External Validity: From Do-calculus to Transportability Across Populations

Abstract

The generalizability of empirical findings to new environments settings or populations, often called "external validity" is essential in most scientific explorations. This paper treats a particular problem of generalizability, called "transportability" defined as a license to transfer causal effects learned in experimental studies to a new population in which only observational studies can be conducted. We introduce a formal representation called "selection diagrams" for expressing knowledge about differences and commonalities between populations of interest and, using this representation, we reduce questions of transportability to symbolic derivations in the do-calculus. This reduction yields graph-based procedures for deciding whether causal effects in the target population can be inferred from experimental findings in the study population. When the answer is affirmative, the procedures identify what experimental and observational findings need be obtained from the two populations, and how they can be combined to ensure bias-free transport.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 2012
Accession Number
ADA563868

Entities

People

  • Elias Bareinboim
  • Judea Pearl

Organizations

  • University of California, Los Angeles

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Age Distribution
  • Artificial Intelligence
  • Behavioral Sciences
  • Calculus
  • Commonality
  • Computer Science
  • Computers
  • Educational Psychology
  • Environment
  • Formal Languages
  • Language
  • Probability
  • Probability Distributions
  • Psychology
  • Reasoning
  • Statistics
  • Transport Ships

Readers

  • Regression Analysis.
  • Software Engineering.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Neural Networks