Calculating Versus Estimating Causal Effects
نویسندگان
چکیده
منابع مشابه
Estimating causal effects.
Although one goal of aetiologic epidemiology is to estimate 'the true effect' of an exposure on disease occurrence, epidemio-logists usually do not precisely specify what 'true effect' they want to estimate. We describe how the counterfactual theory of causation, originally developed in philosophy and statistics, can be adapted to epidemiological studies to provide precise answers to the questi...
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In this paper we introduce the paradigm of multi-agent causal models (MACM), which are an extension of causal graphical models to a setting where there is no longer one single computational entity (agent) observing or not observing all the domain variables V. Instead there are several agents each having access to non-disjoint subsets of V. The incentive for introducing cooperative multiagent mo...
متن کاملmarginal versus conditional causal effects
conditional methods of adjustment are often used to quantify the effect of the exposure on the outcome. as a result, the stratums-specific risk ratio estimates are reported in the presence of interaction between exposure and confounder(s) in the literature, even if the target of the intervention on the exposure is the total population and the interaction itsel...
متن کاملMarginal versus conditional causal effects
Available online at: http://jbe.tums.ac.ir Conditional methods of adjustment are often used to quantify the effect of the exposure on the outcome. As a result, the stratums-specific risk ratio estimates are reported in the presence of interaction between exposure and confounder(s) in the literature, even if the target of the intervention on the exposure is the total population and the interacti...
متن کاملEstimating Causal Effects by Bounding Confounding
I Assessing the causal effect of a treatment variable X on an outcome variable Y from observational data is usually difficult due to the possible existence of unobserved common causes. I In our paper we examine how, given an observed dependence between X and Y , various kinds of additional assumptions which related to the “strength” of confounding of X and Y can help to estimate the causal effe...
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ژورنال
عنوان ژورنال: American Journal of Public Health
سال: 2018
ISSN: 0090-0036,1541-0048
DOI: 10.2105/ajph.2018.304546