Odds Ratios for Mediation Analysis for a Dichotomous Outcome

被引:619
作者
VanderWeele, Tyler J. [1 ,2 ]
Vansteelandt, Stijn [3 ]
机构
[1] Harvard Univ, Sch Publ Hlth, Dept Epidemiol, Boston, MA 02115 USA
[2] Harvard Univ, Sch Publ Hlth, Dept Biostat, Boston, MA 02115 USA
[3] Univ Ghent, Dept Appl Math & Comp Sci, B-9000 Ghent, Belgium
基金
美国国家卫生研究院;
关键词
case-control studies; causal inference; decomposition; dichotomous response; epidemiologic methods; interaction; logistic regression; odds ratio; MARGINAL STRUCTURAL MODELS; PROPORTION; INTERVENTIONS; INFERENCE; ESTROGEN;
D O I
10.1093/aje/kwq332
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
For dichotomous outcomes, the authors discuss when the standard approaches to mediation analysis used in epidemiology and the social sciences are valid, and they provide alternative mediation analysis techniques when the standard approaches will not work. They extend definitions of controlled direct effects and natural direct and indirect effects from the risk difference scale to the odds ratio scale. A simple technique to estimate direct and indirect effect odds ratios by combining logistic and linear regressions is described that applies when the outcome is rare and the mediator continuous. Further discussion is given as to how this mediation analysis technique can be extended to settings in which data come from a case-control study design. For the standard mediation analysis techniques used in the epidemiologic and social science literatures to be valid, an assumption of no interaction between the effects of the exposure and the mediator on the outcome is needed. The approach presented here, however, will apply even when there are interactions between the effect of the exposure and the mediator on the outcome.
引用
收藏
页码:1339 / 1348
页数:10
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