title: Confidence intervals and p-values in clinical decision making.
abstract: 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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Department of Paediatric Gastroenterology, Booth Hall Children's Hospital, Central Manchester and Manchester Children's University Hospitals, Manchester, UK. tony.akobeng@cmmc.nhs.uk
authors.forename: Anthony K
authors.initials: AK
authors.lastname: Akobeng
mesh_terms: D015982:Bias; D016001:Confidence Intervals; D003627:Data Interpretation, Statistical; D003657:Decision Making; D006801:Humans; D010372:Pediatrics / Q000706:statistics & numerical data*