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The Similarity of Causal Inference in Experimental and Non-experimental Studies

Published online by Cambridge University Press:  01 January 2022

Richard Scheines
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Abstract

For nearly as long as the word ‘correlation’ has been part of statistical parlance, students have been warned that correlation does not prove causation, and that only experimental studies, e.g., randomized clinical trials, can establish the existence of a causal relationship. Over the last few decades, somewhat of a consensus has emerged between statisticians, computer scientists, and philosophers on how to represent causal claims and connect them to probabilistic relations. One strand of this work studies the conditions under which evidence accumulated from non-experimental (observational) studies can be used to infer a causal relationship. In this paper, I compare the typical conditions required to infer that one variable is a direct cause of another in observational and experimental studies. I argue that they are essentially the same.

Type
Causality, Confirmation and Inference
Information
Philosophy of Science , Volume 72 , Issue 5: Proceedings of the 2004 Biennial Meeting of The Philosophy of Science Association. Part I: Contributed Papers , December 2005 , pp. 927 - 940
Copyright
Copyright © The Philosophy of Science Association

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