Statistical Applications in Criminology and Criminal Justice 2015-2016
Structural Equation Modeling
Dr. James Jaccard
This seminar provides an introduction to structural equation modeling. It describes the core elements of causal models (including the concepts of mediation and moderation) and how to translate those models into a system of linear equations. The equations are then used to test the viability of the model by comparing predicted patterns of correlations/covariances with observed correlations/covariances in one's data. The seminar will provide an intuitive understanding of the logic underlying this approach and formally compare SEM to more traditional multiple regression based strategies. Strategies for addressing measurement error and complex error structures are introduced.
Bollen, K. (1989). Structural equations with latent variables. New York: Wiley.
Bollen, K. & Long, S. (1993). Testing structural equation models. Newbury Park: Sage.
Byrne, B. (2009). Structural equation modeling with AMOS: Basic concepts, applications and programming. Matwah, NJ: Erlbaum
Kaplan, D. (2008). Structural equation modeling: Foundations and extensions. Newbury Park: Sage.
Kline, R. (2010). Principles and practice of structural equation modeling. New York: Guilford.
Geiser, C. (2012). Data analysis with M Plus. New York: Guilford