The prediction interval is gaining prominence in meta-analysis as it enables the assessment of uncertainties in treatment effects and heterogeneity between studies. However, coverage probabilities of the current standard method for constructing prediction intervals cannot retain their nominal levels in general, particularly when the number of synthesized studies is moderate or small, because their validities depend on large sample approximations. Recently, several methods have developed been to address this issue. This paper briefly summarizes the recent developments in methods of prediction intervals and provides readable examples using R for multiple types of data with simple code. The pimeta package is an R package that provides these improved methods to calculate accurate prediction intervals and graphical tools to illustrate these results. The pimeta package is listed in ``CRAN Task View: Meta-Analysis.'' The analysis is easily performed in R using a series of R packages.
翻译:预测间隔在元分析中越来越突出,因为它有助于评估治疗效果的不确定性和各项研究之间的异质性;然而,目前用于构建预测间隔的标准方法的概率不能保持其一般的名义水平,特别是当综合研究的数量是中度或小,因为其有效性取决于大样本近似值。最近,已经制定了一些方法来解决这一问题。本文件简要概述了预测间隔方法的最新发展情况,并提供了可读的例子,用R来提供具有简单代码的多种类型的数据。Pimeta软件包是一个R软件包,提供这些改进的方法来计算准确的预测间隔和图形工具以说明这些结果。Pimeta软件包在“CRAN任务视图:Meta-Anacultect.”中列出,“Meta-Anacultect.”分析很容易在R中使用一系列R软件包进行。