Causal Transportability of Experiments on Controllable Subsets of Variables: z-Transportability

by   Sanghack Lee, et al.

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 correct 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.


page 1

page 2

page 3

page 4


Identifiability and Transportability in Dynamic Causal Networks

In this paper we propose a causal analog to the purely observational Dyn...

Causal Inference by Surrogate Experiments: z-Identifiability

We address the problem of estimating the effect of intervening on a set ...

Selecting Treatment Effects Models for Domain Adaptation Using Causal Knowledge

Selecting causal inference models for estimating individualized treatmen...

Recommendation Chart of Domains for Cross-Domain Sentiment Analysis:Findings of A 20 Domain Study

Cross-domain sentiment analysis (CDSA) helps to address the problem of d...

Transporting Causal Mechanisms for Unsupervised Domain Adaptation

Existing Unsupervised Domain Adaptation (UDA) literature adopts the cova...

The Role of Embedding Complexity in Domain-invariant Representations

Unsupervised domain adaptation aims to generalize the hypothesis trained...

Learning Predictive Models That Transport

Classical supervised learning produces unreliable models when training a...