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	Comparison between estimates of the potential proportion with and without standardization for a non-confounder
	Wang, Xueli ; Geng, Zhi ; Zhao, Qiang ; Qiao, Qi
	2007
关键词	adjustment causal inference confounder confounding potential-outcome model precision standardization CAUSAL INFERENCE COLLAPSIBILITY
英文摘要	A covariate is not a confounder if it is not a risk factor to disease, or if it has the same distribution in the exposed and unexposed populations. Standardization for a confounder can reduce confounding bias, but that for a non-confounder cannot. A question argued by many authors asks whether or not standardization of a non-confounder can improve the precision of estimation. This paper discusses the hypothetical or potential proportion of individuals in the exposed population who would have developed the disease had they not been exposed. It is shown that the precision of estimation of the hypothetical proportion cannot usually be improved by using standardization for a non-confounder, no matter how one re-categorizes the non-confounder.; Statistics & Probability; SCI(E); 0; ARTICLE; 4; 1643-1656; 17
语种	英语
出处	SCI
出版者	statistica sinica
内容类型	其他
源URL	[http://hdl.handle.net/20.500.11897/397608]
专题	数学科学学院
推荐引用方式 GB/T 7714	Wang, Xueli,Geng, Zhi,Zhao, Qiang,et al. Comparison between estimates of the potential proportion with and without standardization for a non-confounder. 2007-01-01.

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