在检验关于季节变化的假设时使用柯尔莫哥洛夫 - 斯米尔诺夫型统计量。
The use of a Kolmogorov--Smirnov type statistic in testing hypotheses about seasonal variation.
作者信息
Freedman L S
出版信息
J Epidemiol Community Health. 1979 Sep;33(3):223-8. doi: 10.1136/jech.33.3.223.
Abstract
This paper presents a non-parametric method for testing departures from a uniform seasonal variation in incidence of disease. The method may be used either with exact dates of incidence when they are available or with monthly totals. It is equally valid for sinusoidal and non-sinusoidal departures from uniformity. A simulation study shows it to be much more powerful than other non-parametric alternatives and nearly as powerful as Edwards's test in detecting sinusoidal departures.
摘要
本文提出了一种非参数方法，用于检验疾病发病率的均匀季节性变化是否存在偏差。该方法既可以在有确切发病日期时使用，也可以使用每月的总计数据。对于正弦和非正弦的均匀性偏差，该方法同样有效。一项模拟研究表明，在检测正弦偏差方面，它比其他非参数方法更具效力，且几乎与爱德华兹检验的效力相当。
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