Results 31 to 40 of about 606,411 (289)
Clustering of causal graphs to explore drivers of river discharge
Environmental Data Science, 2023 This work aims to classify catchments through the lens of causal inference and cluster analysis. In particular, it uses causal effects (CEs) of meteorological variables on river discharge while only relying on easily obtainable observational data.
Wiebke Günther +3 more
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G3: Genes, Genomes, Genetics, 2018 Influenza A virus (IAV) is a respiratory pathogen that causes substantial morbidity and mortality during both seasonal and pandemic outbreaks. Infection outcomes in unexposed populations are affected by host genetics, but the host genetic architecture is
Paul L. Maurizio +15 more
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Information Bottleneck for Estimating Treatment Effects with Systematically Missing Covariates
Entropy, 2020 Estimating the effects of an intervention from high-dimensional observational data is a challenging problem due to the existence of confounding. The task is often further complicated in healthcare applications where a set of observations may be entirely ...
Sonali Parbhoo +3 more
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Causal inference for process understanding in Earth sciences [PDF]
arXiv, 2021 There is growing interest in the study of causal methods in the Earth sciences. However, most applications have focused on causal discovery, i.e. inferring the causal relationships and causal structure from data. This paper instead examines causality through the lens of causal inference and how expert-defined causal graphs, a fundamental from causal ...
arxiv
Journal of Causal Inference, 2015 Failure (or success) in finding a statistically significant effect of a large-scale intervention may be due to choices made in the evaluation. To highlight the potential limitations and pitfalls of some common identification strategies used for ...
Weber Ann M. +2 more
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Causal Bias Quantification for Continuous Treatments [PDF]
arXiv, 2021 We extend the definition of the marginal causal effect to the continuous treatment setting and develop a novel characterization of causal bias in the framework of structural causal models. We prove that our derived bias expression is zero if, and only if, the causal effect is identifiable via covariate adjustment.
arxiv
Frontiers in Genetics, 2023 Background: Observational studies have shown a bidirectional association between chronic obstructive pulmonary disease (COPD) and gastroesophageal reflux disease (GERD), but it is not clear whether this association is causal.
Menglong Zou +4 more
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Coffee and caffeine consumption and risk of renal cell carcinoma: A Mendelian randomization study
Frontiers in Nutrition, 2022 BackgroundThe association between coffee and caffeine consumption and the risk of renal cell carcinoma was inconsistent among observational studies, and whether these observed associations were causal remained unclear.
Bing-Hui Li +10 more
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The Impact of Wind Farms on the Prices of Nearby Houses in Poland: A Review and Synthesis
Real Estate Management and Valuation, 2016 Since 2009/10 Poland has experienced a dynamic growth of wind energy production. Currently, wind energy is the most popular resource of renewable energy in Poland.
Torzewski Marcin
doaj +1 more source
Multisite chronic pain and the risk of autoimmune diseases: A Mendelian randomization study
Frontiers in Immunology, 2023 BackgroundAccumulating evidence has demonstrated that an association between chronic pain and autoimmune diseases (AIDs). Nevertheless, it is unclear whether these associations refer to a causal relationship. We used a two-sample Mendelian randomization (
Yidan Tang +8 more
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