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Open Access 01-01-2017 | COMMENTARY

Significance testing: Why does it prevail?

Author: Anders Ahlbom

Published in: European Journal of Epidemiology | Issue 1/2017

Excerpt

A report by Seliger et al. on statin use and risk of glioma prompted Greenland to write a letter-to-the-editor in which he again explains why lack of statistical significance must not be interpreted as lack of association [1, 2]. Greenland and colleagues have also stressed recently that a statistically significant association very well may be due to chance [3]. These two statements hold just the same regardless of whether the statistical significance judgment is based on if the P value is smaller than 5% or if the confidence interval excludes the no-effect value. …

Seliger C, Meier CR, Becker C, Jick SS, Bogdahn U, Hau P, et al. Statin use and risk of glioma: population-based case-control analysis. Eur J Epidemiol. 2016;31(9):947–52. doi:10.1007/s10654-016-0145-7.CrossRefPubMed

Greenland S. A serious misinterpretation of a consistent inverse association of statin use with glioma across 3 case–control studies. Eur J Epidemiol. doi:10.1007/s10654-016-0205-z.

Greenland S, Senn SJ, Rothman KJ, Carlin JB, Poole C, Goodman SN, et al. Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations. Eur J Epidemiol. 2016;31(4):337–50. doi:10.1007/s10654-016-0149-3.CrossRefPubMedPubMedCentral

Stang A, Deckert M, Poole C, Rothman KJ. Statistical inference in abstracts of major medical and epidemiology journals 1975–2014: a systematic review. Eur J Epidemiol. doi:10.1007/s10654-016-0211-1.

Title: Significance testing: Why does it prevail?
Author: Anders Ahlbom
Publication date: 01-01-2017
Publisher: Springer Netherlands
Published in: European Journal of Epidemiology / Issue 1/2017
Print ISSN: 0393-2990
Electronic ISSN: 1573-7284
DOI: https://doi.org/10.1007/s10654-016-0220-0

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