# Causal Calculus in the Presence of Cycles, Latent Confounders and Selection Bias

@article{Forr2019CausalCI, title={Causal Calculus in the Presence of Cycles, Latent Confounders and Selection Bias}, author={Patrick Forr{\'e} and Joris M. Mooij}, journal={ArXiv}, year={2019}, volume={abs/1901.00433} }

We prove the main rules of causal calculus (also called do-calculus) for i/o structural causal models (ioSCMs), a generalization of a recently proposed general class of non-/linear structural causal models that allow for cycles, latent confounders and arbitrary probability distributions. We also generalize adjustment criteria and formulas from the acyclic setting to the general one (i.e. ioSCMs). Such criteria then allow to estimate (conditional) causal effects from observational data that was… Expand

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