Timmesfeld Nina, Schäfer Helmut, Müller Hans-Helge
Institute of Medical Biometry and Epidemiology, Philipps University of Marburg, Bunsenstr. 3, Marburg D-35037, Germany.
Stat Med. 2007 May 30;26(12):2449-64. doi: 10.1002/sim.2725.
In clinical trials with t-distributed test statistics the required sample size depends on the unknown variance. Taking estimates from previous studies often leads to a misspecification of the true value of the variance. Hence, re-estimation of the variance based on the collected data and re-calculation of the required sample size is attractive. We present a flexible method for extensions of fixed sample or group-sequential trials with t-distributed test statistics. The method can be applied at any time during the course of the trial and does not require the necessity to pre-specify a sample size re-calculation rule. All available information can be used to determine the new sample size. The advantage of our method when compared with other adaptive methods is maintenance of the efficient t-test design when no extensions are actually made. We show that the type I error rate is preserved.
在采用t分布检验统计量的临床试验中，所需样本量取决于未知方差。根据以往研究进行估计往往会导致对方差真值的错误设定。因此，基于收集到的数据重新估计方差并重新计算所需样本量很有吸引力。我们提出了一种灵活的方法，用于扩展采用t分布检验统计量的固定样本或成组序贯试验。该方法可在试验过程中的任何时间应用，且无需预先指定样本量重新计算规则。所有可用信息均可用于确定新的样本量。与其他自适应方法相比，我们的方法的优势在于，在实际未进行扩展时能保持有效的t检验设计。我们证明了I型错误率得以保持。
