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Scandinavian Journal of Pain

Official Journal of the Scandinavian Association for the Study of Pain

Editor-in-Chief: Breivik, Harald

CiteScore 2017: 0.84

SCImago Journal Rank (SJR) 2017: 0.401
Source Normalized Impact per Paper (SNIP) 2017: 0.452

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Volume 4, Issue 4


Significance tests in clinical research—Challenges and pitfalls

Eva Skovlund
  • Corresponding author
  • School of Pharmacy, University of Oslo, Oslo, Norway
  • Norwegian Institute of Public Health, Oslo, Norway
  • Email
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
Published Online: 2013-10-01 | DOI: https://doi.org/10.1016/j.sjpain.2013.07.023



Statistical analyses are used to help understand the practical significance of the findings in a clinical study. Many clinical researchers appear to have limited knowledge onhowto perform appropriate statistical analysis as well as understanding what the results in fact mean.


This focal review is based on long experience in supervising clinicians on statistical analysis and advising editors of scientific journals on the quality of statistical analysis applied in scientific reports evaluated for publication.


Basic facts on elementary statistical analyses are presented, and common misunderstandings are elucidated. Efficacy estimates, the effect of sample size, and confidence intervals for effect estimates are reviewed, and the difference between statistical significance and clinical relevance is highlighted. The weaknesses of p-values and misunderstandings in how to interpret them are illustrated with practical examples.

Conclusions and recommendations

Some very important questions need to be answered before initiating a clinical trial. What is the research question? To which patients should the result be generalised? Is the number of patients sufficient to draw a valid conclusion? When data are analysed the number of (preplanned) significance tests should be kept small and post hoc analyses should be avoided. It should also be remembered that the clinical relevance of a finding cannot be assessed by the p-value. Thus effect estimates and corresponding 95% confidence intervals should always be reported.

Keywords: Statistical analyses; Clinical trials; p-values; Effect estimates; Confidence intervals


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    Mills JL. Data torturing. N EnglJ Med 1993;329:1196–9.CrossrefGoogle Scholar

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    ICH E9. Note for guidance on statistical principles for clinical trials (CPMP/ICH/363/96); 2013. http://www.ema.europa.eu/docs/en_GB/document_ library/Scientific_guideline/2009/09/WC500002928.pdf.Google Scholar

About the article

School of Pharmacy, University of Oslo, Norway. Tel.: +47 22 85 61 72; fax: +47 22 85 44 02

Received: 2013-07-19

Accepted: 2013-07-19

Published Online: 2013-10-01

Published in Print: 2013-10-01

Conflict of interestNo conflict of interests declared.

Citation Information: Scandinavian Journal of Pain, Volume 4, Issue 4, Pages 220–223, ISSN (Online) 1877-8879, ISSN (Print) 1877-8860, DOI: https://doi.org/10.1016/j.sjpain.2013.07.023.

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