1955
DOI: 10.1080/01621459.1955.10501979
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The Randomization Theory of Experimental Inference*

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Cited by 118 publications
(81 citation statements)
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(25 reference statements)
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“…Therefore, randomisation tests were designed (Kempthorne 1955, Manly 1997. These tests are based on the calculation of the distance between the data distribution and a complete random distribution.…”
Section: Methodsmentioning
confidence: 99%
“…Therefore, randomisation tests were designed (Kempthorne 1955, Manly 1997. These tests are based on the calculation of the distance between the data distribution and a complete random distribution.…”
Section: Methodsmentioning
confidence: 99%
“…In both cases these methods allow the researcher to construct valid confidence intervals. This chapter draws from a variety of literatures, including the statistical literature on the analysis and design of experiments, e.g., Wu and Hamada (2009), Cox and Reid (2000), Altman (1991), Cook and DeMets (2008), Kempthorne (1952Kempthorne ( , 1955, Cochran and Cox (1957), Davies (1954), and Hinkelman and Kempthorne (2005Kempthorne ( , 2008. We also draw on the literature on causal inference, both in experimental and observational settings, Rosenbaum (1995Rosenbaum ( , 2002Rosenbaum ( , 2009), Rubin (2006), Cox (1992), Morgan and Winship (2007), Morton Williams (2010) and Lee (2005), and Imbens and Rubin (2015).…”
Section: Introductionmentioning
confidence: 99%
“…This notation became standard for describing possible outcomes of randomized experiments (e.g., Pitman, 1937, Welch, 1937, McCarthy, 1939, Anscombe, 1948, Kempthorne, 1952, 1955, Brillinger, Jones and Tukey, 1978, and dozens of other places, often assuming additivity as in Cox, 1956, and sometimes being used quite informally as in Freedman, Pisani and Purves, 1978, pages 456-458'). An elaboration with "technical errors" appears in Neyman's (1935) Neyman has always deprecated the statistical works which he produced in Bydogszcz [which is where Neyman (1923) was done], saying that if there is any merit in them, it is not in the few formulas giving various mathematical expectations but in the construction of a probabilistic model of agricultural trials which, at that time, was a novelty.…”
Section: On Neyman's Use Of Potential Yields To Define Causal Effectsmentioning
confidence: 99%