Using intervention time series analyses to assess the effects of imperfectly identifiable natural events: a general method and example.
Using intervention time series analyses to assess the effects of imperfectly identifiable natural events: a general method and example.
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DOI：
10.1186/1471-2288-6-16
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发表时间：
2006-04-03
影响因子：
4
通讯作者：
Day, Carolyn
中科院分区：
文献类型：
--
作者：
Gilmour, Stuart;Degenhardt, Louisa;Day, Carolyn
背景：干预时间序列分析是分析突发事件对时间序列数据影响的重要方法。ITSA方法在本质上是准实验性的，用这些方法建模的有效性取决于对干预时机和过程响应的假设。方法：本文介绍了如何应用ITSA来分析当事件发生的时间不准确时，计划外事件对时间序列的影响，因此ITSA方法的问题被非计划性干预开始点的不确定性放大。这些方法是用2001年澳大利亚海洛因短缺的例子来说明的，这为研究在广泛采取减少危害措施的环境中海洛因供应量突然变化的健康和社会后果提供了机会。这些方法的应用使人们能够对计划外和识别不佳的干预措施的后果有价值的见解，同时最大限度地减少虚假结果的风险。
BACKGROUND: Intervention time series analysis (ITSA) is an important method for analysing the effect of sudden events on time series data. ITSA methods are quasi-experimental in nature and the validity of modelling with these methods depends upon assumptions about the timing of the intervention and the response of the process to it.METHOD: This paper describes how to apply ITSA to analyse the impact of unplanned events on time series when the timing of the event is not accurately known, and so the problems of ITSA methods are magnified by uncertainty in the point of onset of the unplanned intervention.RESULTS: The methods are illustrated using the example of the Australian Heroin Shortage of 2001, which provided an opportunity to study the health and social consequences of an abrupt change in heroin availability in an environment of widespread harm reduction measures.CONCLUSION: Application of these methods enables valuable insights about the consequences of unplanned and poorly identified interventions while minimising the risk of spurious results.