利用调查数据进行因果推断的匹配设计:肯塔基州和田纳西州医用大麻合法化评估》。

IF 1.3 3区 生物学 Q4 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Marco H. Benedetti, Bo Lu, Motao Zhu
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引用次数: 0

摘要

围绕大麻合法化的一个担忧是,吸食大麻后驾车的现象可能会更加普遍。调查数据对于估算政策效果很有价值,但其观察性质和不平等的抽样概率给因果推断带来了挑战。为了利用调查数据估计人口层面的影响,我们提出了一种匹配设计,并实施了敏感性分析,以量化结论对未测量混杂因素的稳健程度。我们还介绍了理论依据和模拟研究。我们没有发现大麻合法化会增加容忍行为和对吸食大麻后驾车的态度,这些结论似乎对未测量的混杂因素具有适度的稳健性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A Matched Design for Causal Inference With Survey Data: Evaluation of Medical Marijuana Legalization in Kentucky and Tennessee

A Matched Design for Causal Inference With Survey Data: Evaluation of Medical Marijuana Legalization in Kentucky and Tennessee

A concern surrounding marijuana legalization is that driving after marijuana use may become more prevalent. Survey data are valuable for estimating policy effects, however their observational nature and unequal sampling probabilities create challenges for causal inference. To estimate population-level effects using survey data, we propose a matched design and implement sensitivity analyses to quantify how robust conclusions are to unmeasured confounding. Both theoretical justification and simulation studies are presented. We found no support that marijuana legalization increased tolerant behaviors and attitudes toward driving after marijuana use, and these conclusions seem moderately robust to unmeasured confounding.

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来源期刊
Biometrical Journal
Biometrical Journal 生物-数学与计算生物学
CiteScore
3.20
自引率
5.90%
发文量
119
审稿时长
6-12 weeks
期刊介绍: Biometrical Journal publishes papers on statistical methods and their applications in life sciences including medicine, environmental sciences and agriculture. Methodological developments should be motivated by an interesting and relevant problem from these areas. Ideally the manuscript should include a description of the problem and a section detailing the application of the new methodology to the problem. Case studies, review articles and letters to the editors are also welcome. Papers containing only extensive mathematical theory are not suitable for publication in Biometrical Journal.
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