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...
| Publicado en: | American Statistician Vol. 60; no. 4; pp. 328 - 332 |
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| Autores principales: | , |
| Formato: | Artículo |
| Publicado: |
American Statistical Association
November 2006
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| Acceso en línea: | Ver este registro en EBSCOhost |
| Sumario: | 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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