23307c
Seminar am PC
WiSe 22/23: S-PC Introduction to Structural Equation Modeling and Generalized Linear Mixed Models in R
Oksana Buzhdygan, Felix May
Hinweise für Studierende
Zusätzliche Modulinfos: Introduction to Structrual Equation Modeling
Schließen
Zusätzl. Angaben / Voraussetzungen
Vorkenntnisse in R und mit linearen Modellen, wie Regression, ANOVA und ANCOVA, sind notwendig. Bitte am Rechner arbeiten, auf einem Tablet lässt sich R schlecht installieren! Die Vorlesungen werden am Vortag jedes Kurstages zur Verfügung gestellt. Die Studierenden sollen sich die Vorlesungen vor dem entsprechenden Seminar anschauen. Schließen
Kommentar
Inhalte:
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:
Schließen
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.
Schließen
Literaturhinweise
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. Schließen
Zuur et al. (2009) Mixed Effects Models and Extensions in Ecology in R. Springer
Crawley, M.J. (2012). The R book. John Wiley & Sons. Schließen