23307c PC-based Seminar

WiSe 21/22: S-PCIntroduction to Structural Equation Modeling and Generalized Linear Mixed Models in R

Oksana Buzhdygan, Felix May

Information for students

Zusätzliche Modulinfos: Introduction to Structrual Equation Modeling close

Additional information / Pre-requisites

Prior knowledge in R and linear models including regression, ANOVA and ANCOVA is required. Please use the computer not a tablet because R is difficult to install on a tablet. The lecture will be made available on the day before. Students are required to go through the lecture until the next live meeting of the module. close


Seminar am PC: In the seminars on the PC, students practically apply the topics and methods, learned during the lectures and seminars. Using a number of worked examples from the published ecological literature, students develop, evaluate, modify and solve the SEM models and mixed effect models using the R software under supervision and later independently. Students practice the selection of data analysis strategies for different datasets (e.g., random vs. not random samples). With SEM models students analyse cause-effect connections, test direct and indirect effects and interpret the mechanisms in the study systems. With mixed effect models and piecewise SEM students analyse grouped and nested data and interpret the results in the ecologically meaningful contexts. Qualifikationsziele:
In this module the students acquire the following knowledge and skills:
  • Gain basic knowledge of structural equation modeling (SEM) framework
  • Learn how to develop, evaluate, refine, solve, and interpret structural equation models
  • Master basic skills to analyze data with SEM in the software R
  • Gain knowledge of nested data and mixed effect models
  • Gain basic knowledge of piecewise SEM and how it differs from the classical SEM
  • Master basic skills to analyse nested data with the mixed effect models and piecewise SEM using the software R
  • Gain basic understanding of causal relations, bottom-up and top-down control, and direct and indirect effects in ecological and biological systems (e.g., communities, food webs, ecosystems)
  • Independently apply SEM and mixed effect models
  • Present statistical methods and results in oral and written form to a specialist audience.


Suggested reading

Grace (2006) Structural Equation Modeling and Natural Systems. Cambridge Univ. Press.
Zuur et al. (2009) Mixed Effects Models and Extensions in Ecology in R. Springer
Crawley, M.J. (2012). The R book. John Wiley & Sons. close

Subjects A - Z