A minimal nontrivial example of higher-order evidence

被引：0
作者：
Cole, Stephen R. [1 ]
Shook-Sa, Bonnie E. [2 ]
Zivich, Paul N. [1 ]
Edwards, Jessie K. [1 ]
机构：
[1] Univ North Carolina, Gillings Sch Global Publ Hlth, Dept Epidemiol, Chapel Hill, NC USA
[2] Univ North Carolina, Gillings Sch Global Publ Hlth, Dept Biostat, Chapel Hill, NC USA
来源：
AMERICAN JOURNAL OF EPIDEMIOLOGY | 2025年
关键词：
bias; measurement error; random error; systematic error;
D O I：
10.1093/aje/kwae321
中图分类号：
R1 [预防医学、卫生学];
学科分类号：
1004 ; 120402 ;
摘要：
Higher-order evidence (ie, evidence about evidence) allows epidemiologists and other health data scientists to account for measurement error in validation data. Here, to illustrate the use of higher-order evidence, we provide a minimal nontrivial example of estimating the proportion and show how higher-order evidence can be used to construct sensitivity analyses. The proposed method provides a flexible approach to account for multiple levels of distortion in the results of epidemiologic studies.
引用
收藏
页码：886 / 888
页数：3
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