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Like all statistical methods, RCTs are subject to both 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. Regarding Type II errors, despite the publication of a 1978 paper noting that the sample sizes of many "negative" RCTs were too small to make definitive conclusions about the negative results, by 2005-2006 a sizeable proportion of RCTs still had inaccurate or incompletely reported sample size calculations.
 
Like all statistical methods, RCTs are subject to both 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. Regarding Type II errors, despite the publication of a 1978 paper noting that the sample sizes of many "negative" RCTs were too small to make definitive conclusions about the negative results, by 2005-2006 a sizeable proportion of RCTs still had inaccurate or incompletely reported sample size calculations.
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像所有的统计方法一样,rct 同时受到 i 型(“假阳性”)和 II 型(“假阴性”)统计错误的影响。关于 i 型错误,一个典型的 RCT 将使用0.05(即,1/20)作为 RCT 错误地发现两个同样有效的治疗方法显著不同的概率。关于第二类错误,尽管1978年发表的一篇论文指出,许多”负面”随机对照试验的样本量太小,无法对负面结果作出明确的结论,但到2005-2006年,相当大一部分随机对照试验的样本量计算仍然不准确或不完全。
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像所有的统计方法一样,rct 同时受到Ⅰ型(“假阳性”)和 II 型(“假阴性”)统计错误的影响。关于Ⅰ型错误,一个典型的 RCT 将使用0.05(即,1/20)作为 RCT 错误地发现两个同样有效的治疗方法显著不同的概率。关于第二类错误,尽管1978年发表的一篇论文指出,许多”负面”随机对照试验的样本量太小,无法对负面结果作出明确的结论,但到2005-2006年,相当大一部分随机对照试验的样本量计算仍然不准确或不完全。
    
This is a commonly used and intuitive procedure, similar to "repeated fair coin-tossing."<ref name="SchulzGrimes2002"/> Also known as "complete" or "unrestricted" randomization, it is [[Robust statistics|robust]] against both selection and accidental biases. However, its main drawback is the possibility of imbalanced group sizes in small RCTs.  It is therefore recommended only for RCTs with over 200 subjects.<ref name="Lachin-1988b">{{Cite journal |vauthors=Lachin JM, Matts JP, Wei LJ | title = Randomization in clinical trials: conclusions and recommendations | journal = [[Controlled Clinical Trials]] | volume = 9 | issue = 4 | pages = 365–74 | year = 1988 | pmid = 3203526 |  doi = 10.1016/0197-2456(88)90049-9 | hdl = 2027.42/27041 | url = https://deepblue.lib.umich.edu/bitstream/2027.42/27041/1/0000029.pdf | hdl-access = free }}</ref>
 
This is a commonly used and intuitive procedure, similar to "repeated fair coin-tossing."<ref name="SchulzGrimes2002"/> Also known as "complete" or "unrestricted" randomization, it is [[Robust statistics|robust]] against both selection and accidental biases. However, its main drawback is the possibility of imbalanced group sizes in small RCTs.  It is therefore recommended only for RCTs with over 200 subjects.<ref name="Lachin-1988b">{{Cite journal |vauthors=Lachin JM, Matts JP, Wei LJ | title = Randomization in clinical trials: conclusions and recommendations | journal = [[Controlled Clinical Trials]] | volume = 9 | issue = 4 | pages = 365–74 | year = 1988 | pmid = 3203526 |  doi = 10.1016/0197-2456(88)90049-9 | hdl = 2027.42/27041 | url = https://deepblue.lib.umich.edu/bitstream/2027.42/27041/1/0000029.pdf | hdl-access = free }}</ref>
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