Inference from randomized (factorial) experiments

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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.
Original languageEnglish
Pages (from-to)352-355
Number of pages4
JournalStatistical Science
Issue number3
Early online date1 Sept 2017
Publication statusPublished - 2017


  • Factorial design
  • Marginality
  • Randomization
  • Unit-treatment additivity


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