Bespoke instrumental variables with nonideal reference populations.

IF 5 2区 医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Arvid Sjölander, Erin E Gabriel
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引用次数: 0

Abstract

Recently, a bespoke instrumental variable method was proposed, which, under certain assumptions, can eliminate bias due to unmeasured confounding when estimating the causal exposure effect among the exposed. This method uses data from both the study population of interest and a reference population in which the exposure is completely absent. In this article, we extend the bespoke instrumental variable method to allow for a nonideal reference population that may include exposed individuals. Such an extension is particularly important in randomized trials with nonadherence, where even individuals in the control arm may have access to the treatment under investigation. We further scrutinize the assumptions underlying the bespoke instrumental method and caution the reader about the potential nonrobustness of the method to these assumptions.

使用非理想参考人口的定制工具变量。
最近,有人提出了一种定制的工具变量方法,在某些假设条件下,这种方法可以在估计暴露者的因果暴露效应时消除由于未测量的混杂因素造成的偏差。该方法同时使用相关研究人群和完全不存在暴露的参照人群的数据。在本文中,我们对定制工具变量方法进行了扩展,以考虑可能包括暴露对象的非理想参照人群。这种扩展在有非依从性的随机试验中尤为重要,因为在这种试验中,即使是对照组的受试者也有可能获得所研究的治疗。我们进一步仔细研究了定制工具法的基本假设,并提醒读者注意该方法对这些假设的潜在非稳健性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
American journal of epidemiology
American journal of epidemiology 医学-公共卫生、环境卫生与职业卫生
CiteScore
7.40
自引率
4.00%
发文量
221
审稿时长
3-6 weeks
期刊介绍: The American Journal of Epidemiology is the oldest and one of the premier epidemiologic journals devoted to the publication of empirical research findings, opinion pieces, and methodological developments in the field of epidemiologic research. It is a peer-reviewed journal aimed at both fellow epidemiologists and those who use epidemiologic data, including public health workers and clinicians.
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