Causal transportability of experiments on controllable subsets of variables: Z-transportability

Sanghack Lee, Vasant Honavar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

We introduce z-transportability, the problem of estimating the causal effect of a set of variables X on another set of variables Y in a target domain from experiments on any subset of controllable variables Z where Z is an arbitrary subset of observable variables V in a source domain. z-Transportability generalizes z-identifiability, the problem of estimating in a given domain the causal effect of X on Y from surrogate experiments on a set of variables Z such that Z is disjoint from X. z-Transportability also generalizes transportability which requires that the causal effect of X on Y in the target domain be estimable from experiments on any subset of all observable variables in the source domain. We first generalize z-identifiability to allow cases where Z is not necessarily disjoint from X. Then, we establish a necessary and sufficient condition for z-transportability in terms of generalized z-identifiability and transportability. We provide a sound and complete algorithm that determines whether a causal effect is z-transportable; and if it is, produces a transport formula, that is, a recipe for estimating the causal effect of X on Y in the target domain using information elicited from the results of experimental manipulations of Z in the source domain and observational data from the target domain. Our results also show that do-calculus is complete for z-transportability.

Original languageEnglish (US)
Title of host publicationUncertainty in Artificial Intelligence - Proceedings of the 29th Conference, UAI 2013
Pages361-370
Number of pages10
StatePublished - 2013
Event29th Conference on Uncertainty in Artificial Intelligence, UAI 2013 - Bellevue, WA, United States
Duration: Jul 11 2013Jul 15 2013

Other

Other29th Conference on Uncertainty in Artificial Intelligence, UAI 2013
CountryUnited States
CityBellevue, WA
Period7/11/137/15/13

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

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    Lee, S., & Honavar, V. (2013). Causal transportability of experiments on controllable subsets of variables: Z-transportability. In Uncertainty in Artificial Intelligence - Proceedings of the 29th Conference, UAI 2013 (pp. 361-370)