Handbook of structural equation modeling
"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...
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| Format: | UnknownFormat |
| Sprache: | eng |
| Veröffentlicht: |
New York, London
The Guilford Press
2023
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| Ausgabe: | Second edition |
| Schlagworte: | |
| Online Zugang: | Inhaltsverzeichnis |
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Tag hinzufügen | Zusammenfassung: | "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"-- "The definitive one-stop resource on structural equation modeling (SEM) from leading methodologists is now in a significantly revised second edition. Twenty-three new chapters cover model selection, bifactor models, item parceling, multitrait-multimethod models, exploratory SEM, mixture models, SEM with small samples, and more. The book moves from fundamental SEM topics (causality, visualization, assumptions, estimation, model fit, and managing missing data); to major model types focused on unobserved causes of covariance between observed variables; to more complex, specialized applications. Each chapter provides conceptually oriented descriptions, fully explicated analyses, and engaging examples that reveal modeling possibilities for use with the reader's data. The expanded companion website presents full datasets, code, and output for many of the chapters, as well as bonus selected chapters from the prior edition. New to This Edition *Chapters on additional topics not mentioned above: SEM-based meta-analysis, dynamic SEM, machine-learning approaches, and more. *Chapters include computer code associated with example analyses (in Mplus and/or the R package lavaan), along with written descriptions of results. *60% new material reflects a decade's worth of developments in the mechanics and application of SEM. *Many new contributors and fully rewritten chapters. "-- |
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| Beschreibung: | Literaturangaben |
| Beschreibung: | xiv, 785 Seiten Diagramme |
| ISBN: | 9781462544646 978-1-4625-4464-6 |