Bias formulas for external adjustment and sensitivity analysis of unmeasured confounders

被引:83
作者
Arah, Onyebuchi A. [1 ,2 ]
Chiba, Yasutaka [2 ,3 ]
Greenland, Sander [2 ,4 ]
机构
[1] Univ Amsterdam, Acad Med Ctr, Dept Social Med, NL-1100 DE Amsterdam, Netherlands
[2] Univ Calif Los Angeles, Sch Publ Hlth, Dept Epidemiol, Los Angeles, CA 90024 USA
[3] Kyoto Univ, Sch Publ Hlth, Dept Biostat, Kyoto 6068501, Japan
[4] Univ Calif Los Angeles, Coll Letters & Sci, Dept Stat, Los Angeles, CA 90024 USA
关键词
bias; bias adjustment; confounding; epidemiologic methods; odds ratio; risk difference; risk ratio; sensitivity analysis; unmeasured confounders;
D O I
10.1016/j.annepidem.2008.04.003
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
PURPOSE: Uncontrolled confounders are an important source of bias in epidermiologic studies. The authors review and derive a set of parallel simple formulas for bias factors in the risk difference, risk ratio, and odds ratio from studies with an unmeasured polytomous confounder and a dichotomous exposure and outcome. METHODS: The authors show how the bias formulas are related to and are sometimes simpler than earlier formulas. The article contains three examples, including a Monte Carlo sensitivity analysis of a preadjusted or conditional estimate. RESULTS: All the bias expressions can be given parallel formulations as the difference or ratio of (i) the Sum across confounder strata of each exposure-stratified confounder-outcome effect measure multiplied by the confounder prevalences among the exposed and (ii) the sum across confounder strata of the same effect measure multiplied by the confounder prevalences among the unexposed. The basic formulas can be applied to scenarios with a polytomous confounder, exposure, or outcome. CONCLUSIONS: In addition to aiding design and analysis strategies for confounder control, the bias for, mulas provide a link between classical standardization decompositions of demography and classical bias formulas of epidemiology. They are also useful in constructing general programs for sensitivity analysis and more elaborate probabilistic risk analyses.
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页码:637 / 646
页数:10
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