We provide a formal definition of the notion of transportability, or external validity, as a license to transfer causal information from experimental studies to a different population in which only observational studies can be conducted. We introduce a formal representation called selection diagrams for expressing differences and commonalities between populations of interest and, using this representation, we derive procedures for deciding whether causal effects in the target population can be inferred from experimental findings in a different population. When the answer is affirmative, the procedures identify the set of experimental and observational studies that need be conducted to license the transport.
Keywords: Counterfactual; Directed Acyclic Graphs; Transportability
Biography: Judea Pearl is Professor of Computer Science and Statistics and Director of the Cognitive Systems Laboratory at the University of California, in Los Angeles. He has contributed to the field of causal inference with unifying theory for counterfactuals, structural equations, and directed acyclic graphs. His book Causality was first published in 2000, and has already become a reference work in the field.