- - - - [ statistics statistique ] BASIC STATISTICS FOR CLINICLNS : 2 . INTERPRETING STUDY RESULTS : CONFIDENCE INTERVALS

In the second of fotur articles, the authors discuss the /estimatioin" approach to linterpreting stuidy results. Whereas, in hypothesis testing, study restIlts lead the reader to reject or accept a null hypothesis, in estimationi the reader can assess whether a result is strong or weak, definitive or not. A confidence interval, based on the observed result and the size of the samnple, is calcUlated. It provides a range of probabilities wlithir which the true probability would lie 95% or 90%Y of the time, depeniding on the precisionl desired. It also provides a way of determining whether the sample is large enoLugh to nmake the trial definitive. If the lower bouindary of a confidence interval is above the threshold considered clinically significant, theni the trial is positive and definitive; if the lower boundary is somewhat below the threshold, the trial is positive, but stuLdies with larger samples are needed. Sinmilarly, if the upper bouLndary of a confidenice interval is below the threshold considered significanit, the trial is negative and definitive. However, a negative result with a confidence interval that crosses the threshold means that trials with larger samples are needed to make a definitive determination of clin1ical importance.