The definitive one-stop resource on structural equation modeling (SEM) is now in a significantly revised second edition. New chapters cover 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. 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.