Literature DB >> 31594165

[Design and analysis of two groups interrupt time series].

Y Li1, S C Yu2, C G Jin3, M J Yang1, X J Ma1, Q Q Wang2.   

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.

Keywords:  Interrupted time-series design; Intervention; Program evaluation; Quasi-experimental design

Mesh:

Year:  2019        PMID: 31594165     DOI: 10.3760/cma.j.issn.0254-6450.2019.09.027

Source DB:  PubMed          Journal:  Zhonghua Liu Xing Bing Xue Za Zhi        ISSN: 0254-6450


  1 in total

1.  The impacts of Chinese drug volume-based procurement policy on the use of policy-related antibiotic drugs in Shenzhen, 2018-2019: an interrupted time-series analysis.

Authors:  Ying Yang; Lei Chen; Xinfeng Ke; Zongfu Mao; Bo Zheng
Journal:  BMC Health Serv Res       Date:  2021-07-08       Impact factor: 2.655

  1 in total

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