Handbook of Structural Equation Modeling

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.