Causal model

A causal model is an abstract model that describes the causal mechanisms of a system. The model must express more than correlation because correlation does not imply causation.

Judea Pearl defines a causal model as an ordered triple $\langle U, V, E\rangle$, where U is a set of exogenous variables whose values are determined by factors outside the model; V is a set of endogenous variables whose values are determined by factors within the model; and E is a set of structural equations that express the value of each endogenous variable as a function of the values of the other variables in U and V.

Further reading

• Greenland, S.; Brumback, B. (2002). "An overview of relations among causal modelling methods". International Journal of Epidemiology 31 (5): 1030–1037. doi:10.1093/ije/31.5.1030. PMID 12435780. 

See also

• Causal diagram – representing causal relations with diagrams
• Causal network – a Bayesian network with an explicit requirement that the relationships be causal
• Structural equation modeling – a statistical technique for testing and estimating causal relations