Update: Greenland and Robins (1986). Identifiability, exchangeability and epidemiological confounding
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چکیده
منابع مشابه
Update: Greenland and Robins (1986). Identifiability, exchangeability and epidemiological confounding
We are pleased to publish an update to "Identifiabiliity, exchangeability and epidemiological confounding" (IEEC) by Sander Greenland and James Robins, originally published in 1986 in the International Journal of Epidemiology. This is the first in a series of updates to classic epidemiologic-methods papers that EP&I has commissioned.
متن کاملIdentifiability, exchangeability, and epidemiological confounding.
Non-identifiability of parameters is a well-recognized problem in classical statistics, and Bayesian statisticians have long recognized the importance of exchangeability assumptions in making statistical inferences. A seemingly unrelated problem in epidemiology is that of confounding: bias in estimation of the effects of an exposure on disease risk, due to inherent differences in risk between e...
متن کاملIdentifiability, exchangeability and confounding revisited
In 1986 the International Journal of Epidemiology published "Identifiability, Exchangeability and Epidemiological Confounding". We review the article from the perspective of a quarter century after it was first drafted and relate it to subsequent developments on confounding, ignorability, and collapsibility.
متن کاملRe: "The failure of academic epidemiology: witness for the prosecution".
1. Kulkarni PM, Wang S. Re: "Assessing the direction of causality in cross-sectional studies." (Letter). Am J Epidemiol 1997;146:786-7. 2. Flanders WD, Lin L, Pirkle JL, et al. Assessing the direction of causality in cross-sectional studies. Am J Epidemiol 1992; 135:926-35. 3. Greenland S, Robins JM. Identifiability, exchangeability, and epidemiological confounding. Int J Epidemiol 1986;15: 413...
متن کاملIdentifiability and exchangeability for direct and indirect effects.
We consider the problem of separating the direct effects of an exposure from effects relayed through an intermediate variable (indirect effects). We show that adjustment for the intermediate variable, which is the most common method of estimating direct effects, can be biased. We also show that even in a randomized crossover trial of exposure, direct and indirect effects cannot be separated wit...
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ژورنال
عنوان ژورنال: Epidemiologic Perspectives & Innovations
سال: 2009
ISSN: 1742-5573
DOI: 10.1186/1742-5573-6-3