https://scholars.lib.ntu.edu.tw/handle/123456789/521750
標題: | Analysis of seasonal data using the Lorenz curve and the associated Gini Index | 作者: | WEN-CHUNG LEE | 公開日期: | 1996 | 卷: | 25 | 期: | 2 | 起(迄)頁: | 426-434 | 來源出版物: | International Journal of Epidemiology | 摘要: | Background. Epidemiological inferences about the aetiology of a disease can often be made from its seasonal patterns. However, due to its multifactorial nature, the seasonality component can be obscured by other factors. It is therefore important to develop statistical techniques which are sensitive to minute temporal changes. Methods. The Lorenz curve and the associated Gini index are applied for characterizing and testing seasonal variations. Computer simulations were conducted to compare the powers of the Gini test and other seasonality tests. We also show that the Gini index can itself be interpreted as a probability related to temporal clustering. Results. The powers of the proposed tests are shown to be higher than or at least comparable to other tests under various conditions. Conclusions. Though computer-demanding, the proposed method is well-suited for analysing seasonal data. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-0029918059&doi=10.1093%2fije%2f25.2.426&partnerID=40&md5=ece05e0778c76e5fca736ee3743c2947 https://scholars.lib.ntu.edu.tw/handle/123456789/521750 |
ISSN: | 0300-5771 | DOI: | 10.1093/ije/25.2.426 | SDG/關鍵字: | article; computer analysis; computer simulation; data analysis; female; human; major clinical study; newborn; priority journal; probability; reliability; seasonal variation; system analysis; Anencephaly; Cluster Analysis; Computer Simulation; England; Humans; Incidence; Infant, Newborn; Reproducibility of Results; Risk Factors; Seasons; Sensitivity and Specificity; Statistics, Nonparametric |
顯示於: | 流行病學與預防醫學研究所 |
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