Transportability of Causal Effects: Completeness Results

Abstract

The study of transportability aims to identify conditions under which causal information learned from experiments can be reused in a different environment where only passive observations can be collected. The theory introduced in [Pearl and Bareinboim, 2011] (henceforth [PB, 2011]) defines formal conditions for such transfer but falls short of providing an effective procedure for deciding whether transportability is feasible for a given set of assumptions about differences between the source and target domains. This paper provides such procedure. It establishes a necessary and sufficient condition for deciding when causal effects in the target domain are estimable from both the statistical information available and the causal information transferred from the experiments. The paper further provides a complete algorithm for computing the transport formula, that is, a way of fusing experimental and observational information to synthesize an estimate of the desired causal relation.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2012
Accession Number
ADA557446

Entities

People

  • Elias Bareinboim
  • Judea Pearl

Organizations

  • University of California, Los Angeles

Tags

Communities of Interest

  • Autonomy
  • Biomedical
  • C4I

DTIC Thesaurus Topics

  • Age Distribution
  • Algorithms
  • Artificial Intelligence
  • Calculus
  • Causal Reasoning
  • Computer Science
  • Construction
  • Data Science
  • Environment
  • Experimental Design
  • New York
  • Observation
  • Probability
  • Probability Distributions
  • Reasoning
  • Statistics
  • Transport Ships

Readers

  • Distributed Systems and Data Platform Development
  • Logistics and Supply Chain Management.
  • Regression Analysis.