Research Centre for Gender, Health and Ageing, Newcastle Institute of Public Health, University of Newcastle, Newcastle, Australia.
J Health Serv Res Policy. 2011 Jul;16(3):147-52. doi: 10.1258/jhsrp.2010.010063. Epub 2011 May 4.
To show how fractional polynomial methods can usefully replace the practice of arbitrarily categorizing data in epidemiology and health services research.
A health service setting is used to illustrate a structured and transparent way of representing non-linear data without arbitrary grouping.
When age is a regressor its effects on an outcome will be interpreted differently depending upon the placing of cutpoints or the use of a polynomial transformation.
Although it is common practice, categorization comes at a cost. Information is lost, and accuracy and statistical power reduced, leading to spurious statistical interpretation of the data. The fractional polynomial method is widely supported by statistical software programs, and deserves greater attention and use.
展示分数多项式方法如何在流行病学和卫生服务研究中有用地替代任意分类数据的做法。
利用卫生服务环境来说明一种结构化和透明的表示非线性数据的方法，而无需任意分组。
当年龄是一个回归变量时，根据分界点的位置或多项式变换的使用，其对结果的影响将有所不同。
尽管分类是一种常见的做法，但它也有代价。信息会丢失，准确性和统计效力会降低，从而导致对数据的虚假统计解释。分数多项式方法得到了广泛的统计软件程序的支持，值得更多的关注和使用。
