TableOne: an online web application and R package for summarising and visualising data
TableOne: an online web application and R package for summarising and visualising data
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DOI：
10.1136/ebmental-2020-300162
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发表时间：
2020-08-01
影响因子：
5.2
通讯作者：
Mavridis, Dimitris
中科院分区：
文献类型：
--
作者：
Panos, Agapios;Mavridis, Dimitris
目的开发一个易于使用的R包和Web应用程序，以总结临床试验不同分支或不同暴露的基线特征。方法表格和图表是可视化、交流和汇总数据的有效手段。在比较有效性研究中，提供不同治疗组的特征和结果的概要是常见的。这种表的流行为它赢得了一个名字，我们简单地叫它‘TableOne’，因为它通常是TableOne在查看已发表的临床试验时遇到的第一个。这样的表不仅包括每个组的描述性统计数据，还包括用于检查组间差异的适当测试(p值和95%配置项)。我们已经开发了一个R包(称为TableOne)(可通过访问)来快速总结和比较不同组的结果。我们还将其扩展到一个研究人员易于处理的在线Web应用程序。所有的计算都是在R中完成的，曲线图是使用PLOTY库生成的。我们提供了如何使用Web应用程序的详细说明。结果应用程序以分步格式(向导)指导用户，并且可以通过以下链接(https://esm.uoi.gr/shiny/tableone/).)中的任何浏览器进行访问结论这一简单易用的Web应用程序将帮助研究人员快速、轻松地可视化不同处理组或不同暴露的差异。
Objective To develop an easy-to-use R package and web application that summarises baseline characteristics across different arms of a clinical trial or different exposures.Methods Tables and figures are the efficient means of visualising, communicating and summarising data. It is common in comparative effectiveness research to provide a synopsis of characteristics and outcomes across the various treatment groups. The popularity of such a table has earned it a name and we simply call it the 'TableOne', as it is usually the first TableOne encounters looking at a published clinical trial. Such a table includes not only descriptive statistics for each group but also appropriate tests (p values and 95% CIs) for checking for differences across groups. We have developed an R package (called TableOne) (accessible through) th at quickly summarises and compares results across different groups. We have also extended it to an online web application that is easily handled by the researcher. All computations are done in R and plots are produced using the plotly library. We provide a detailed description on how to use the web application.Results The application guides the user in a step by step format (wizard) and it is accessible through any browser in the following link (https://esm.uoi.gr/shiny/tableone/). Finally, appropriate interactive plots are provided for each variable.Conclusions This easy-to-use web application will help researchers quickly and easily to visualise differences across treatment groups or different exposures.