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Randomization and the Design of Experiments

Published online by Cambridge University Press:  01 April 2022

Peter Urbach*
Affiliation:
Department of Philosophy, Logic and Scientific Method, London School of Economics

Abstract

In clinical and agricultural trials, there is the danger that an experimental outcome appears to arise from the causal process or treatment one is interested in when, in reality, it was produced by some extraneous variation in the experimental conditions. The remedy prescribed by classical statisticians involves the procedure of randomization, whose effectiveness and appropriateness is criticized. An alternative, Bayesian analysis of experimental design, is shown, on the other hand, to provide a coherent and intuitively satisfactory solution to the problem.

Type
Research Article
Copyright
Copyright © 1985 by the Philosophy of Science Association

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Footnotes

I wish to thank Lucien Foldes, Steve Gould, Colin Howson, and especially Jon Dorling for their many helpful criticisms and suggestions for the improvement of earlier versions of this paper.

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