Doubly robust estimation of the generalized impact fraction

被引:12
|
作者
Taguri, Masataka [1 ]
Matsuyama, Yutaka [2 ]
Ohashi, Yasuo [2 ]
Harada, Akiko [3 ]
Ueshima, Hirotsugu [4 ]
机构
[1] Yokohama City Univ, Dept Biostat & Epidemiol, Grad Sch Med, Minami Ku, Yokohama, Kanagawa 2320024, Japan
[2] Univ Tokyo, Dept Biostat, Sch Publ Hlth, Tokyo, Japan
[3] Publ Hlth Res Fdn, Stress Res Inst, Tokyo, Japan
[4] Shiga Univ Med Sci, Lifestyle Related Dis Prevent Ctr, Shiga, Japan
关键词
Attributable fraction; Causal inference; Doubly robust estimation; Generalized impact fraction; Inverse probability weighting; ATTRIBUTABLE FRACTION; INFERENCE; RISK;
D O I
10.1093/biostatistics/kxr038
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
The attributable fraction (AF) is commonly used in epidemiology to quantify the impact of an exposure to a disease. Recently, Sjolander and Vansteelandt (2011. Doubly robust estimation of attributable fractions. Biostatistics 12, 112-121) introduced the doubly robust (DR) estimator of the AF, which involves positing models for both the exposure and the outcome and is consistent if at least one of these models is correct. In this article, we derived a DR estimator of the generalized impact fraction (IF) with a polytomous exposure. The IF is a measure that generalizes the AF by allowing the possibility of incomplete removal of the exposure. We demonstrated the performance of the proposed estimator via a simulation study and by application to data from a large prospective cohort study conducted in Japan.
引用
收藏
页码:455 / 467
页数:13
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