Introduction to Structural Equation Modeling (SEM)

Lecturers: Eldad Davidov & Peter Schmidt 

Modality: Online

Week 1: 14-18 August 2023


Workshop Contents and Objectives
The objective of this course is to show how structural equation modeling can be used to develop and/or test both measurement models (scales) and causal theories between latent variables with survey data. When discussing full structural equation modeling, we will treat formative and reflective indicators, mediation, indirect effects and moderation. A further important aim is to familiarise participants with the AMOS program. The program will be run by graphical input via path diagrams (AMOS Graphics). A special focus will be given to the analysis of comparative data across groups.

This includes how to test for measurement invariance using Multiple group confirmatory factor analysis. Participants are encouraged to bring their own data and apply the new procedures besides the prepared examples of the instructors in the practical sessions.


Some experience with regression analysis techniques is required. Basic knowledge of factor analysis is recommended.


Recommended Reading

Basic texts/overview

  • Arbuckle, J.L. (2019): AMOS 26.0 User's Guide. Chicago: SPSS/Erlbaum.
  • Brown, Timothy, A. (2015). Confirmatory Factor Analysis for Applied Research. New York: Guilford
  • Byrne, Barbara M. (2016): Structural equation modeling with AMOS. Basic concepts, application, and programming. 3rd Edition. Ney York: Routledge.
  • Davidov, E., P. Schmidt, J. Billiet and B. Meuleman (eds.) (2018). Cross-cultural analysis: Methods and applications. Second edition. NY: Routledge.
  • Kline, R. B. (2016). Principles and Practice of Structural Equation Modeling. Fourth edition. Guilford Press: New York.

Additional reading

  • Aleman JA, Schmidt P, Meitinger K and Meuleman B (2022) Editorial: Comparative political science and measurement invariance: Basic issues and current applications. Front. Polit. Sci. 4:1039744. doi: 10.3389/fpos.2022.1039744
  • Cieciuch, J., E. Davidov, P. Schmidt and R. Algesheimer (2016). The assessment of cross-cultural comparability. Pp. 630-648 in: C. Wolf, D. Joye, T. W. Smith & Y.-C. Fu (eds.), The Sage Handbook in Survey Methodology. New York: Sage.
  • Davidov, E., J. Cieciuch, B. Meuleman, P. Schmidt and J. Billiet (2014). Measurement equivalence in cross-national research. Annual Review of Sociology, 40, 55-75
  • Davidov, Schmidt and Schwartz (2008). Bringing values back in: the adequacy of the European social survey to measure values in 20 countries. Public opinion quarterly, 72, 420-445.
  • Davidov, Meuleman, Billiet and Schmidt (2008). Values and support for immigration: a cross-country comparison. European sociological review, 24, 583-599.
  • Davidov, E., D. Seddig, A. Gorodzeisky, R. Raijman, P. Schmidt and M. Semyonov (2020). Direct and indirect predictors of opposition to immigration in Europe: Individual values, cultural values, and symbolic threat.  Journal of Ethnic and Migration Studies, 46(3), 553-573.