A Selective Review of Negative Control Methods in Epidemiology.

A Selective Review of Negative Control Methods in Epidemiology.
复制标题

DOI:
10.1007/s40471-020-00243-4
复制
发表时间:
2020-12
影响因子:
3.3
通讯作者:
Tchetgen ET
Tchetgen ET
中科院分区:
医学4区
文献类型:
--
作者:
Shi X;Miao W;Tchetgen ET

文献摘要

参考文献

被引文献

相似文献

阴性对照是在流行病学研究中检测和调整偏差的有力工具。本文将负面对照介绍给更广泛的受众,并在一个正式的负面对照框架的基础上,为原则性设计和因果分析提供指导。我们回顾和总结因果和统计假设、实用策略和验证标准,这些假设和验证标准可以与主题知识相结合来执行负面对照分析。我们还回顾了现有的检测、减少和纠正混杂偏差的统计方法,并简要讨论了在双阴性对照设计中因果效应的非参数识别的最新进展。利用现代医疗数据进行有效和准确的因果推断具有巨大的潜力,在当代医疗数据中,负面对照经常可用。利用阴性对照设计和分析观测数据是卫生和社会科学日益感兴趣的一个领域。尽管取得了这些进展,但还需要进一步努力传播这些新方法,以确保执业流行病学家采用这些方法。
Negative controls are a powerful tool to detect and adjust for bias in epidemiological research. This paper introduces negative controls to a broader audience and provides guidance on principled design and causal analysis based on a formal negative control framework. We review and summarize causal and statistical assumptions, practical strategies, and validation criteria that can be combined with subject-matter knowledge to perform negative control analyses. We also review existing statistical methodologies for the detection, reduction, and correction of confounding bias, and briefly discuss recent advances towards nonparametric identification of causal effects in a double-negative control design. There is great potential for valid and accurate causal inference leveraging contemporary healthcare data in which negative controls are routinely available. Design and analysis of observational data leveraging negative controls is an area of growing interest in health and social sciences. Despite these developments, further effort is needed to disseminate these novel methods to ensure they are adopted by practicing epidemiologists.
DOI: 10.1097/ede.0000000000000504
发表时间: 2016-09
期刊: Epidemiology (Cambridge, Mass.)
影响因子: --
作者:
Arnold BF;Ercumen A;Benjamin-Chung J;Colford JM Jr
通讯作者: Colford JM Jr
DOI: 10.2307/1912775
发表时间: 1982-01-01
期刊: ECONOMETRICA
影响因子: 6.1
作者:
HANSEN, LP
通讯作者: HANSEN, LP
DOI: 10.1093/aje/kww154
发表时间: 2017-01-01
影响因子: 5
作者:
Lin, Brian M.;Curhan, Sharon G.;Curhan, Gary C.
通讯作者: Curhan, Gary C.
DOI: 10.1097/ede.0b013e3181d61eeb
发表时间: 2010-05
期刊: Epidemiology (Cambridge, Mass.)
影响因子: --
作者:
Lipsitch M;Tchetgen Tchetgen E;Cohen T
通讯作者: Cohen T
DOI: 10.2307/2291629
发表时间: 1996-06-01
影响因子: 3.7
作者:
Angrist, JD;Imbens, GW;Rubin, DB
通讯作者: Rubin, DB