Bormel J I, Ferguson L R
UCLA Center for Health Sciences.
Proc Annu Symp Comput Appl Med Care. 1994:944-8.
Analyzing raw data can be prohibitively time consuming. A variety of graphical techniques have been developed to address this problem. Although graphical analysis can provide a simple yet comprehensive overview of a large dataset, often these techniques fail to capture the essence of data trends. In addition, the ability to easily query any component of the data subset frequently remains burdensome. In this paper, we present a general method to address these issues for cross-tabulation tables and provide examples of their use in medical research.
分析原始数据可能极其耗时。人们已经开发了各种图形技术来解决这个问题。尽管图形分析可以提供对大型数据集的简单而全面的概述，但这些技术往往无法抓住数据趋势的本质。此外，频繁轻松查询数据子集的任何组件的能力通常仍然很麻烦。在本文中，我们提出了一种针对交叉表解决这些问题的通用方法，并提供了它们在医学研究中的使用示例。
