Robertson C, Boyle P
Division of Epidemiology and Biostatistics, European Institute of Oncology, Milan, Italy.
Stat Med. 1998 Jun 30;17(12):1325-39. doi: 10.1002/(sici)1097-0258(19980630)17:12<1325::aid-sim854>3.0.co;2-r.
In a companion article we have reviewed a number of available modelling approaches employed in estimating the influence of age, period and cohort effects on chronic disease rates. Here we review some of the graphical methods for displaying disease rates with a view to extracting information about the separate and joint effects of age, period and cohort. The more traditional displays such as line charts are compared to approaches based on smoothing and two- and three-dimensional plots which have recently been proposed. Other graphical techniques which are principally concerned with displaying interactions, such as biplots and correspondence analysis, are also considered. These techniques are illustrated with examples to compare the techniques revealing their strengths and weaknesses. It is clear that graphical approaches can be useful tools in understanding the behaviour of chronic disease time trends.
在一篇配套文章中，我们回顾了一些用于估计年龄、时期和队列效应对慢性病发病率影响的现有建模方法。在此，我们回顾一些用于展示疾病发病率的图形方法，以便提取有关年龄、时期和队列的单独及联合效应的信息。将更传统的展示方式（如折线图）与最近提出的基于平滑以及二维和三维绘图的方法进行比较。还考虑了主要用于展示相互作用的其他图形技术，如双标图和对应分析。通过示例对这些技术进行说明，以比较它们的优缺点。显然，图形方法在理解慢性病时间趋势的行为方面可以成为有用的工具。
