Significance tests in clinical research—Challenges and pitfalls

Significance tests in clinical research—Challenges and pitfalls AbstractBackgroundStatistical 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.MethodsThis 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.ResultsBasic 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 recommendationsSome 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Scandinavian Journal of Pain de Gruyter

Significance tests in clinical research—Challenges and pitfalls

Loading next page...
 
/lp/degruyter/significance-tests-in-clinical-research-challenges-and-pitfalls-y11OX7iggE
Publisher
De Gruyter
Copyright
© 2013 Scandiavian Association for the Study of Pain
ISSN
1877-8860
eISSN
1877-8879
D.O.I.
10.1016/j.sjpain.2013.07.023
Publisher site
See Article on Publisher Site

Abstract

AbstractBackgroundStatistical 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.MethodsThis 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.ResultsBasic 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 recommendationsSome 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.

Journal

Scandinavian Journal of Painde Gruyter

Published: Dec 29, 2017

There are no references for this article.

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 12 million articles from more than
10,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Unlimited reading

Read as many articles as you need. Full articles with original layout, charts and figures. Read online, from anywhere.

Stay up to date

Keep up with your field with Personalized Recommendations and Follow Journals to get automatic updates.

Organize your research

It’s easy to organize your research with our built-in tools.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

Monthly Plan

  • Read unlimited articles
  • Personalized recommendations
  • No expiration
  • Print 20 pages per month
  • 20% off on PDF purchases
  • Organize your research
  • Get updates on your journals and topic searches

$49/month

Start Free Trial

14-day Free Trial

Best Deal — 39% off

Annual Plan

  • All the features of the Professional Plan, but for 39% off!
  • Billed annually
  • No expiration
  • For the normal price of 10 articles elsewhere, you get one full year of unlimited access to articles.

$588

$360/year

billed annually
Start Free Trial

14-day Free Trial