strategies for the study of complex social and behavioral processes

"The impressive author list reads like a 'who's who' in Structural Equation Modeling (SEM) - and they cover all the major (and most of the minor) issues in the field. I highly recommend this handbook to researchers using SEM as the next book they need after reading one of the introductory texts. I like the hands-on approach in many of the chapters; in my view, there is no such thing as a superfluous example." - Joop J. Hox, Utrecht University, The Netherlands "An exceptionally useful and comprehensive resource, the Handbook of Structural Equation Modeling covers all facets of this flexible approach to data analysis. Accessible to analysts in numerous scientific fields, it begins with foundational materials on model formulation and representation, continuing through estimation, assessment, and interpretation. With due attention to conceptual issues and matters of implementation alike, this handbook strikes an excellent balance between fundamentals, extensions, applications, and current innovations." - Peter V. Marsden, Harvard University, Massachusetts, USA "This cutting-edge book is an exceptionally ambitious scholarly masterpiece. Broad in scope, the many self-contained chapters cover the basics and extend SEM to the four corners of statistical analysis. This is a crucial contribution to the literature for behavioral and social scientists, applied statisticians and econometricians, and researchers in the business, education, and health disciplines." - Richard P. Bagozzi, University of Michigan, USA "An absolutely remarkable book. It spans every conceivable topic - from history to fundamentals to the most advanced topics under development - and brings together the leading scientists currently working in statistical design and analysis. The chapters are technically rigorous yet accessible to a broad audience. This is a great reference for all who are interested in SEM, whether novices or seasoned professionals." - Patrick J. Curran, University of North Carolina at Chapel Hill, USA "In this welcome addition to the personal libraries of quantitative and applied researchers alike, Rick Hoyle brings considerable editorial skill to bear on the 40-chapter Handbook of Structural Equation Modeling. The breadth of topics covered in this reference text leaves little doubt that a firm grasp of data analysis with latent variables is essential to the advancement of scholarship in the social and behavioral sciences...An excellent resource for the many conceptual and analytical problems frequently encountered by researchers making use of SEM. About half of the chapters remain true to the Handbook's objective of accessibility to a novice readership (Chapters 1-4, 6-10, 12, 13, 15, 16, 19, 21, 22, 27-29, and 31), and several others are more suitable for readers with a modest background in latent variable modeling (Chapters 11, 14, 18, 20, 23, 25, 32, 34, and 36-40). A small number of chapters are suitable for advanced readers and those actively working in a quantitative discipline (Chapters 5, 30, 33, and 35). As a reference text, it