constraint-based
Definition
Constraint-based refers to a class of causal discovery methods that utilize patterns of statistical (in)dependence estimated from observational data to infer causal structures. These methods can be applied to both acyclic and cyclic causal models. Constraint-based cyclic causal discovery methods are particularly valuable for psychological research because they can discover feedback loops and reciprocal relationships characteristic of psychopathology using only a single observational dataset.
Sources: Park et al. (2024)
Related Terms
Applications
Constraint-based and Cyclic Causal Models
Constraint-based cyclic causal discovery methods are specifically designed to discover feedback loops and reciprocal relationships between variables in psychological phenomena such as psychopathology.
Sources: Park et al. (2024)
Constraint-based and Observational Data
Constraint-based methods have the practical advantage of being applicable to a single observational dataset, making them more feasible for psychological research. By analyzing patterns of statistical dependence and independence in observational data, constraint-based methods can infer causal structures.
Sources: Park et al. (2024)
