This chapter applies the ideas about intervention and invariance developed in previous chapters to so-called causal models of the sort used in the social, behavioral, and biomedical sciences. Both regression models and structural equation models are explored and a modularity condition is defended in connection with the latter. Connections with the Causal Markov condition are also briefly discussed.
Keywords: causal models,, regression,, structural equations,, modularity,, Causal Markov condition,