APS 2018 — the conference of the Association for Psychological Science in San Francisco, May 2018 — featured many talks on the topics complex systems, time-series models, network models, and modeling intensive longitudinal data assessed via experience sampling. I promised to collect all slides I could hunt down, and want …
This guest post was written by Tessa F. Blanken and Marie K. Deserno who are both PhD-students associated with the Psychosystems Lab at the University of Amsterdam. They secretly meet up every Friday to vividly discuss potential extensions of the network analysis toolbox. This post summarizes a new paper available …
TL;DR: This blog post summarizes and discusses Information Filtering Networks introduced in a new paper by Christensen et al. 2018, and discusses them compared to the lasso-regularized Markov Random Fields. The post ends with an R tutorial on how to estimate such networks. Markov Random Fields (MRF) have quickly become …
In a previous tutorial blog post, I summarized the bootstrapping routine developed by Sacha Epskamp and me that we recommend for testing the stability / accuracy / precision of estimated network models and parameters. This matters a great deal and should be considered a standard step in every empirical network …
This guest post was written by Tobias Spiller (tobias.r.spiller@gmail.com) who recently finished Medical School at the University of Zurich. Tobias has published a paper using network analysis with a refugee sample and currently works on several other network analytic projects. Last year, 15 articles using network analytic methods in PTSD/psychotraumatology …
Since replication, replicability, and generalizability have become such important topics in the field of network psychometrics — arguably the topic of the year 2017 — I want to highlight seven new papers that came out in the last weeks on the topic. 7 papers on replicability Fried et al. 2017 …
Lizanne Schweren, a Postdoc at the University Medical Center Groningen, and colleagues published a paper in JAMA Psychiatry this morning showing that the connectivity of depression symptoms is, in contrast to what a prior paper found, not a predictor of treatment response. This is the first non-replication in the psychopathology …
When I see limitations in published network papers that I find sufficiently relevant to address, I discuss the papers here, and try to provide ways forward. For instance, Madhoo & Levine (2016) drew inferences from visually inspecting their networks, which inspired me to write a tutorial blog post on the …
In the last months, a number of free resources for network analysis appeared online which I wanted to summarize briefly. Sacha Epskamp and Adela Isvoranu organized the 5-day Psychological Networks Amsterdam Summer, with presentations from over 10 researchers. All resources are available online. I gave several 2-day workshops this year, …
This guest post was written by Payton Jones (payton_jones@g.harvard.edu) and Haley Elliott (haleyelliott@college.harvard.edu), and is based on a recent letter in which they highlight the importance of non-symptom variables in psychological networks. Payton is a graduate student at Harvard University in the Richard J. McNally lab. His research focuses on …
