Propensity score techniques and the assessment of measured covariate balance to test causal associations in psychological research.
Propensity score techniques and the assessment of measured covariate balance to test causal associations in psychological research.
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DOI：
10.1037/a0019623
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发表时间：
2010-09
影响因子：
7
通讯作者：
Anthony, James C.
中科院分区：
文献类型：
--
作者：
Harder, Valerie S.;Stuart, Elizabeth A.;Anthony, James C.
在心理学研究中，使用倾向评分（PS）统计技术来解决因果推理问题引起了相当大的兴趣。许多PS技术存在，但很少有指导方针，以帮助应用研究人员在他们的理解，使用和评估。本研究概述了PS估计和PS应用的可用技术。它还提供了一种帮助比较PS技术的方法，使用所得的测量协变量平衡作为在技术之间进行选择的标准。这项研究的实证例子涉及到早发性大麻问题与随后的负面心理健康结果之间的潜在因果关系，使用的数据来自一项前瞻性队列研究。PS技术是根据其平衡患有和不患有早发性大麻问题的个人的测量的潜在混杂协变量分布的能力来描述和评估的。本文确定了PS技术，产生良好的统计平衡的背景下，这个特定的研究问题和队列中所选择的测量协变量。
There is considerable interest in using propensity score (PS) statistical techniques to address questions of causal inference in psychological research. Many PS techniques exist, yet few guidelines are available to aid applied researchers in their understanding, use and evaluation. This study gives an overview of available techniques for PS estimation and PS application. It also provides a way to help compare PS techniques, using the resulting measured covariate balance as the criterion for selecting between techniques. The empirical example for this study involves the potential causal relationship linking early-onset cannabis problems and subsequent negative mental health outcomes, using data from a prospective cohort study. PS techniques are described and evaluated based on their ability to balance the distributions of measured potentially confounding covariates for individuals with and without early-onset cannabis problems. This paper identifies the PS techniques that yield good statistical balance of the chosen measured covariates within the context of this particular research question and cohort.
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