Multilevel Matching in Natural Experimental Studies: Application to Stepping up Counties.

Niloofar Ramezani, Alex Breno, Jill Viglione, Benjamin Mackey, Alison Evans Cuellar, April Chase, Jennifer Johnson, Faye Taxman
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Abstract

Among many approaches for selecting match control cases, few methods exist for natural experiments (Li, Zaslavsky & Landrum, 2007), especially when studying clustered or hierarchical data. The lack of randomization of treatment exposure gives importance to using proper statistical procedures that control for individual differences. In this natural experimental study, which has a hierarchical structure, we plan to evaluate the efforts of 455 counties across the United States to make targeted efforts to improve mental health services and reduce jail utilization over time. Nested within states, counties are clustered on health and social indicators, which affect the likelihood of making improvements in these areas. Similar to a randomized trial, prior to collecting survey data, it is necessary to identify matched control counties as study sites based on an array of state and county covariates. Accounting for the hierarchal structure of data, a blend of various probability-based models are presented to achieve this goal. Methods include multivariable models that control for observed differences among treatment and control groups, shrinkage based LASSO as a variable selection technique, and logistic models.

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自然实验研究中的多层次匹配:在提速县中的应用。
在许多选择匹配控制案例的方法中,很少有方法用于自然实验(Li, Zaslavsky & Landrum, 2007),特别是在研究聚类或分层数据时。治疗暴露缺乏随机化,因此必须使用适当的统计程序来控制个体差异。在这个具有等级结构的自然实验研究中,我们计划评估美国455个县的努力,以有针对性地改善心理健康服务,并随着时间的推移减少监狱的利用率。县嵌套在州内,按健康和社会指标进行分组,这影响到在这些领域取得改善的可能性。与随机试验类似,在收集调查数据之前,有必要根据一系列州和县协变量确定匹配的对照县作为研究地点。考虑到数据的层次结构,提出了一种基于概率的混合模型来实现这一目标。方法包括控制治疗组和对照组之间观察到的差异的多变量模型,基于收缩的LASSO作为变量选择技术,以及逻辑模型。
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Random Change-Point Non-linear Mixed Effects Model for left-censored longitudinal data: An application to HIV surveillance. Multilevel Matching in Natural Experimental Studies: Application to Stepping up Counties. Adaptive Design in the National Immunization Survey-Teen Provider Record Check Phase. Reducing Accelerometer Data from Instrumented Vehicles. An Evaluation of the Impact of Using an Alternate Caller ID Display in the National Immunization Survey.
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