In this course, we learn different network analytical techiniques that can be applied to psychological research.
Special attention is given to the link between research question, data structure, analysis pipeline, and inference.
At the end of the course we are equipped with a ‘network analytical toolbox’, consisting of both
practical knowledge (‘how to’) as well as critical questions and reflections on the use of network analysis in
general (‘why’) and the link between research question and analysis in particular.
Topics cover both theoretical and practical aspects of network analysis including:
- Theoretical foundation of network analysis
- R packages for network modeling
- Causal network models and Pairwise Markov Random Fields (PMRF)
- Network estimation from time series data
- Simulating network dynamics and interventions
| Files/Folders | Description |
|---|---|
| Lectures | lecture slides (.pdf files) |
| Assignment | Three assignment folders; each contains a .Rmd file rendering a .pdf file |
| FinalProject | A group project and an individual report; check the README of each project for further information |
| Textbook | Network Analysis book used for this course |