Network analysis workshops

Here you find more information on our network analysis workshops. I gave these workshops either alone or together with my brilliant colleagues Marie Deserno, Jonas Dalege, Sacha Epskamp, and Maarten de Schryver.

Download all workshop materials for free

We have made all workshops materials of the latest 3-day workshop freely available. The workshop covers an R introduction, network estimation, network inference, and network accuracy for between-subjects cross-sectional networks and within-subjects time-series networks. The last update of the slides was March 2017. If you or your group / Department / University are interested in a workshop, please do not hesitate to contact me and we can get in touch about the details. I am also happy to send you anonymized versions of prior evaluations that were all very positive.

All workshop materials are freely available on the Open Science Framework; if you want, you can cite the workshop with the DOI 10.17605/OSF.IO/XCBFF. A brief overview of the workshop is available HERE

The 3-day network workshop starts with a 1-day introduction to R.

Day 2 starts with a conceptual introduction to psychopathological networks — in which we explain the main differences between the network framework and alternatives like the common cause model – and an overview of the prior literature organized into disorders (e.g., depression, PTSD, psychosis, substance abuse, etc.) and topics (e.g., centrality, comorbidity, early warning signals). The focus of the second day is on group-level networks: what is the symptom network of a group of patients with, for instance, Major Depression? Using packages such as qgraph, bootnet, and IsingFit, we use the free statistical environment R, and a free dataset on Posttraumatic Stress Disorder, to learn the basics about (1) network estimation, (2) network inference, and (3) network stability and accuracy. Network estimation is concerned with the question which types of models are appropriate for our data, such as the Ising Model for binary data or the Gaussian Graphical Model for metric data. In this section, we also discuss how to apply regularization methods to networks in order to avoid estimating false positive associations. The second topic, network inference, covers graph theoretical measures such as centrality that allow us to interpret networks. What symptoms are most connected and relevant with other symptoms in the causal web? Finally, stability and accuracy estimation allows us to gain insight into the robustness of our networks: how likely are they going to be replicated? We conclude the day with advanced methods such as the statistical comparison of networks, the modeling of networks containing different types of variables (mixed graphical models via the R-package mgm), and some considerations about causality.

The focus of the third day is on dynamic time-series models: how do symptoms impact on each other over time? After an introduction into the general modeling framework with some substantive examples of recent papers, we learn to estimate the network model – specifically, the vector auto-regressive (VAR) model – for one participant via the package graphicalVAR. We then go through the assumptions that the VAR model requires such as stationarity and equidistance of measurement points. After that, we discuss the multilevel extension of the VAR model to the case of a group of participants, using the package mlVAR, followed by a discussion of some common problems and advanced techniques. In the afternoon of the second day, we spend about 3.5 hours with R in a practical session, and workshop participants learn to apply the knowledge of day 1 and day 2 to several datasets.

Overview of previous workshops

  • 2016/05: 2-day workshop, Harvard University & McLean Hospital, Cambridge (reference) (Eiko, Marie, Sacha)
  • 2016/06: 2-day workshop, University of Washington, St Louis (reference) (Eiko, Marie, Sacha)
  • 2016/07: 1-day workshop, Ulster University, Ireland (reference) (Eiko)
  • 2016/11: 1-day workshop, University of Utrecht (reference) (Eiko, Sacha)
  • 2016/11: 1-day workshop, University of Brussels (reference) (Eiko)
  • 2017/01: 3-day workshop, University of Gent (reference) (Eiko, Maarten & Sacha)
  • 2017/02: 2-day workshop, Experimental Psychopathology meeting (reference) (Eiko & Jonas)

Summer and winter schools

Please also note that in addition to these workshops, our Psychosystems group in Amsterdam has organized network analysis summer (2016) and winter (2017) schools that were very well received (main organizers: Marie Deserno & Jonas Dalege). There will likely be future summer and winter schools — stay tuned!