Nam J M
Biostatistics Branch, National Cancer Institute, Rockville, Maryland 20892, USA.
Stat Med. 1995 Sep 30;14(18):2037-49. doi: 10.1002/sim.4780141809.
When designing a trial to establish that a new treatment is as effective as a standard one, the conventional test procedure and sample size based on a null hypothesis of no difference between two treatments is inappropriate. Several authors have investigated test statistics and corresponding sample sizes based on the null hypothesis that the standard treatment is more effective than the new by at least some specific value for a single 2 x 2 table. This paper considers a trial that involves several 2 x 2 tables and presents an approximate formula for the sample size required to obtain a given power of a one-tailed score test for a null hypothesis of a specific common non-zero difference between two treatments across strata. I show that the sample size for a trial based on an unstratified test is always larger than that based on a stratified test when the design is balanced.
在设计一项试验以确定一种新疗法与标准疗法效果相同时,基于两种疗法无差异的零假设的传统测试程序和样本量是不合适的。几位作者针对单个2×2表格,基于标准疗法比新疗法至少有效某个特定值的零假设,研究了检验统计量和相应的样本量。本文考虑了一个涉及多个2×2表格的试验,并给出了一个近似公式,用于计算在各层中两种疗法存在特定共同非零差异的零假设下,获得给定单尾得分检验功效所需的样本量。我证明,当设计平衡时,基于未分层检验的试验样本量总是大于基于分层检验的样本量。