Count data regression charts for the monitoring of surveillance time series
Count data regression charts for the monitoring of surveillance time series
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DOI：
10.1016/j.csda.2008.02.015
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发表时间：
2008-05-15
影响因子：
1.8
通讯作者：
Paul, Michaela
中科院分区：
文献类型：
--
作者：
Hoehle, Michael;Paul, Michaela
控制图的泊松和负二项分布的基础上，监测时间序列的计数通常出现在传染病的监测。假设对照组平均值随时间变化，在对数尺度上呈线性，具有截距和季节性分量。如果截距发生偏移，系统将失去控制。使用广义似然比（GLR）统计量的监测计划，制定在线检测是否发生偏移的截距。在泊松的情况下，GLR检测器的必要数量可以有效地计算递归公式。扩展到更一般的替代品，例如包含自回归流行病的组件进行了讨论。使用Monte Carlo模拟运行长度的性质所提出的计划进行了研究和泊松计划相比，现有的方法。图表的实用性证明，将其应用到观测到的数量在德国2001-2006年的盐性海达病例。(c)2008 Elsevier B. V.保留所有权利。
Control charts based on the Poisson and negative binomial distribution for monitoring time series of counts typically arising in the surveillance of infectious diseases are presented. The in-control mean is assumed to be time-varying and linear on the log-scale with intercept and seasonal components. If a shift in the intercept occurs the system goes out-of-control. Using the generalized likelihood ratio (GLR) statistic a monitoring scheme is formulated to detect on-line whether a shift in the intercept occurred. In the case of Poisson the necessary quantities of the GLR detector can be efficiently computed by recursive formulas. Extensions to more general alternatives e.g. containing an auto-regressive epidemic component are discussed. Using Monte Carlo simulations run-length properties of the proposed schemes are investigated and the Poisson scheme is compared to existing methods. The practicability of the charts is demonstrated by applying them to the observed number of salmonella hadar cases in Germany 2001-2006. (c) 2008 Elsevier B.V. All rights reserved.