Meta-Transportability of Causal Effects: A Formal Approach

In Proceedings of the 16th International Conference on Artificial Intelligence and Statistics (AISTATS), pp. 135-143, 2013.

9 Pages Posted: 26 Oct 2013

See all articles by Elias Bareinboim

Elias Bareinboim

University of California, Los Angeles (UCLA)

Judea Pearl

University of California, Los Angeles (UCLA) - Computer Science Department

Date Written: July 22, 2013

Abstract

This paper considers the problem of transferring experimental findings learned from multiple heterogeneous domains to a different environment, in which only passive observations can be collected. Pearl and Bareinboim (2011) established a complete characterization for such transfer between two domains, a source and a target, and this paper generalizes their results to multiple heterogeneous domains. It establishes a necessary and sufficient condition for deciding when effects in the target domain are estimable from both statistical and causal information transferred from the experiments in the source domains. The paper further provides a complete algorithm for computing the transport formula, that is, a way of fusing observational and experimental information to synthesize an unbiased estimate of the desired effects.

Suggested Citation

Bareinboim, Elias and Pearl, Judea, Meta-Transportability of Causal Effects: A Formal Approach (July 22, 2013). In Proceedings of the 16th International Conference on Artificial Intelligence and Statistics (AISTATS), pp. 135-143, 2013. , Available at SSRN: https://ssrn.com/abstract=2343825

Elias Bareinboim

University of California, Los Angeles (UCLA) ( email )

405 Hilgard Avenue
Box 951361
Los Angeles, CA 90095
United States

Judea Pearl (Contact Author)

University of California, Los Angeles (UCLA) - Computer Science Department ( email )

4732 Boelter Hall
Los Angeles, CA 90095
United States

HOME PAGE: http://www.cs.ucla.edu/~judea/

Do you want regular updates from SSRN on Twitter?

Paper statistics

Downloads
20
Abstract Views
346
PlumX Metrics