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The Difference Between “Significant” and “Not Significant” is not Itself Statistically Significant.

One problem with declarations of statistical significance or nonsignificance is that changes in statistical significance are often not themselves statistically significant. Not only is any particular threshold arbitrary, but even large changes in significance levels can correspond to small, nonsign...

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Published in:American Statistician Vol. 60; no. 4; pp. 328 - 332
Main Authors: Gelman, Andrew, Stern, Hal
Format: Article
Published: American Statistical Association November 2006
Online Access:View this record in EBSCOhost
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      dt: November 2006
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        atl: The Difference Between “Significant” and “Not Significant” is not Itself Statistically Significant.
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          Gelman, Andrew
          Stern, Hal
      su: Statistical significance
      sug:
        subj: Statistical significance
      ab: One problem with declarations of statistical significance or nonsignificance is that changes in statistical significance are often not themselves statistically significant. Not only is any particular threshold arbitrary, but even large changes in significance levels can correspond to small, nonsignificant changes in the underlying quantities. The writers present theoretical and applied examples to illustrate this error of interpretation, stressing that students and practitioners must be made more aware of this ubiquitous statistical error.
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    language: English
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