RITS: a toolbox for assessing complex interventions via interrupted time series models.
RITS: a toolbox for assessing complex interventions via interrupted time series models.
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DOI：
10.1186/s12874-021-01322-w
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发表时间：
2021-07-08
影响因子：
4
通讯作者：
Ombao HC
中科院分区：
文献类型：
--
作者：
Cruz M;Pinto-Orellana MA;Gillen DL;Ombao HC
各种相互作用和相互依存的组成部分构成了复杂的干预措施。这些组成部分造成了评估旨在改善以患者为中心的结果的干预措施的真正影响的困难。中断时间序列(ITS)设计借鉴了病例交叉设计，作为一种准实验方法，能够在考虑时间相关性的同时，回顾评估干预的影响。虽然其设计适合于研究大规模公共卫生政策的影响，但现有的ITS软件实现了僵化的ITS方法，这种方法往往假设干预前和干预后阶段完全不同(通过一个已知的变化点或一组时间点)，不允许平均函数和相关结构的变化。本文介绍了稳健的中断时间序列(RITS)工具箱，这是一个独立的、用户友好的应用程序，研究人员可以使用它来实现灵活的ITS模型，该模型可以估计单个和多个ITS的干预对结果、水平和趋势变化的滞后影响，以及干预后相关性结构的变化。RITS工具箱结合了对结果中是否存在变化的正式测试，并在研究人员定义的一组可能的变化点上估计变化点。在具有多个ITS的设置中，RITS提供全局的所有单位变化点，并允许平均函数和相关结构中的单位特定变化。RITS工具箱是第一个允许研究人员使用灵活的ITS模型的软件，这些模型测试变化点的存在，估计变化点(如果需要估计的话)，并允许在变化点处的平均函数和相关结构的变化。RITS不需要任何统计(或其他)编程语言的知识，社区可以免费获得，并且可以在本地机器上下载和使用，以确保数据保护。
Various interacting and interdependent components comprise complex interventions. These components create difficulty in assessing the true impact of interventions designed to improve patient-centered outcomes. Interrupted time series (ITS) designs borrow from case-crossover designs and serve as quasi-experimental methodology able to retrospectively assess the impact of an intervention while accounting for temporal correlation. While ITS designs are aptly situated for studying the impacts of large-scale public health policies, existing ITS software implement rigid ITS methodology that often assume the pre- and post-intervention phases are fully differentiated (by a known change-point or set of time points) and do not allow for changes in both the mean functions and correlation structure. This article describes the Robust Interrupted Time Series (RITS) toolbox, a stand-alone user-friendly application researchers can use to implement flexible ITS models that estimate the lagged effect of an intervention on an outcome, level and trend changes, and post-intervention changes in the correlation structure, for single and multiple ITS. The RITS toolbox incorporates a formal test for the existence of a change in the outcome and estimates a change-point over a set of possible change-points defined by the researcher. In settings with multiple ITS, RITS provides a global over-all units change-point and allows for unit-specific changes in the mean functions and correlation structures. The RITS toolbox is the first piece of software that allows researchers to use flexible ITS models that test for the existence of a change-point, estimate the change-point (if estimation is desired), and allow for changes in both the mean functions and correlation structures at the change point. RITS does not require any knowledge of a statistical (or otherwise) programming language, is freely available to the community, and may be downloaded and used on a local machine to ensure data protection.
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影响因子：
2
作者：
Cruz M;Gillen DL;Bender M;Ombao H
通讯作者：
Ombao H
影响因子：
3.7
作者：
QUANDT, RE
通讯作者：
QUANDT, RE
DOI：
10.1046/j.1365-2710.2002.00430.x
发表时间：
2002-08-01
影响因子：
2
作者：
Wagner, AK;Soumerai, SB;Ross-Degnan, D
通讯作者：
Ross-Degnan, D
影响因子：
3.5
作者：
Alpert, Abby
通讯作者：
Alpert, Abby
影响因子：
7.7
作者：
Bernal JL;Cummins S;Gasparrini A
通讯作者：
Gasparrini A