Generalizing Experimental Findings

Pearl Judea ()
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Pearl Judea: Computer Science Department, University of California, Los Angeles, Los Angeles, CA 90095-1596, USA

Journal of Causal Inference, 2015, vol. 3, issue 2, 259-266

Abstract: This note examines one of the most crucial questions in causal inference: “How generalizable are randomized clinical trials?” The question has received a formal treatment recently, using a non-parametric setting, and has led to a simple and general solution. I will describe this solution and several of its ramifications, and compare it to the way researchers have attempted to tackle the problem using the language of ignorability. We will see that ignorability-type assumptions need to be enriched with structural assumptions in order to capture the full spectrum of conditions that permit generalizations, and in order to judge their plausibility in specific applications.

Keywords: generalizability; transportability; selection bias; admissibility; ignorability (search for similar items in EconPapers)
Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:bpj:causin:v:3:y:2015:i:2:p:259-266:n:10

DOI: 10.1515/jci-2015-0025

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