Essex Summer School in
Social Science Data Analysis

Peter Schmidt

Peter Schmidt is Professor at the research training school “group related enmity” of the German Science Foundation at the University of Marburg. His research interests are the foundations and applications of structural equations models, analysis of panel data, and empirically testing rational choice theory. Applications include studies of national identity, inter-ethnic relations, and environmental behaviour. He has published several books and many papers on these topics in the European Sociological Review, Social Science Research, International Journal of Cross-Cultural Sociology, International Journal of Conflict and Violence Research, Basic and Applied Social Psychology, Journal of Applied Social Psychology, Journal of Social Issues, Methodology, Political Psychology, Public Opinion Quarterly, International Journal of Public Opinion Research, Quality and Quantity, Rationality and Society, Sociological methods and Research, and Environment and Behaviour.

2H Causal Models and Structural Equations

Peter Schmidt, University of Giessen
23 July - 3 August (two week course / 35 hrs)

Detailed Course Outline [PDF] 

Course Content

The course shows how a causal theory can be represented translated into a structural equation model, and how the model can be estimated and tested with the MPLUS 6.1 computer programme. In the first part, we deal with confirmatory factor analysis (CFA) relating single or multiple indicators to one (CFA) or several latent variables(SCFA). Different specifications of measurement models are tested via confirmatory factor analysis (CFA) as a special case of a structural equation model (SEM). Special emphasis is given to the cross cultural analysis of multiple groups (MGCFA) for comparisons within societies and between societies including intercepts and latent means. The second part comprises both the structural model and the measurement model. Topics include recursive vs. non-recursive models for the structural part of the model, Moderation (Interaction effects) and mediation, missing data, use of formative vs. reflective indicators in MIMIC Models. Special emphasis is directed toward the use of the multiple-group option, for cross-national comparisons of both the measurement and the structural model. Special attention is given to the process of model modification and alternative model testing using adequate fit measures and how to report CFA and SEM results.

Course Objectives

The objectives of this course are to show how confirmatory factor analysis and structural equation modelling can be used to develop and/or test both measurement models and causal theories with latent variables. A further important aim is to familiarize participants with the MPLUS programme to handle the most important standard models especially for comparisons within and between societies. The programme will be run by syntax.

Course Prerequisites

Participants are expected to have extensive familiarity with Windows applications, good knowledge of exploratory factor analysis and regression analysis is required.

Remedial Reading

T. Brown, (2006). Confirmatory Factor Analysis for Applied Research. Guilford Press.

R. E. Schumacker/R.G.Lomax (2004). A Beginners Guide to Structural Equation Modeling (2nd edition). Erlbaum.

B. Muthen, L. Muthen, (2009). Mplus manual, available from the MPLUS Website.

Representative Background Reading

E. Davidov,P. Schmidt,S. Schwartz, (2008). Bringing values back in. The adequacy of the European Social Survey to measure values in 20 countries. Public Opinion Quarterly 72, 3, 420-445.

E. Davidov, B. Meuleman, J. Billiet, P. Schmidt, (2008). Values and the Support for immigration: A Cross Country Comparison, European Sociological Review, 24, 5, 583-599.

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