Confounding and Collapsibility in Causal Inference
نویسندگان
چکیده
منابع مشابه
Confounding, Homogeneity and Collapsibility for Causal Effects in Epidemiologic Studies
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 confound...
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Association between two variables may be reversed by marginalizing over another possibly unobserved background. This reversal is called the Yule-Simpson paradox (Yule, 1903; Simpson, 1951). To avoid the reversal, many authors discussed collapsibility of association measures over a background (Wermuth, 1987; Geng, 1992; Cox and Wermuth, 2003). Causal effects and relationships among variables may...
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One of the identifiability assumptions of causal effects defined by marginal structural model (MSM) parameters is the experimental treatment assignment (ETA) assumption. Practical violations of this assumption frequently occur in data analysis when certain exposures are rarely observed within some strata of the population. The inverse probability of treatment weighted (IPTW) estimator is partic...
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ژورنال
عنوان ژورنال: Statistical Science
سال: 1999
ISSN: 0883-4237
DOI: 10.1214/ss/1009211805