Lui K J
Department of Mathematical Sciences, College of Sciences, San Diego State University, California 92182-7720, USA.
J Pharmacokinet Biopharm. 1997 Aug;25(4):507-13. doi: 10.1023/a:1025749210833.
When the measurement of outcome is unreliable or the cost of obtaining an additional subject is relatively high compared to the cost of obtaining an additional measurement from the same subject, it may be desirable to consider taking more than one measurement per subject to increase power or to minimize the cost in a clinical trial. When each subject in two comparison groups has a fixed number of repeated measurements, this paper develops an asymptotic procedure to calculate the number of subjects per group required to achieve a given power for an a-level bioequivalence test. Furthermore, Monte Carlo simulation is used to evaluate the accuracy of the approximate sample size calculation procedure and a brief discussion on how to determine the optimal number of repeated measurements is included.
当结局测量不可靠，或者与从同一受试者获取额外测量值的成本相比，获取额外受试者的成本相对较高时，在临床试验中可能需要考虑对每个受试者进行多次测量，以提高检验效能或使成本最小化。当两个比较组中的每个受试者都有固定次数的重复测量时，本文提出了一种渐近方法，用于计算每组达到给定检验效能的a水平生物等效性检验所需的受试者数量。此外，使用蒙特卡罗模拟来评估近似样本量计算程序的准确性，并包含了关于如何确定重复测量最佳次数的简要讨论。
