...
首页> 外文期刊>Statistical methods in medical research >Sample size considerations in active-control non-inferiority trials with binary data based on the odds ratio
【24h】

Sample size considerations in active-control non-inferiority trials with binary data based on the odds ratio

机译:基于比值比的具有二进制数据的主动控制非劣效性试验中的样本量注意事项

获取原文
获取原文并翻译 | 示例

摘要

This paper presents an approximate closed form sample size formula for determining non-inferiority in active-control trials with binary data. We use the odds-ratio as the measure of the relative treatment effect, derive the sample size formula based on the score test and compare it with a second, well-known formula based on the Wald test. Both closed form formulae are compared with simulations based on the likelihood ratio test. Within the range of parameter values investigated, the score test closed form formula is reasonably accurate when non-inferiority margins are based on odds-ratios of about 0.5 or above and when the magnitude of the odds ratio under the alternative hypothesis lies between about 1 and 2.5. The accuracy generally decreases as the odds ratio under the alternative hypothesis moves upwards from 1. As the non-inferiority margin odds ratio decreases from 0.5, the score test closed form formula increasingly overestimates the sample size irrespective of the magnitude of the odds ratio under the alternative hypothesis. The Wald test closed form formula is also reasonably accurate in the cases where the score test closed form formula works well. Outside these scenarios, the Wald test closed form formula can either underestimate or overestimate the sample size, depending on the magnitude of the non-inferiority margin odds ratio and the odds ratio under the alternative hypothesis. Although neither approximation is accurate for all cases, both approaches lead to satisfactory sample size calculation for non-inferiority trials with binary data where the odds ratio is the parameter of interest.
机译:本文提出了一种近似封闭形式的样本量公式,用于确定具有二进制数据的主动对照试验中的非劣效性。我们使用比值比作为相对治疗效果的量度,基于得分测试得出样本量公式,并将其与基于Wald检验的第二个众所周知的公式进行比较。将两个封闭式公式与基于似然比检验的模拟进行比较。在所调查的参数值范围内,当非劣质性差基于约0.5或更高的赔率比,并且替代假设下赔率比的大小介于约1和1之间时,分数检验封闭形式公式是相当准确的。 2.5。当替代假设下的优势比从1向上移动时,准确性通常会降低。随着非劣质性优势优势比从0.5降低,分数检验封闭式公式会越来越高估样本大小,而与假设下的优势比的大小无关替代假设。 Wald检验封闭式公式在分数检验封闭式公式运行良好的情况下也相当准确。在这些情况之外,Wald检验封闭式公式可能会低估或高估样本大小,具体取决于非劣质边际优势比和替代假设下的优势比的大小。尽管两种近似方法都不适合所有情况,但是对于使用二进制数据进行非劣效性试验而言,两种方法均能获得令人满意的样本量计算,其中优势比是相关参数。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号