Uncertainty of the time of first significance in random effects cumulative meta-analysis
Uncertainty of the time of first significance in random effects cumulative meta-analysis
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DOI：
10.1016/s0197-2456(96)00014-1
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发表时间：
1996-10-01
期刊：
影响因子：
--
通讯作者：
Antman, EM
中科院分区：
文献类型：
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作者：
Berkey, CS;Mosteller, F;Antman, EM
我们提出了一个过程中的累积荟萃分析的临床和统计利益的数量进行评估。我们使用蒙特卡罗模拟研究来评估累积荟萃分析中达到显著性时间的误差方差。对于我们模拟的特定累积荟萃分析，在最早显著性时通过随机效应方法估计的治疗效应的95%置信区间似乎大致合适，除非假设的治疗效应接近零。当两种治疗方法的疗效不同时，我们使用的蒙特卡罗方法也可以估计累积荟萃分析的功效。我们在五个累积荟萃分析的背景下说明了这些问题，每个分析比较了两种预防心肌梗死死亡率的治疗方法。这些模拟荟萃分析证明了我们的主要观点，即首次显著性时间，无论如何参数化，本身是一个具有误差方差的随机变量。(C)Elsevier Science Inc.
We propose a process for evaluating quantities of clinical and statistical interest in cumulative meta-analysis. We use Monte Carlo simulation studies to assess the error variance of the time to significance in cumulative meta-analysis. For the specific cumulative meta-analyses that we simulated, the 95% confidence interval of the treatment effect, estimated by the random effects method at the time of earliest significance, appears to be approximately appropriate except when the hypothesized treatment effect is near the null. The Monte Carlo approach that we used can also estimate the power of a cumulative meta-analysis when two treatments differ in efficacy. We illustrate these issues in the context of five cumulative meta-analyses, each comparing two treatments for preventing mortality from myocardial infarction. These simulated meta-analyses demonstrate our main point, which is that the time of first significance, however parameterized, is itself a random variable with error variance. (C) Elsevier Science Inc.