多介质的异质介入效应:半参数和非参数方法

IF 1.7 4区 医学 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Journal of Causal Inference Pub Date : 2023-01-01 DOI:10.1515/jci-2022-0070
Max Rubinstein, Zach Branson, Edward Kennedy
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引用次数: 0

摘要

摘要:我们提出了半参数和非参数方法来估计在两个因果顺序未知的离散中介条件下的条件干预间接效应。平均干预间接效应已被证明将平均治疗效应分解为直接效应和干预间接效应,量化假设干预对中介分布的影响。然而,这些效应在协变量分布中可能是异质的。我们考虑在特定点估计这些效应的问题。我们提出了一个基于影响函数的条件效应投影估计,并证明在某些条件下我们可以获得根n一致和渐近正态估计。其次,我们提出了一种完全非参数的估计方法,并展示了这种方法可以达到oracle收敛速度的条件。最后,我们提出了一个敏感性分析,以确定在存在中介结果混淆的情况下平均和条件效应的界限。我们证明了同样的方法很容易扩展到允许对这些边界进行估计。我们通过研究2021年2月期间COVID-19疫苗接种对抑郁症的影响的异质性效应来得出结论。
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Heterogeneous interventional effects with multiple mediators: Semiparametric and nonparametric approaches
Abstract We propose semiparametric and nonparametric methods to estimate conditional interventional indirect effects in the setting of two discrete mediators whose causal ordering is unknown. Average interventional indirect effects have been shown to decompose an average treatment effect into a direct effect and interventional indirect effects that quantify effects of hypothetical interventions on mediator distributions. Yet these effects may be heterogeneous across the covariate distribution. We consider the problem of estimating these effects at particular points. We propose an influence function-based estimator of the projection of the conditional effects onto a working model, and show under some conditions that we can achieve root-n consistent and asymptotically normal estimates. Second, we propose a fully nonparametric approach to estimation and show the conditions where this approach can achieve oracle rates of convergence. Finally, we propose a sensitivity analysis that identifies bounds on both the average and conditional effects in the presence of mediator-outcome confounding. We show that the same methods easily extend to allow estimation of these bounds. We conclude by examining heterogeneous effects with respect to the effect of COVID-19 vaccinations on depression during February 2021.
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来源期刊
Journal of Causal Inference
Journal of Causal Inference Decision Sciences-Statistics, Probability and Uncertainty
CiteScore
1.90
自引率
14.30%
发文量
15
审稿时长
86 weeks
期刊介绍: Journal of Causal Inference (JCI) publishes papers on theoretical and applied causal research across the range of academic disciplines that use quantitative tools to study causality.
期刊最新文献
Evaluating Boolean relationships in Configurational Comparative Methods Comparison of open-source software for producing directed acyclic graphs. LINGUISTIC FEATURES AND PRESENTATION OF MATERIALS ON ENGLISH TEXTBOOK “WHEN ENGLISH RINGS A BELL” BASED ON BSNP Heterogeneous interventional effects with multiple mediators: Semiparametric and nonparametric approaches Attributable fraction and related measures: Conceptual relations in the counterfactual framework
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