Chapter 6 Can Graphical Causal Inference Be Extended to Nonlinear Settings? An Assessment of Conditional Independence Tests

Graphical models are a powerful tool for causal model specification. Besides al-lowing for a hierarchical representation of variable interactions, they do not require any a priori specification of the functional dependence between variables. The con-struction of such graphs hence often relies on the mere testing of whether or no