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.

中文翻译：

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如何使用 R 进行荟萃分析：实用教程。

目的 荟萃分析对于获得对现有证据的公正评估至关重要。总的来说，在过去三十年中，荟萃分析的使用不断增加，心理健康成为一个主要研究课题。因此，必须充分理解其方法并解释其结果。在本出版物中，我们使用心理健康领域的工作示例描述了如何使用免费的统计软件环境 R 进行荟萃分析。方法 R包meta用于进行标准荟萃分析。使用 R 包 metasens 对缺失的二元结果数据和潜在的选择偏差进行敏感性分析。提供并清楚地描述了所有必要的 R 命令以进行和报告分析。结果工作示例考虑了二元结果：我们展示了如何进行固定效应和随机效应荟萃分析和亚组分析，生成森林图和漏斗图，以及测试和调整漏斗图的不对称性。所有这些步骤对于其他结果类型的作用类似。结论 R 是进行荟萃分析的强大而灵活的工具。本出版物简要介绍了该主题，并提供了 R 中可用的更高级元分析方法的指导。