Teaching

Exploratory Graph Analysis (EGA)

• Introduction to networks
• Graphical least absolute shrinkage and selection operator (GLASSO)
• Extended Bayesian information criterion (EBIC) for model selection
• Community detection: Walktrap and Louvain algorithms
• Consensus clustering
• Unidimensionality
• Entropy and Total Entropy Fit Index (TEFI)
• EGA with TEFI community selection

EGA Robustness

• Measurement concepts
• Redundancy and unique variable analysis (UVA)
• Bootstrap EGA
• Item and dimension stability
• Network loadings
• Metric measurement invariance
• Hierarchical EGA

Dynamic EGA

• Generalized Local Linear Approximation
• Dynamic EGA
• Normalized Mutual Information
• Jensen-Shannon Distance
• Hierarchical Clustering
• Information Theory Clustering