Selection Bias Requires Selection: The Case of Collider Stratification Bias

被引:6
作者
Lu, Haidong [2 ,3 ,4 ]
Gonsalves, Gregg S. [3 ,4 ,5 ]
Westreich, Daniel [1 ,6 ]
机构
[1] UNC Gillings Sch Global Publ Hlth, Dept Epidemiol, 105C McGavran Greenberg Hall CB 7435, Chapel Hill, NC 27599 USA
[2] Yale Sch Med, Dept Internal Med, Sect Gen Internal Med, New Haven, CT USA
[3] Yale Sch Publ Hlth, Publ Hlth Modeling Unit, New Haven, CT USA
[4] Yale Sch Med, Program Addict Med, New Haven, CT USA
[5] Yale Sch Publ Hlth, Dept Epidemiol Microbial Dis, New Haven, CT USA
[6] UNC Gillings Sch Global Publ Hlth, Dept Epidemiol, Chapel Hill, NC USA
基金
美国国家卫生研究院;
关键词
causal diagrams; collider adjustment bias; collider stratification bias; epidemiologic research; overadjustment bias; selection bias;
D O I
10.1093/aje/kwad213
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
In epidemiology, collider stratification bias, the bias resulting from conditioning on a common effect of two causes, is oftentimes considered a type of selection bias, regardless of the conditioning methods employed. In this commentary, we distinguish between two types of collider stratification bias: collider restriction bias due to restricting to one level of a collider (or a descendant of a collider) and collider adjustment bias through inclusion of a collider (or a descendant of a collider) in a regression model. We argue that categorizing collider adjustment bias as a form of selection bias may lead to semantic confusion, as adjustment for a collider in a regression model does not involve selecting a sample for analysis. Instead, we propose that collider adjustment bias can be better viewed as a type of overadjustment bias. We further provide two distinct causal diagram structures to distinguish collider restriction bias and collider adjustment bias. We hope that such a terminological distinction can facilitate easier and clearer communication.
引用
收藏
页码:407 / 409
页数:3
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