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Statistical significance and scientific misconduct: improving the style of the published research paper

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  • Stephen T. Ziliak

Abstract

A science, business, or law that is basing its validity on the level of p -values, t statistics and other tests of statistical significance is looking less and less relevant and more and more unethical. Today’s economist uses a lot of wit putting a clever index of opportunity cost into his models; but then, like the amnesiac, he fails to see opportunity cost in statistical estimates he makes of those same models. Medicine, psychology, pharmacology and other fields are similarly damaged by this fundamental error of science, keeping bad treatments on the market and good ones out. A few small changes to the style of the published research paper using statistical methods can bring large beneficial effects to more than academic research papers. It is suggested that misuse of statistical significance be added to the definition of scientific misconduct currently enforced by the NIH, NSF, Office of Research Integrity and others.

Suggested Citation

  • Stephen T. Ziliak, 2016. "Statistical significance and scientific misconduct: improving the style of the published research paper," Review of Social Economy, Taylor & Francis Journals, vol. 74(1), pages 83-97, March.
    • Handle: RePEc:taf:rsocec:v:74:y:2016:i:1:p:83-97
    DOI: 10.1080/00346764.2016.1150730
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    Cited by:

    1. Jens Rommel & Meike Weltin, 2021. "Is There a Cult of Statistical Significance in Agricultural Economics?," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 43(3), pages 1176-1191, September.
    2. Hirschauer Norbert & Grüner Sven & Mußhoff Oliver & Becker Claudia, 2019. "Twenty Steps Towards an Adequate Inferential Interpretation of p-Values in Econometrics," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 239(4), pages 703-721, August.

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