statistical network model
Definition
A statistical network model is a probabilistic graphical model that uses graphs to express conditional (in)dependencies between random variables, where vertices represent variables and edges encode the statistical relationships among them. Recent advances in psychological research have demonstrated that cyclic causal discovery methods offer advantages over traditional acyclic approaches for modeling phenomena such as mental disorders, which are characterized by feedback loops and reciprocal relationships between symptoms.
Sources: Park et al. (2024)
Related Terms
Applications
Statistical Network Model and Causal Discovery
Statistical network models are frequently employed in psychological research as causal discovery tools. Constraint-based cyclic causal discovery methods represent a purpose-built alternative that can more accurately discover causal structures, particularly when feedback loops and reciprocal relationships are theoretically expected.
Sources: Park et al. (2024)
Statistical Network Model and Psychopathology
Cyclic causal models may be more appropriate for capturing the feedback loops that characterize psychological phenomena such as mental disorders.
Sources: Park et al. (2024)
