Introduction to Structural Equation Modeling (SEM)

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. In the first part we deal with building scales by employing confirmatory factor analysis, simultaneous factor analysis, bifactor models, multiple group factor analysis and higher order factor analysis as well as measurement invariance over groups and countries. When discussing full structural equation modeling, we will treat formative and reflective indicators, mediation, indirect effects, moderation and multiple group structural equation modeling. A further important aim is to familiarize 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 strongly encouraged to bring their own data, prepare in advance the raw data or correlations and standard deviations according to the specifications necessary for AMOS or R-lavaan and apply the new procedures besides the prepared examples of the instructors in the practical sessions. Everyone will be able to receive consultation and have the opportunity to present own first results on the last day to receive feedback and recommendations for further analyses. Workshop design A combination of either live lectures or recorded video lectures, theoretical exercises as well as applied exercises with the program Amos, group work where applicable, and individual or group work on own models with consultation and a presentation on the last day of the course. Deatiled lecture plan (daily schedule) Day 1. Basic ideas of measurement models Day 2. Confirmatory factor analysis (CFA) Day 3. Variants of Confirmatory Factor Models(Bifactor, MTMM, Higher Order), Multiple group confirmatory factor analysis (MGCFA) and introduction to Structural Equation Modeling (SEM) Day 4. SEM Day 5. Presentations of participants and summary, open questions See course outline online for details. Prerequisites Some experience with regression analysis techniques is required. Basic knowledge of factor analysis is recommended. Participants who bring their own data will most profit from the course.

Course leader

Eldad Davidov is a Professor of sociology at the Universities of Cologne, Germany and Zurich, Switzerland. Peter Schmidt is a Professor emeritus of social science methodology at the University of Giessen, Germany.

Target group

graduate students, doctoral researchers, early career researchers, experienced researchers