Networks in psychology: More than a pretty picture?
In this project, I provide different perspectives on networks in psychology. In contrast to social networks, the connections in psychological networks are often not given. Instead, these links or edges have to be inferred from some kind of a (dynamic) model, such as the vector autoregressive model. Besides pretty pictures, the network approach provides a new toolbox of analyses. Centrality analyses, for example, give information about how important a variable is in a network. Recently the interest in networks in psychology and especially psychopathology has grown tremendously. However, with increasing popularity, also the criticism grows. For example, how well can the raw coefficients of a multilevel VAR, and thus the edges of the network, be interpreted? Furthermore, the exact meaning and significance of the centrality measures in networks remains unclear. I will study these and other challenges to the network approach, ultimately answering the question: Networks in psychology - more than a pretty picture?
Researchers and partnersdr. L.F. (Laura) Bringmann, Psychometrics and Statistics
University of Groningen, outside of Behavioural and Socials Sciences
- Markus Eronen Faculty of philosophy
- Bringmann, L.F. (2016). Dynamical networks in psychology: More than a pretty picture? (Doctoral dissertation). DOI: 10.13140/RG.2.2.28223.10404
University's focus areas
- Healthy Ageing
- Sustainable Society
|Last modified:||29 March 2021 10.18 a.m.|