Network meta-analysis is a general approach to integrate the results of multiple studies in which multiple treatments are compared, often in a pairwise manner. In this tutorial, we illustrate the procedures for conducting a network meta-analysis for binary outcomes data in the Bayesian framework using example data. Our goal is to describe the workflow of such an analysis and to explain how to generate informative results such as ranking plots and treatment risk posterior distribution plots. The R code used to conduct a network meta-analysis in the Bayesian setting is provided at GitHub.

中文翻译：

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如何进行贝叶斯网络元分析。


网络荟萃分析是整合多项研究结果的通用方法，其中通常以成对的方式比较多种治疗方法。在本教程中，我们使用示例数据说明在贝叶斯框架中对二元结果数据进行网络元分析的过程。我们的目标是描述此类分析的工作流程，并解释如何生成信息丰富的结果，例如排名图和治疗风险后验分布图。 GitHub 上提供了用于在贝叶斯设置中进行网络元分析的 R 代码。