BACKGROUND Data-visualization methods are essential to explore and communicate meta-analytic data and results. With a large number of novel graphs proposed quite recently, a comprehensive, up-to-date overview of available graphing options for meta-analysis is unavailable. METHODS We applied a multi-tiered search strategy to find the meta-analytic graphs proposed and introduced so far. We checked more than 150 retrievable textbooks on research synthesis methodology cover to cover, six different software programs regularly used for meta-analysis, and the entire content of two leading journals on research synthesis. In addition, we conducted Google Scholar and Google image searches and cited-reference searches of prior reviews of the topic. Retrieved graphs were categorized into a taxonomy encompassing 11 main classes, evaluated according to 24 graph-functionality features, and individually presented and described with explanatory vignettes. RESULTS We ascertained more than 200 different graphs and graph variants used to visualize meta-analytic data. One half of these have accrued within the past 10 years alone. The most prevalent classes were graphs for network meta-analysis (45 displays), graphs showing combined effect(s) only (26), funnel plot-like displays (24), displays showing more than one outcome per study (19), robustness, outlier and influence diagnostics (15), study selection and p-value based displays (15), and forest plot-like displays (14). The majority of graphs (130, 62.5%) possessed a unique combination of graph features. CONCLUSIONS The rich and diverse set of available meta-analytic graphs offers a variety of options to display many different aspects of meta-analyses. This comprehensive overview of available graphs allows researchers to make better-informed decisions on which graphs suit their needs and therefore facilitates using the meta-analytic tool kit of graphs to its full potential. It also constitutes a roadmap for a goal-driven development of further graphical displays for research synthesis.

中文翻译：

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绘制用于荟萃分析和系统评价的图形显示景观：综合评价、分类和特征分析。

背景技术数据可视化方法对于探索和传达元分析数据和结果至关重要。由于最近提出了大量新颖的图表，因此无法对元分析可用的图表选项进行全面、最新的概述。方法我们应用多层搜索策略来查找迄今为止提出和介绍的元分析图。我们从头到尾检查了 150 多本关于研究综合方法论的可检索教科书、六种经常用于荟萃分析的不同软件程序，以及两种领先的研究综合期刊的全部内容。此外，我们还进行了谷歌学术和谷歌图像搜索以及对该主题先前评论的引用参考文献搜索。检索到的图表被分为包含 11 个主要类别的分类法，根据 24 个图表功能特征进行评估，并用解释性插图单独呈现和描述。结果我们确定了 200 多个用于可视化元分析数据的不同图表和图表变体。其中一半是在过去十年内产生的。最常见的类别是网络荟萃分析图表（45 个显示）、仅显示组合效应的图表 (26)、漏斗图式显示 (24)、显示每项研究多个结果的显示 (19)、稳健性、异常值和影响诊断 (15)、研究选择和基于 p 值的显示 (15) 以及森林图式显示 (14)。大多数图表（130 个，62.5%）拥有独特的图表特征组合。结论 丰富多样的可用荟萃分析图表提供了多种选项来显示荟萃分析的许多不同方面。对可用图表的全面概述使研究人员能够就哪些图表适合他们的需求做出更明智的决定，从而有助于充分发挥图表元分析工具包的潜力。它还为研究综合的进一步图形显示的目标驱动开发制定了路线图。