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Randomized controlled trial
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=== Interpretation of statistical results === Like all statistical methods, RCTs are subject to both [[type I and type II errors|type I ("false positive") and type II ("false negative") statistical errors]]. Regarding Type I errors, a typical RCT will use 0.05 (i.e., 1 in 20) as the probability that the RCT will falsely find two equally effective treatments significantly different.<ref name="Wittes-2002">{{Cite journal |vauthors=Wittes J |year=2002 |title=Sample size calculations for randomized controlled trials |journal=Epidemiologic Reviews |volume=24 |issue=1 |pages=39β53 |doi=10.1093/epirev/24.1.39 |pmid=12119854 |doi-access=free}}</ref> Regarding Type II errors, despite the publication of a 1978 paper noting that the [[sample size]]s of many "negative" RCTs were too small to make definitive conclusions about the negative results,<ref name="Freiman-1978">{{Cite journal |vauthors=Freiman JA, Chalmers TC, Smith H, Kuebler RR |date=September 1978 |title=The importance of beta, the type II error and sample size in the design and interpretation of the randomized control trial. Survey of 71 "negative" trials |journal=The New England Journal of Medicine |volume=299 |issue=13 |pages=690β694 |doi=10.1056/NEJM197809282991304 |pmid=355881}}</ref> by 2005-2006 a sizeable proportion of RCTs still had inaccurate or incompletely reported sample size calculations.<ref name="Charles-2009">{{Cite journal |vauthors=Charles P, Giraudeau B, Dechartres A, Baron G, Ravaud P |date=May 2009 |title=Reporting of sample size calculation in randomised controlled trials: review |journal=BMJ |volume=338 |pages=b1732 |doi=10.1136/bmj.b1732 |pmc=2680945 |pmid=19435763 |doi-access=free}}</ref>
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