This popular text provides an accessible guide to the application, interpretation, and pitfalls of structural equation modeling (SEM). Reviewed are fundamental statistical concepts--such as correlation, regressions, data preparation and screening, path analysis, and confirmatory factor analysis--as well as more advanced methods, including the evaluation of nonlinear effects, measurement models and structural regression models, latent growth models, and multilevel SEM.

Special Features: The companion Web page offers data and program syntax files for many of the research examples, electronic overheads that can be downloaded and printed by instructors or students, and links to SEM-related resources.

This title is part of the Methodology in the Social Sciences Series, edited by Todd D. Little.