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Arguments for Randomizing

Published online by Cambridge University Press:  28 February 2022

Patrick Suppes*
Affiliation:
Stanford University

Extract

I have organized my remarks about randomizing under four headings: computation, communication, causal Inference, and complexity. It Is hard to think of a wore controversial subject than that of randomization. My remarks are simpler and more extreme than they ought to be. I have put them in a rather bald and definite way in order to draw the lines more sharply and to make my message as clear as possible. I do not doubt that under extended debate it would be necessary to qualify some of the things I have to say, but I would insist on the point that I would be offering qualifications, not retractions.

It is often said by pure Bayesians that once the likelihood function is available knowledge of any randomization scheme used is superfluous Information. It seems to me that this argument misses an Important point which I want to illustrate by a simple artificial example.

Type
Part XI. Randomization in Statistical Inference and Experimental Design
Copyright
Copyright © 1983 Philosophy of Science Association

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References

Basu, D. (1980). “Randomization Analysis of Experimental Data: the Fisher Randomization Test.” Journal of the American Statistical Association 75: 575-595.CrossRefGoogle Scholar
Suppes, Patrick. (1970). A Probabilistic Theory of Causality. Amsterdam: North-Holland.Google Scholar
Suppes, Patrick.; Macken, E.; and Zanotti, M. (1978). “The Role of Global Psychological Models in Instructional Technology.” In Advances in Instructional Psychology. Volume 1. Edited by Glaser, R.. Hillsdale, N.J.: Erlbaum. Pages 229-259.Google Scholar