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 data sets 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. |Handbook of Structural Equation Modeling Second Edition | Psychology
