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August 2017 Inference from Randomized (Factorial) Experiments
R. A. Bailey
Statist. Sci. 32(3): 352-355 (August 2017). DOI: 10.1214/16-STS600


This is a contribution to the discussion of the interesting paper by Ding [Statist. Sci. 32 (2017) 331–345], which contrasts approaches attributed to Neyman and Fisher. I believe that Fisher’s usual assumption was unit-treatment additivity, rather than the “sharp null hypothesis” attributed to him. Fisher also developed the notion of interaction in factorial experiments. His explanation leads directly to the concept of marginality, which is essential for the interpretation of data from any factorial experiment.


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R. A. Bailey. "Inference from Randomized (Factorial) Experiments." Statist. Sci. 32 (3) 352 - 355, August 2017.


Published: August 2017
First available in Project Euclid: 1 September 2017

zbMATH: 06870248
MathSciNet: MR3695998
Digital Object Identifier: 10.1214/16-STS600

Keywords: factorial design , marginality , randomisation , Unit-treatment additivity

Rights: Copyright © 2017 Institute of Mathematical Statistics

Vol.32 • No. 3 • August 2017
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