| 李洋,于石成,金承刚,杨梦婕,马学军,王琦琦.两组中断时间序列设计及其分析方法[J].Chinese journal of Epidemiology,2019,40(9):1159-1163 |
| 两组中断时间序列设计及其分析方法 |
| Design and analysis of two groups interrupt time series |
| Received:January 07, 2019 |
| DOI：10.3760/cma.j.issn.0254-6450.2019.09.027 |
| KeyWord: 中断时间序列设计 类实验设计 干预 项目评价 |
| English Key Word: Interrupted time-series design Quasi-experimental design Intervention Program evaluation |
| FundProject:国家传染病重大专项（2018ZX10711001，2017ZX10104001）；国家重点研发计划（2018YFC1315300，2018YFC1315305） |
| Author Name | Affiliation | E-mail | | Li Yang | Key Laboratory of Medical Virology and Viral Diseases of National Health Commission, National Institute of Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China | | | Yu Shicheng | Office of Epidemiology, Chinese Center for Disease Control and Prevention, Beijing 102206, China | | | Jin Chenggang | School of Social Development and Public Policy, Beijing Normal University, Beijing 100875, China | | | Yang Mengjie | Key Laboratory of Medical Virology and Viral Diseases of National Health Commission, National Institute of Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China | | | Ma Xuejun | Key Laboratory of Medical Virology and Viral Diseases of National Health Commission, National Institute of Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China | maxj@ivdc.chinacdc.cn | | Wang Qiqi | Office of Epidemiology, Chinese Center for Disease Control and Prevention, Beijing 102206, China | wangqq@chinacdc.cn |
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| Abstract: |
| 中断时间序列（ITS）是对具有时间序列特点的结果变量进行分析，评价干预措施是否有效的类实验设计方法。相对于单组ITS，两组ITS可以更好地控制干预前混杂因素的影响，评价干预措施的效果。本文阐述两组ITS的设计原理和统计方法，以两市疾病发病率为例，采用Prais-Winsten法和Newey-West法拟合线性回归模型，并对结果进行了详细的解释和比较。在干预实施的时间窗口中存在多个政策转变时，两组ITS可以更好地平衡序列干预前已存在的趋势，科学地估计干预措施有效性具有重要的现实意义，为项目效果评价提供一个新的思路。 |
| English Abstract: |
| Interrupted time-series (ITS) is a quasi-experimental design which evaluates the effectiveness of an intervention based on time-series outcome variables. Compared with the single group of ITS, the two groups of ITS can better control the influence of pre-interventional confounding factors and evaluate the effectiveness of the intervention. This paper summarizes the principles and statistical methods of two groups of ITS by an example of evaluating vaccine effect on the incidence of a disease in two cities. The regression model is fitted by Prais-Winsten method and Newey-West method and the results are explained and compared in detail. When the intervention is performed with other confounding interventions at the same time, the two groups of ITS can be more effective to balance the existing trends before the intervention, and evaluate the effectiveness of intervention. The method of two groups of ITS has important practical significance, providing new insights in program evaluation. |
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