Two new papers on predictability of symptom networks

This guest post was written by Jonas Haslbeck (jonas.haslbeck@gmail.com) who is a PhD student in the Psychosystems lab at the University of Amsterdam. Symptom networks have become popular in clinical psychology because they promise to provide insights into the topology and dynamics of mental disorders. Most analyses so far focused …

Tutorial paper on new methods for estimating psychological networks

This guest post was written by Giulio Costantini (costantinigiulio@gmail.com) who recently finished his PhD at the University of Milan Bicocca. His blog describes a new tutorial paper that was just published in Personality and Individual Differences (PDF), and follows his earlier 2015 tutorial paper on estimating psychological networks. In a …

The network approach to psychopathology: pitfalls, challenges, and future directions

After Angelique Cramer and colleagues published the first paper on empirical networks for psychopathology in 2010, a few years of great enthusiasm followed, and psychological network science felt a bit like the Wild West: Everything was possible, and it was difficult to find qualified reviewers due to the novelty of …

Network replicability: a cross-cultural PTSD study across of clinical datasets

Let’s start with a teaser: This blog post is a summary of the first psychological network study ever looking at the replicability of network models in 4 datasets, with a total N of 2,782 (Preprint). The paper is fully reproducible, and includes the covariance matrices of the four datasets so …

Public time-series data of 40 outpatients (21 items, 130 measurements)

This guest post was written by Aaron Fisher (afisher@berkeley.edu) who is an Assistant Professor of Psychology and the Director of the Idiographic Dynamics Lab at the University of California, Berkeley. Aaron argues for a shift from nomothetic to idiographic research, and describes a new dataset he made publicly available for …

Six new network papers, including a review of the empirical literature

The last weeks have been pretty busy with teaching, traveling, and writing that I didn’t find the time I wanted to for blogging. To catch up, this blog post will feature several new network papers (in alphabetical order by first author). It is becoming increasingly hard to keep up with …

New paper: differential variability of variables drives network structure

In psychopathological networks, we often model ordinal items (problems or symptoms) that are not normally distributed, especially in general population samples. But if a variable shows a floor effect, meaning that the mean is close to 0, it often has a small variance, which in turn means that the variable …

R tutorial: power issues & robustness of network models

A new paper by Mohammad Afzali and colleagues was published a few days ago in the Journal of Affective Disorders, entitled “A Network Approach to the Comorbidity between Posttraumatic Stress Disorder and Major Depressive Disorder: the Role of Overlapping Symptoms”. The authors estimate the network structure of 36 symptoms in …

Dynamical systems study follows 1 psychotic patient for 1 full year

When we recently submitted a review paper on empirical network studies in psychopathology, we realized that the majority of prior papers had focused on the analyses of groups, e.g. depressed patients, psychotic patients, or people with autism. Fewer studies had looked into the question of the dynamic character of symptoms …

Expected influence: a new centrality metric by Robinaugh et al. 2016

When we estimate the centrality of nodes in networks, one metric that is commonly used is node strength centrality or degree centrality. In unweighted networks were edges are either 0 or 1, this is simply the sum of edges. Let’s create a brief example in R: we create an adjacency …