On Thursday 27th we will host the satellite session “Understanding Psychological Phenomena as Complex Systems” at the Conference on Complex Systems 2018, focusing on advancing the theoretical foundations of the network approach to psychopathology. Abstracts and slides are available on the satellite website!
Estimated network and predictability measures (blue pie charts) for the data in McNally et al. (2014)
Predictability of nodes in network models offer an additional perspective on symptom networks, which relates to the practical relevance of edges, the selection of optimal treatment and the degree to which (parts of) the network are self-determined or determined by factors outside of the networks.
For a brief introduction and fully reproducible example of how to compute and visualize predictability in R, have a look at this blog post. The preprint of the paper can be found here.
How to interpret interactions between categorical variables in a mixed graphical model? How can we recover the direction of interactions between continuous variables? Have a look at this blog post to find out!
In many situations one is interested in constructing a network from different types of variables, for example age (continuous), type of medication (categorical) and number of diagnoses (count). In this blog post on R-bloggers.com, I describe how to construct such a network using the R-package “mgm”: