The reassessment of trial perspectives from interim data - a critical view
The reassessment of trial perspectives from interim data - a critical view
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DOI：
10.1002/sim.2180
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发表时间：
2006-01-15
影响因子：
2
通讯作者：
Koenig, F
中科院分区：
文献类型：
--
作者：
Bauer, P;Koenig, F
如果在审判期间进行中期分析，考虑到在中期分析中观察到的结果，很容易确定在审判中达到驳回的条件权力。由于实际效果大小未知，因此可通过使用在规划阶段为研究提供动力的效果大小或通过使用真实大小的中期估计(或两者的组合)来计算条件能力。在任何一种情况下，条件功率都是随机变量，其密度取决于分析时间和实际影响大小。在零假设下，在小比例样本单元后的早期中期分析中，当使用规划阶段的影响大小进行计算时，条件功率通常会接近总体功率。在这种情况下，仍然必须进行大多数观察，第一阶段的小样本总体上将被基于错误参数值的假设的第二阶段机会所支配。结果表明，在中等强度的研究中，条件功率可以在0.5左右对称分布。当使用中期估计来计算条件功率时，密度通常是U形的。与相应的成组序贯设计相比，在总体功效和平均样本量方面，通过一个具体的例子，展示了使用条件能力来使用灵活的两阶段组合检验来重新评估样本量的影响。对于较小的真实效应大小，根据中期估计重新计算试验中的样本量可能会导致平均样本量相对于总体功率的增加而付出过大的代价。最后，从真条件幂估计的角度讨论了这一问题。版权所有(C)2005 John Wiley&Sons，Ltd.
If an interim analysis is performed during a trial it is tempting to determine the conditional power to reach a rejection in the trial given the observed results in the interim analysis. Since the true effect size is unknown the conditional power may be calculated by using the effect size, which the study has been powered for in the planning phase or by using an interim estimate of the true size (or a combination of both). In either case the conditional power is a random variable and its density is investigated depending on the analysis time and the true effect size. Under the null hypothesis, in early interim analyses after a small proportion of sample units, the conditional power typically will be close to the overall power when the effect size from the planning stage is used for calculation. In this case the majority of observations must still be made and the small first-stage sample in general will be dominated by the hypothetical second-stage chance based on the wrong parameter value. It is shown that the conditional power in moderately underpowered studies can have a distribution symmetric around 0.5. When using the interim estimate for calculating the conditional power the density in general will be u-shaped. The impact of using conditional power to reassess the sample size using flexible two-stage combination tests is shown for a specific example in terms of overall power and average sample size as compared to the corresponding group sequential design. For small true effect sizes mid-trial sample size recalculation based on an interim estimate may lead to an overly large price to be paid in average sample size in relation to the gain in overall power. Finally, the problem is discussed in terms of estimating the true conditional power. Copyright (c) 2005 John Wiley & Sons, Ltd.