Bayesian Networks are probabilistic graphical models that represent conditional
independence relationships among variables as a directed acyclic graph (DAG), where …

Research in cultural psychology over the last three decades has revealed the profound
influence of culture on cognitive, emotional, and motivational processes shaping individuals …

In recent years, network approaches to psychopathology have sparked much debate and
have had a significant impact on how mental disorders are perceived in the field of clinical …

Statistical network models describing multivariate dependency structures in psychological
data have gained increasing popularity. Such comparably novel statistical techniques …

The goal of person-centered methods is to identify subpopulations of individuals based on
within-group similarity of data relative to between-group variability. In this article, we provide …

Behavioral researchers increasingly recognize the need for more diverse samples that
capture the breadth of human experience. Current attempts to establish generalizability …

Significantly revised, the fifth edition of the most complete, accessible text now covers all
three approaches to structural equation modeling (SEM)--covariance-based SEM …

The global rollout of COVID-19 vaccines faces a significant barrier in the form of vaccine
hesitancy. This study adopts a dynamic and network perspective to explore the determinants …

The components model of addiction posits that all addictions share six components, namely
salience, tolerance, mood modification, relapse, withdrawal, and conflict. This highly …

This commentary reflects on the articles included in the Psychometrika Special Issue on
Network Psychometrics in Action. The contributions to the special issue are related to …