Hostname: page-component-78c5997874-g7gxr Total loading time: 0 Render date: 2024-11-18T11:19:52.307Z Has data issue: false hasContentIssue false

The Role of Randomization in Inference

Published online by Cambridge University Press:  28 February 2022

Extract

Who is there that has not longed that the power and privilege of selection among alternatives should be taken away from him in some important crisis of his life, and that his conduct should be arranged for him, either this way or that, by some divine power if it were possible, — by some patriarchal power in the absence of divinity, — or by chance even, if nothing better than chance could be found to do it? Anthony Trollope Phineas Finn Vol. II, Ch. LX.

In the design and analysis of an experiment there are several places where an element of randomization can be used: the design can be selected at random, the result can have a random element adjoined to it, or the random element already present can be used in the analysis. The first technique is much used by statisticians; for example, in making a survey of a population, Basu (1980) calls it prerandomization.

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

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Basu, D. (1975). “Statistical Information and Likelihood.” Sankhyā A 37: 1-55, with discussion 56-71.Google Scholar
Basu, D. (1980). “Randomization Analysis of Experimental Data: the Fisher Randomization Test.” Journal of American Statistical Association 75: 575-582, with discussion 582-595.CrossRefGoogle Scholar
Birnbaum, A. (1962). “On the Foundations of Statistical Inference.” Journal of American Statistical Association 57: 269-306, with discussion 307-326.CrossRefGoogle Scholar
Birnbaum, A. (1972). “More on Concepts of Statistical Evidence.” Journal of American Statistical Association 67: 858-861.CrossRefGoogle Scholar
Cohen, M.R. and Nagel, E. (1931). An Introduction to Logic and Scientific Method. New York: Harcourt Brace.Google Scholar
Cox, D.R. (1980). “Local Ancillarity.” Biometrika 67: 279-286.CrossRefGoogle Scholar
de Finetti, B. (1970). Teoria delle probabilità. (2 vols.) Torino: G. Einaudi. (As reprinted as Theory of Probability. (2 vols.) (trans.) de Haohi, A. and Smith, A.. London: John Wiley & Sons, 1974, 1975.Google Scholar
Lindley, D.V. and Novick, M.R. (1981). “The Role of Exchangeability in Inference.” The Annals of Statistics 9: H5-58.CrossRefGoogle Scholar
Rubin, Donald B. (1978). “Bayesian Inference for Causal Effects: The Role of Randomization.” The Annals of Statistics 6: 34-58.CrossRefGoogle Scholar
Simpson, E.H. (1951). “The Interpretation of Interaction in Contingency Tables.” Journal of Roval Statistioal Society B 13: 238-241.Google Scholar