Conditions for uniformly non-confounding of causal distribution effects over multiple covariates

被引：0

作者：

Wang, Xueli ^{[1
]}

机构：

[1] Beijing Univ Posts & Telecommun, Sch Sci, Beijing 100876, Peoples R China

来源：

JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY | 2010年 / 23卷 / 04期

关键词：

Causal distribution effect; confounding; covariates; uniform non-confounding; INFERENCE; COLLAPSIBILITY;

D O I：

10.1007/s11424-010-8417-x

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

Causation is a distinct concept from association and more important than association in epidemiologic studies. This paper proposes the concept of uniform non-confounding for causal distribution effects over multiple covariates, and gives the sufficient conditions for uniform non-confounding over a covariate set C including confounders or non-confounders, and also shows the conditions for conditionally non-confounding in the subpopulations. All these conditions can be tested by observed data.

引用

页码：796 / 803

页数：8

共 45 条

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