Statistical estimates and clinical trials.
Statistical estimates and significance tests address distinct (but related) questions using the same data. Point estimates and confidence intervals of differences are statistical estimates that address: "How LARGE is the difference in the population of interest?" A significance test addresses the question: "How LIKELY was the difference to have occurred by chance?" Because p-values deal with the existence of a real nonzero difference between treatments but not the size of that treatment difference, they cannot be used to assess clinical (practical) significance. A confidence interval is a range of values used to infer both the size of a difference and the uncertainty of the estimate. Examples illustrate how confidence intervals help us assess both the clinical significance and the statistical significance of an observed difference. The point estimate is the outcome difference actually observed in the study sample; it is also the best single-number estimate of the unknown difference in the sampled population. Point estimates, confidence intervals, and p-values extract complementary information from study data and should all be reported for major results.
Braitman
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Office for Research Development, Albert Einstein Medical Center, Philadelphia, Pennsylvania 19141.
D002986:Clinical Trials as Topic / Q000706:statistics & numerical data*; D016001:Confidence Intervals; D003627:Data Interpretation, Statistical; D016013:Likelihood Functions