This course introduces a wide range of topics in structural equation models with latent variables, including history, underlying theory, controversy, applications in personality and social psychological research, and practical use in model specification with major existing computer packages. Specific topics include model specification, estimation, modification, evaluation, and comparisons. In addition, most recent developments in the field, including debates on goodness-of-fit and model modification, as well as modeling factor structures with "special" data situations (i.e., non-normal data, missing data, "other than" interval level data, nested data, growth, mixed models, are also considered.

This course is partitioned into three sections. The first section deals with basic issues in covariance structure modeling, including logic behind these models, criticisms, and issues in identification, estimation, and assessment of model fit. The second section examines some published applications and begins to explore various "special" data situations. The final section demonstrates the utility and flexibility of these models in multimodal cases -- that is, where observations are made across groups, methods, situations, and/or time.