Dr. Susanne Elpers
Konzeptionelle Nachwuchsförderung Schwerpunkt Postdocs und Gleichstellung

+49 (0)441-798 2939

Dr. Julia Anna Matz
Konzeptionelle Nachwuchsförderung Schwerpunkt Promovierende und Internationales

+49 (0)441-798 4286


Susanne Bartel

Tel.: +49 (0)441-798 4628


Workshop: Introduction to Structural Equation Modeling with R (Dr. M. Murat Ardag)

3GO + Graduiertenakademie

In words of Yves Rosseel, the developer of the R package lavaan (latent variable analysis), “In the social sciences, structural equation modeling (SEM) is often considered to be the mother of all statistical modeling. It includes univariate and multivariate regression models, generalized linear mixed models, factor analysis, path analysis, item response theory, latent class analysis, and much more. SEM can also handle missing data, non-normal data, categorical data, multilevel data, longitudinal data, (in)equality constraints, and on a good day, SEM makes you a fresh cup of tea.” Put simply: there is almost nothing you cannot do with SEM.

This workshop is designed to be a practitioner’s guide. After going over the fundamentals of the outlined topics below, we will get to focus on their application in the R environment. There is almost no math involved; however we will get to understand the conceptual reasoning over the math going on in the background.

Target Audience are the graduate students at the following departments: Social Sciences, Educational Sciences, Business Administration & Economics, Psychology, Biology.

Please note that a general familiarity with R is a prerequisite for attending the workshop. I can provide prep material for R before the workshop.

Day 1

Morning session(s)

  1. Recap: Simple & multiple linear regression

  2. Path analysis: going beyond the regression framework to test hypothesized mechanisms

  3. Recap: Principal component analysis vs. exploratory factor analysis

  4. Applications in the R environment

Afternoon session(s)

  1. Confirmatory factor analysis: are the operationalizations valid and reliable?

  2. Basics of item response theory: eliminating the bad items in a measurement model and seeing the general psychometric qualities of the scale with graded response model

  3. Structural equation modeling: finding the associations between the operationalized constructs

  4. Applications in the R environment

Day 2

Morning session(s)

  1. Multiple group models: exact vs. approximate measurement invariance across groups, SEM trees & forests

  2. Non-recursive structural equation models for (pseudo-)causal relationships: testing causality with cross-sectional survey data

  3. Application of structural equation models in experiments: testing causality with multi-group models

  4. Applications in the R environment

Afternoon session(s)

  1. Multilevel structural equation models: dealing with nested data structures 

  2. Including survey-weights in structural equation models: when to weight the indicators?

  3. Applications in the R environment

Dieser Workshop wird organisiert von der 3GO.
Für weitere Informationen zu diesem Workshop richten Sie sich bitte an:

Geschäftsführung und Koordination:
Rea Kodalle
S 1-130
+49 (0)441 798-5481

Koordination der Programme für Studierende/Evaluation:
Robert Mitschke

Die Anmeldung bitte über Stud.IP vornehmen.


19. Februar 2020, 09:00 – Enddatum: 20. Februar 2020, 16:00

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