AC-PCoA: Adjustment for confounding factors using principal coordinate analysis [PDF]
PLoS Computational Biology, 2022 Confounding factors exist widely in various biological data owing to technical variations, population structures and experimental conditions. Such factors may mask the true signals and lead to spurious associations in the respective biological data ...
Yu Wang +3 more
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Confounding factors in algal phosphorus limitation experiments. [PDF]
PLoS ONE, 2018 Assessing algal nutrient limitation is critical for understanding the interaction of primary production and nutrient cycling in streams, and nutrient diffusing substrate (NDS) experiments are often used to determine limiting nutrients such as nitrogen (N)
Whitney S Beck, Ed K Hall
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phMRI: methodological considerations for mitigating potential confounding factors [PDF]
Frontiers in Neuroscience, 2015 Pharmacological Magnetic Resonance Imaging (phMRI) is a variant of conventional MRI that adds pharmacological manipulations in order to study the effects of drugs, or uses pharmacological probes to investigate basic or applied (e.g.
Julius H Bourke +2 more
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Factors confounding the assessment of reflection: a critical review [PDF]
BMC Medical Education, 2011 Background Reflection on experience is an increasingly critical part of professional development and lifelong learning. There is, however, continuing uncertainty about how best to put principle into practice, particularly as regards assessment.
Koole Sebastiaan +6 more
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Companies’ Responses to a Tax on Sugar-Sweetened Beverages: Implications for Research; Comment on “Understanding Marketing Responses to a Tax on Sugary Drinks: A Qualitative Interview Study in the United Kingdom, 2019” [PDF]
International Journal of Health Policy and Management, 2023 The paper by Forde et al, newly published in this journal, sheds light on how sugar-sweetened beverages (SSBs) companies may react to the introduction of a SSB tax.
Judite Gonçalves
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Enhancing result reliability by addressing potential confounding factors [PDF]
Microbiology SpectrumSatoru Mitsuboshi
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Restricted maximum-likelihood method for learning latent variance components in gene expression data with known and unknown confounders [PDF]
, 2021 Random effect models are popular statistical models for detecting and correcting spurious sample correlations due to hidden confounders in genome-wide gene expression data.
Malik, Muhammad Ammar, Michoel, Tom
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Application of Standardization for Causal Inference in Observational Studies: A Step-by-step Tutorial for Analysis Using R Software [PDF]
Journal of Preventive Medicine and Public Health, 2022 Epidemiological studies typically examine the causal effect of exposure on a health outcome. Standardization is one of the most straightforward methods for estimating causal estimands.
Sangwon Lee, Woojoo Lee
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Understanding confounding effects in linguistic coordination: an information-theoretic approach [PDF]
, 2015 We suggest an information-theoretic approach for measuring stylistic coordination in dialogues. The proposed measure has a simple predictive interpretation and can account for various confounding factors through proper conditioning.
Galstyan, Aram +2 more
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Confounders in Identification and Analysis of Inflammatory Biomarkers in Cardiovascular Diseases
Biomolecules, 2021 Proinflammatory biomarkers have been increasingly used in epidemiologic and intervention studies over the past decades to evaluate and identify an association of systemic inflammation with cardiovascular diseases.
Qurrat Ul Ain +4 more
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