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The use of controls in interrupted time series studies of public health interventions.
International Journal of Epidemiology ( IF 7.7 ) Pub Date : 2018-12-01 , DOI: 10.1093/ije/dyy135
James Lopez Bernal 1 , Steven Cummins 1 , Antonio Gasparrini 1, 2
Affiliation  

Interrupted time series analysis differs from most other intervention study designs in that it involves a before-after comparison within a single population, rather than a comparison with a control group. This has the advantage that selection bias and confounding due to between-group differences are limited. However, the basic interrupted time series design cannot exclude confounding due to co-interventions or other events occurring around the time of the intervention. One approach to minimizse potential confounding from such simultaneous events is to add a control series so that there is both a before-after comparison and an intervention-control group comparison. A range of different types of controls can be used with interrupted time series designs, each of which has associated strengths and limitations. Researchers undertaking controlled interrupted time series studies should carefully consider a priori what confounding events may exist and whether different controls can exclude these or if they could introduce new sources of bias to the study. A prudent approach to the design, analysis and interpretation of controlled interrupted time series studies is required to ensure that valid information on the effectiveness of health interventions can be ascertained.

中文翻译:

在公共卫生干预措施的中断时间序列研究中使用对照。

中断时间序列分析与大多数其他干预研究设计的不同之处在于,它涉及在单个人群中进行前后比较,而不是与对照组进行比较。这样做的好处是,由于组间差异而导致的选择偏差和混淆是有限的。然而,基本的中断时间序列设计不能排除由于共同干预或干预前后发生的其他事件造成的混杂。最小化此类同时事件的潜在混杂的一种方法是添加一个控制系列,以便同时进行前后比较和干预对照组比较。一系列不同类型的控件可用于中断时间序列设计,每种控件都有相关的优势和局限性。进行受控中断时间序列研究的研究人员应该先验地仔细考虑可能存在哪些混杂事件,以及不同的控制是否可以排除这些,或者它们是否会给研究引入新的偏差来源。需要对受控中断时间序列研究的设计、分析和解释采取审慎的方法,以确保可以确定有关健康干预措施有效性的有效信息。
更新日期:2018-07-05
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