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	Confounding, homogeneity and collapsibility for causal effects in epidemiologic studies
	Geng, Z ; Guo, JH ; Lau, TS ; Fung, WK
	2001
关键词	causal effect collapsibility confounding effect modification homogeneity CONTINGENCY-TABLES INTERVAL ESTIMATION RELATIVE RISK DIFFERENCE INFERENCE TESTS
英文摘要	Detection of confounding and confounders is important for observational studies, and especially so for epidemiologic studies. Miettinen and Cook (1981) derived two criteria for detecting confounders. Using a model, Wickramaratne and Holford (1987) proved that the two criteria are necessary but not sufficient conditions for confounders. We take uniform nonconfounding to mean there is no confounding at a coarse-subpopulation-level obtained by pooling any number of subpopulations. We discuss the necessity and sufficiency of the two criteria for uniform nonconfounding. The concepts of homogeneity and collapsibility for causal effects are also defined, and the relation among confounding, homogeneity and collapsibility is discussed. We show that the common causal effect over all fine subpopulations is just the causal effect of the whole population.; Statistics & Probability; SCI(E); 9; ARTICLE; 1; 63-75; 11
语种	英语
出处	SCI
出版者	statistica sinica
内容类型	其他
源URL	[http://hdl.handle.net/20.500.11897/389191]
专题	数学科学学院
推荐引用方式 GB/T 7714	Geng, Z,Guo, JH,Lau, TS,et al. Confounding, homogeneity and collapsibility for causal effects in epidemiologic studies. 2001-01-01.

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