300082 Structural Equation Modeling with Lavaan (engl.) (S) (WiSe 2014/2015)

This course will give a basic introduction into the techniques of causal modelling and shows how a theoretical model
containing causal relationships can be represented by a path or structural equation model (SEM) to be applied to empirical data. Different specifications of measurement models are tested with confirmatory factor analysis. We will expand these models to allow measurement and structural relations in the model simultaneously. The usefulness of such models for measuring attitudinal and behavioural aspects will also be addressed. Different aspects related to cross-sectional, cross-cultural and longitudinal designs are emphasized.

Techniques of structural equation modeling will be shown with the program Lavaan:
http://lavaan.ugent.be/

Most examples are used from the Manual of Lavaan. Some examples are modified for clarification and better understanding. Some other examples are added. Participants should have basic knowledge in statistical data analysis with programs like SPSS, SAS or STATA which are required by Master and Diploma degrees. Participants should have knowledge to run data analysis with script-files (e. g, sps-files in SPSS, do-files in STATA).

References:
A. Beaujean (2014). Latent Variable Modeling using R, Routledge.

Bollen, K. A. & Curran, P. J. (2006). Latent curve models: A structural equation perspective. New Jersey: Wiley.

Bollen, K. A. (1989). Structural equations with latent variables. New York: Wiley.

Bollen, K. A. / Long, J. S. (Eds.). (1993). Testing structural equation models. Newbury Park: Sage.

Bortz, J. (2005). Statistik für Human- und Sozialwissenschaftler (6. Auflage). Berlin: Springer.

Byrne, B. M. (2012). Structural equation modeling with Mplus. New York: Taylor & Francis.

Christ, O. & Schlüter, E. (2012). Strukturgleichungsmodelle mit Mplus. München: Oldenbourg.

Duncan, T. E., Duncan, S. C., Strycker, L. A., Li, F., & Alpert, A. (2006). An introduction to latent variable growth curve modeling: Concepts, issues, and applications. Mahwah: Lawrence Erlbaum.

Enders, C. K. (2010). Applied missing data analysis. New York and London: Guilford Press.

Geiser, C. (2013). Data analysis with Mplus. New York: Guilford Press.

Hancock, G. R., & Mueller, R. O. (2006) (Eds.). Structural equation modeling: A second course.
Greenwich, CT: Information Age Publishing.

Hox, J. J. (2010). Multilevel analysis. Techniques and applications. Mahwah: Lawrence Erlbaum.

Kaplan, D. (2009). Structural equation modeling: Foundations and extensions. Los Angeles: Sage.

Kline, R. B. (2011). Principles and practice of structural equation modeling.
3nd. Edition, New York: Guilford Press.

Mulaik, S. A. (2009). Linear causal modeling with structural equations.
Boca Raton: Chapman Hall.

\item Muthén, L., & Muthén, B. O. (1998-2012). Mplus users guide (Version 7).
Los Angeles: Muthén & Muthén.

Raykov, T., & Marcoulides, G. A. (2006). A first course in structural equation modeling.
Mahwah: Lawrence Erlbaum.

Reinecke, J. (2014). Strukturgleichungsmodelle in den Sozialwissenschaften. 2. Auflage.
München: DeGruyter & Oldenbourg.

Reinecke, J. (2012). Wachstumsmodelle. Mehring: Rainer Hampp.

Schumacker, R. E., & Lomax, R. G. (2010). A beginners guide to structural equation modeling (3nd ed.).
New York: Taylor & Francis.

Weiber, R. & Mühlhaus, D. (2014). Strukturgleichungsmodellierung (2. Auflage). Wiesbaden: Gabler & Springer.