Sequential methods for random-effects meta-analysis.

Sequential methods for random-effects meta-analysis.
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DOI:
10.1002/sim.4088
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发表时间:
2011-04-30
影响因子:
2
通讯作者:
Simmonds, Mark
Simmonds, Mark
中科院分区:
医学3区
文献类型:
--
作者:
Higgins, Julian P. T.;Whitehead, Anne;Simmonds, Mark

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虽然荟萃分析通常被视为回顾性活动,但它们越来越多地被应用于前瞻性研究,为特定的研究问题提供最新的证据。当更新荟萃分析时,应考虑由于重复显著性检验而导致假阳性结果的可能性。我们讨论了使用序贯方法进行荟萃分析,纳入随机效应,以允许异质性的研究。我们提出了一种方法,使用近似的半贝叶斯过程来更新证据的统计研究方差,从一个信息丰富的先验分布,可能是基于以前的荟萃分析的结果。我们在模拟研究中将我们的方法与其他方法(包括传统的累积荟萃分析方法)进行了比较,并观察到它的I型和II型错误率接近名义水平。我们举例说明了在治疗消化性溃疡出血的方法。版权所有© 2010约翰威利父子有限公司.
Although meta-analyses are typically viewed as retrospective activities, they are increasingly being applied prospectively to provide up-to-date evidence on specific research questions. When meta-analyses are updated account should be taken of the possibility of false-positive findings due to repeated significance tests. We discuss the use of sequential methods for meta-analyses that incorporate random effects to allow for heterogeneity across studies. We propose a method that uses an approximate semi-Bayes procedure to update evidence on the among-study variance, starting with an informative prior distribution that might be based on findings from previous meta-analyses. We compare our methods with other approaches, including the traditional method of cumulative meta-analysis, in a simulation study and observe that it has Type I and Type II error rates close to the nominal level. We illustrate the method using an example in the treatment of bleeding peptic ulcers. Copyright © 2010 John Wiley & Sons, Ltd.
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