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Confidence intervals and p‐values in clinical decision making
Author(s) -
Akobeng Anthony K
Publication year - 2008
Publication title -
acta pædiatrica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.772
H-Index - 115
eISSN - 1651-2227
pISSN - 0803-5253
DOI - 10.1111/j.1651-2227.2008.00836.x
Subject(s) - medicine , confidence interval , population , statistics , clinical trial , range (aeronautics) , value (mathematics) , statistical hypothesis testing , clinical practice , clinical significance , family medicine , mathematics , materials science , environmental health , composite material
Clinical trials are usually performed on a sample of people drawn from the population of interest. The results of a trial are, therefore, estimates of what might happen if the treatment were to be given to the entire population of interest. Confidence intervals (CIs) provide a range of plausible values for a population parameter and give an idea about how precise the measured treatment effect is. CIs may also provide some useful information on the clinical importance of results and, like p‐values, may also be used to assess ‘statistical significance’. Although other CIs can be calculated, the 95% CI is usually reported in the medical literature. In the long run, the 95% CI of an estimate is the range within which we are 95% certain that the true population parameter will lie. Despite the usefulness of the CI approach, hypothesis testing and the generation of p‐values are common in the medical literature. The p‐value is often used to express the probability that the observed differences between study groups are due to chance. p‐values provide no information on the clinical importance of results. Conclusion: It is good practice for authors of research articles to report CIs with their estimates instead of just p‐values as p‐values are less informative and convey no information on clinical importance.