Results 11 to 20 of about 1,784,130 (283)
BackgroundEpidemiological observational studies have investigated the relationship between rheumatoid arthritis(RA) and pre-eclampsia, but no consistent conclusions were obtained due to various limitations.
Dingyi Zhang +13 more
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Integrated multiple mediation analysis: A robustness–specificity trade-off in causal structure [PDF]
Recent methodological developments in causal mediation analysis have addressed several issues regarding multiple mediators. However, these developed methods differ in their definitions of causal parameters, assumptions for identification, and ...
Albert JM +42 more
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IntroductionPhysical fitness is an essential part of a healthy lifestyle that concerns the overall health of the nation. Research on the relationship between the Internet and physical fitness has long been caught in the dilemma of “media mobilization ...
Long Zhang +6 more
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Background: The association between serum bilirubin level and heart failure (HF) was controversial in previous observational studies and the causal effects of bilirubin on HF have not been investigated.
Bo Guan +7 more
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Causality fields in nonlinear causal effect analysis
与线性因果相比, 非线性因果具有更复杂的特点和内涵. 本文主要讨论非线性因果中的若干个问题, 并着重强调因果域的概念. 本文基于广泛应用的计算模型和方法, 围绕非线性因果分析与计算以及因果域的识别问题提出相应观点和建议, 并通过几个具体案例揭示非线性因果在处理复杂因果推断问题中的重要性和现实意义.
Aiguo Wang +3 more
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MERLiN: Mixture Effect Recovery in Linear Networks [PDF]
Causal inference concerns the identification of cause-effect relationships between variables, e.g. establishing whether a stimulus affects activity in a certain brain region.
Gretton, Arthur +2 more
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COVID-19 and the risk of neuromyelitis optica spectrum disorder: a Mendelian randomization study
BackgroundAn increasing number of studies have elucidated a close nexus between COVID-19 phenotypes and neuromyelitis optica spectrum disorder (NMOSD), yet the causality between them remains enigmatic.MethodsIn this study, we conducted a Mendelian ...
Dongren Sun +5 more
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Identifiability and transportability in dynamic causal networks [PDF]
In this paper we propose a causal analog to the purely observational Dynamic Bayesian Networks, which we call Dynamic Causal Networks. We provide a sound and complete algorithm for identification of Dynamic Causal Networks, namely, for computing the ...
Arias Vicente, Marta +2 more
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Causal Induction from Continuous Event Streams: Evidence for Delay-Induced Attribution Shifts [PDF]
Contemporary theories of Human Causal Induction assume that causal knowledge is inferred from observable contingencies. While this assumption is well supported by empirical results, it fails to consider an important problem-solving aspect of causal ...
Buehner, M, May, J
core +4 more sources
The incorporation of causal inference in mediation analysis has led to theoretical and methodological advancements -- effect definitions with causal interpretation, clarification of assumptions required for effect identification, and an expanding array ...
Nguyen, Trang Quynh +2 more
core +1 more source

