Title |
The thresholds for statistical and clinical significance – a five-step procedure for evaluation of intervention effects in randomised clinical trials
|
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Published in |
BMC Medical Research Methodology, March 2014
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DOI | 10.1186/1471-2288-14-34 |
Pubmed ID | |
Authors |
Janus Christian Jakobsen, Christian Gluud, Per Winkel, Theis Lange, Jørn Wetterslev |
Abstract |
Thresholds for statistical significance are insufficiently demonstrated by 95% confidence intervals or P-values when assessing results from randomised clinical trials. First, a P-value only shows the probability of getting a result assuming that the null hypothesis is true and does not reflect the probability of getting a result assuming an alternative hypothesis to the null hypothesis is true. Second, a confidence interval or a P-value showing significance may be caused by multiplicity. Third, statistical significance does not necessarily result in clinical significance. Therefore, assessment of intervention effects in randomised clinical trials deserves more rigour in order to become more valid. |
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Spain | 1 | 9% |
Unknown | 7 | 64% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 5 | 45% |
Scientists | 4 | 36% |
Science communicators (journalists, bloggers, editors) | 1 | 9% |
Practitioners (doctors, other healthcare professionals) | 1 | 9% |
Mendeley readers
Geographical breakdown
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New Zealand | 1 | <1% |
United States | 1 | <1% |
Russia | 1 | <1% |
Peru | 1 | <1% |
Unknown | 194 | 98% |
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Readers by professional status | Count | As % |
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Student > Ph. D. Student | 35 | 18% |
Student > Master | 24 | 12% |
Other | 16 | 8% |
Student > Bachelor | 11 | 6% |
Other | 42 | 21% |
Unknown | 30 | 15% |
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Psychology | 16 | 8% |
Nursing and Health Professions | 10 | 5% |
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Mathematics | 5 | 3% |
Other | 36 | 18% |
Unknown | 47 | 24% |