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Optimal Bayesian Randomization
Author(s) -
Berry Scott M.,
Kadane Joseph B.
Publication year - 1997
Publication title -
journal of the royal statistical society: series b (statistical methodology)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.523
H-Index - 137
eISSN - 1467-9868
pISSN - 1369-7412
DOI - 10.1111/1467-9868.00098
Subject(s) - randomization , restricted randomization , bayesian probability , computer science , econometrics , machine learning , artificial intelligence , mathematics , clinical trial , medicine , pathology
Randomization is a puzzle for Bayesians. The intuitive need for randomization is clear, but there is a standard result that Bayesians need not randomize. In this paper we propose a model in which randomization is a strictly optimal procedure. The most important aspect of our model is that there are several parties who make different decisions and observe different data. The result also sheds light on the ethical considerations involving randomization in a clinical trial.