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Statistics, Politics and Policy

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Substantive Importance and the Veil of Statistical Significance

Kelly McCaskey
  • Corresponding author
  • Department of Political Science, Texas A&M University, 2010 Allen Building, College Station, TX 77843, USA
  • Email:
/ Carlisle Rainey
  • Department of Political Science, Texas A&M University, 2010 Allen Building, College Station, TX 77843, USA
Published Online: 2015-11-06 | DOI: https://doi.org/10.1515/spp-2015-0001


Political science is gradually moving away from an exclusive focus on statistical significance and toward an emphasis on the magnitude and importance of effects. While we welcome this change, we argue that the current practice of “magnitude-and-significance,” in which researchers only interpret the magnitude of a statistically significant point estimate, barely improves the much-maligned “sign-and-significance” approach, in which researchers focus only on the statistical significance of an estimate. This exclusive focus on the point estimate hides the uncertainty behind a veil of statistical significance. Instead, we encourage researchers to explicitly account for uncertainty by interpreting the range of values contained in the confidence interval. Especially when making judgments about the importance of estimated effects, we advise researchers to make empirical claims if and only if those claims hold for the entire confidence interval.


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About the article

Corresponding author: Kelly McCaskey, PhD Student, Department of Political Science, Texas A&M University, 2010 Allen Building, College Station, TX 77843, USA, e-mail:

Published Online: 2015-11-06

Published in Print: 2015-12-01

Citation Information: Statistics, Politics and Policy, ISSN (Online) 2151-7509, ISSN (Print) 2194-6299, DOI: https://doi.org/10.1515/spp-2015-0001. Export Citation

Comments (1)

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  • Confidence intervals that don't cover the null value suffer from problems just as significance values do. See my paper Shaffer, J.P. (2004), Confidence intervals on subsets may be misleading, Journal of Modern Applied Statistical Methods, 3, 261-270, plus the errata (2006), 5, 281.

    posted by: Juliet Shaffer on 2015-12-05 06:53 PM (Europe/Berlin)