Healthy Skepticism Library item: 2278

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Publication type: Journal Article

Sterne J, Smith G.
Sifting the evidence -- what's wrong with significance tests?
BMJ 2001; 322:226-231
http://bmj.bmjjournals.com/cgi/content/full/322/7280/226?maxtoshow=&HITS=10&hits=10&RESULTFORMAT=&author1=Sterne+J&andorexactfulltext=and&searchid=1124938332664_18808&stored_search=&FIRSTINDEX=0&sortspec=relevance&resourcetype=1

Abstract:

Summary points

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P values, or significance levels, measure the strength of the evidence against the null hypothesis; the smaller the P value, the stronger the evidence against the null hypothesis

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An arbitrary division of results, into “significant” or “non-significant” according to the P value, was not the intention of the founders of statistical inference

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A P value of 0.05 need not provide strong evidence against the null hypothesis, but it is reasonable to say that P<0.001 does. In the results sections of papers the precise P value should be presented, without reference to arbitrary thresholds

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Results of medical research should not be reported as “significant” or “non-significant” but should be interpreted in the context of the type of study and other available evidence. Bias or confounding should always be considered for findings with low P values

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To stop the discrediting of medical research by chance findings we need more powerful studies