- Dates: 14-18 October 2013
- University: FAINOR
- Location: Vitória da Conquista, Bahia, Brazil
General material:
Contents
Monday: Introduction to network analysis and R
Further reading:
- Very short introduction to R
- The Network Takeover
-
Network Analysis: An Integrative Approach to the Structure of Psychopathology
- Comorbidity: a network perspective
Tuesday: Correlational structures
Further reading:
- qgraph: Network Visualizations of Relationships in Psychometric Data
- The pathoplasticity of dysphoric episodes: Differential impact of stressful life events on the pattern of depressive symptom inter-correlations.
Wednesday: Network descriptives
Further reading:
- Borsboom et al: The small world of psychopathology
- Opsahl et al: Node centrality in weighted networks: Generalizing degree and shortest paths
- Watts & Strogatz: Collective dynamics of ‘small-world’networks
Thursday: Causal networks
Further reading:
- Lecture notes 1: d-separation
- Lecture notes 2: Conditional Independence
- Lecture notes 3: Causal network discovery
- Cosma Shalizi: Discovering Causal Structure from Observations
- Judea Pearl: Causality
- Causal Inference Using Graphical Models with the R Package pcalg
- bnlearn website
Friday: State of the art network analysis
- Lecture slides
- Rising fit function (available on request)
Further reading:
- Bringmann et al.: A Network Approach to Psychopathology: New Insights into Clinical Longitudinal Data
- Abegaz & Wit: Sparse time series chain graphical models for reconstructing genetic networks.
- LVNA manuscript available on request
- eLasso manuscript available on request