Gu Hong-Qiu, Li Dao-Ji, Liu Chelsea, Rao Zhen-Zhen
China National Clinical Research Center for Neurological Diseases, Beijing 100050, China.
Tiantan Clinical Trial and Research Center for Stroke, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100050, China.
Ann Transl Med. 2018 Aug;6(16):326. doi: 10.21037/atm.2018.08.13.
Demographic tables are widely used to report baseline characteristics in medical research. However, the traditional copy-paste production method is time-consuming and frequently generates typing errors. Current available statistical tools are still far away from ideal, because they are difficult to understand and they lack flexibility. A user-friendly, dynamic, and flexible tool is needed for researchers to automate the creation of demographic tables. In this paper, we introduce a SAS macro, %ggBaseline, that automatically analyzing and reporting baseline characteristics with the final production of publication-quality demographic tables. The macro provides optional parameters that allow for the full customization of desired demographic tables. Since %ggBaseline allows for the quick creation of reproducible and fully customizable tables, it can be beneficial to academics, clinical trials and medical research studies by making the presentation and formatting of results faster and more efficient.
人口统计学表格在医学研究中被广泛用于报告基线特征。然而,传统的复制粘贴制作方法耗时且经常产生打字错误。当前可用的统计工具仍远非理想之选,因为它们难以理解且缺乏灵活性。研究人员需要一个用户友好、动态且灵活的工具来自动创建人口统计学表格。在本文中,我们介绍了一个SAS宏%ggBaseline,它能自动分析并报告基线特征,最终生成具有发表质量的人口统计学表格。该宏提供了可选参数,可对所需的人口统计学表格进行完全定制。由于%ggBaseline允许快速创建可重复且完全可定制的表格,通过使结果的呈现和格式化更快、更高效,它对学术界、临床试验和医学研究具有益处。