Temporal changes in magnitude of effect sizes reported in many areas of research are a threat to the credibility of the results and conclusions of meta‐analysis. Numerous sequential methods for meta‐analysis have been proposed to detect changes and monitor trends in effect sizes so that meta‐analysis can be updated when necessary and interpreted based on the time it was conducted. The difficulties of sequential meta‐analysis under the random‐effects model are caused by dependencies in increments introduced by the estimation of the heterogeneity parameter τ². In this paper, we propose the use of a retrospective cumulative sum (CUSUM)‐type test with bootstrap critical values. This method allows retrospective analysis of the past trajectory of cumulative effects in random‐effects meta‐analysis and its visualization on a chart similar to CUSUM chart. Simulation results show that the new method demonstrates good control of Type I error regardless of the number or size of the studies and the amount of heterogeneity. Application of the new method is illustrated on two examples of medical meta‐analyses. © 2016 The Authors. Research Synthesis Methods published by John Wiley & Sons Ltd.

中文翻译：

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随机效应荟萃分析中的顺序变化检测和时间趋势监测。


许多研究领域报告的效应大小的时间变化对荟萃分析的结果和结论的可信度构成威胁。人们提出了许多用于荟萃分析的序贯方法来检测效应大小的变化和监测趋势，以便荟萃分析可以在必要时更新并根据进行时间进行解释。随机效应模型下序贯荟萃分析的困难是由异质性参数τ ²的估计引入的增量依赖性引起的。在本文中，我们建议使用具有引导临界值的回顾性累积和（CUSUM）型检验。该方法允许对随机效应荟萃分析中累积效应的过去轨迹进行回顾性分析，并在类似于 CUSUM 图的图表上进行可视化。模拟结果表明，无论研究的数量或规模以及异质性的数量如何，新方法都可以很好地控制 I 类错误。新方法的应用通过两个医学荟萃分析的例子进行了说明。 © 2016 作者。研究合成方法由 John Wiley & Sons Ltd 出版。