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Channeling Fisher: Randomization Tests and the Statistical Insignificance of Seemingly Significant Experimental Results

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  • Alwyn Young

Abstract

I follow R. A. Fisher'sThe Design of Experiments (1935), using randomization statistical inference to test the null hypothesis of no treatment effects in a comprehensive sample of 53 experimental papers drawn from the journals of the American Economic Association. In the average paper, randomization tests of the significance of individual treatment effects find 13% to 22% fewer significant results than are found using authors’ methods. In joint tests of multiple treatment effects appearing together in tables, randomization tests yield 33% to 49% fewer statistically significant results than conventional tests. Bootstrap and jackknife methods support and confirm the randomization results.

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  • Alwyn Young, 2019. "Channeling Fisher: Randomization Tests and the Statistical Insignificance of Seemingly Significant Experimental Results," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 134(2), pages 557-598.
    • Handle: RePEc:oup:qjecon:v:134:y:2019:i:2:p:557-598.
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    File URL: http://hdl.handle.net/10.1093/qje/qjy029
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