How to perform a meta-analysis with R: a practical tutorial
How to perform a meta-analysis with R: a practical tutorial
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DOI：
10.1136/ebmental-2019-300117
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发表时间：
2019-11-01
影响因子：
5.2
通讯作者：
Schwarzer, Guido
中科院分区：
文献类型：
--
作者：
Balduzzi, Sara;Ruecker, Gerta;Schwarzer, Guido
目的Meta分析对于获得对现有证据的无偏倚评价具有重要意义。一般来说，在过去的三十年中，荟萃分析的使用一直在增加，心理健康是一个主要的研究课题。因此，必须充分理解其方法并解释其结果。在这份出版物中，我们描述了如何执行一个荟萃分析与免费提供的统计软件环境R，使用一个工作的例子，从该领域的精神health.Methods R包Meta进行标准的荟萃分析。使用R软件包元分析对缺失的二元结局数据和潜在的选择偏倚进行敏感性分析。所有必要的R命令，并清楚地描述进行和报告analysis.Results工作的例子认为是一个二元的结果：我们展示了如何进行固定效应和随机效应的荟萃分析和亚组分析，产生一个森林和漏斗图，并测试和调整漏斗图不对称。所有这些步骤对其他结果类型的工作类似。结论R代表了一个强大而灵活的工具来进行荟萃分析。这篇文章简要介绍了这个主题，并为R语言中更先进的荟萃分析方法提供了指导。
Objective Meta-analysis is of fundamental importance to obtain an unbiased assessment of the available evidence. In general, the use of meta-analysis has been increasing over the last three decades with mental health as a major research topic. It is then essential to well understand its methodology and interpret its results. In this publication, we describe how to perform a meta-analysis with the freely available statistical software environment R, using a working example taken from the field of mental health.Methods R package meta is used to conduct standard meta-analysis. Sensitivity analyses for missing binary outcome data and potential selection bias are conducted with R package metasens. All essential R commands are provided and clearly described to conduct and report analyses.Results The working example considers a binary outcome: we show how to conduct a fixed effect and random effects meta-analysis and subgroup analysis, produce a forest and funnel plot and to test and adjust for funnel plot asymmetry. All these steps work similar for other outcome types.Conclusions R represents a powerful and flexible tool to conduct meta-analyses. This publication gives a brief glimpse into the topic and provides directions to more advanced meta-analysis methods available in R.