Ganju Jitendra, Xing Biao
Amgen Inc., 1120 Veterans Blvd., South San Francisco, CA 94080, USA.
Stat Med. 2009 Jan 15;28(1):24-38. doi: 10.1002/sim.3442.
We extend a method we had previously described (Statist. Med. 2005) to estimate the within-group variance of a continuous endpoint without breaking the blind in a randomized clinical trial. Specifically, we: (a) explain how the method may be used for a wider set of designs than we had previously indicated; (b) obtain a within-group, covariate-adjusted, blinded variance estimator; (c) illustrate use of the method for sample size re-estimation; and (d) describe a procedure to determine whether or not the blinded variance estimator works well not just on average but for the data set at hand. The proposed method is simple to use and makes no additional assumptions than is made for unblinded analysis. Simulations show that for realistic sample sizes there is virtually no inflation in the Type I error rate. When weighing the burden imposed by interim unblinded re-estimation with the loss in precision with blinded re-estimation, it may be advantageous for some trials to use the blinded method.
我们扩展了之前描述的一种方法（《统计医学》，2005年），用于在不打破随机临床试验盲态的情况下估计连续终点的组内方差。具体而言，我们：(a) 解释该方法如何用于比我们之前指出的更广泛的设计集；(b) 获得一个组内、经协变量调整的盲态方差估计量；(c) 说明该方法在样本量重新估计中的应用；以及 (d) 描述一种程序，以确定盲态方差估计量不仅在平均水平上，而且对于手头的数据集是否有效。所提出的方法易于使用，并且除了非盲态分析所做的假设外，不做额外假设。模拟表明，对于实际样本量，第一类错误率几乎没有膨胀。在权衡中期非盲态重新估计带来的负担与盲态重新估计精度损失时，对于某些试验来说，使用盲态方法可能是有利的。
