Course as part of the modul 'Introduction to Structural Equation Modeling and Generalized Linear Mixed Models in R'

Additional module information: <a href='https://www.bcp.fu-berlin.de/studium-lehre/studiengaenge/biologie/master_biodiv/Modulbeschreibungen_SPO_2018/Modulbeschreibungen_-Lehrveranstaltungsvarianten_MSc_BioDiv/Varianten_MSc_BioDiv/Introduction-to-Structural-Equation-Modeling_May-Buzdhygan.pdf'>Introduction to Structrual Equation Modeling</b></a> Schließen

Inhalte:
Vorlesung:
During the seminars, the topics covered in the lectures are deepened and discussed.

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

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