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• W3136994940 abstract "Challenges arise in researching health effects associated with chemical mixtures. Several methods have recently been proposed for estimating the association between health outcomes and exposure to chemical mixtures, but a formal simulation study comparing broad-ranging methods is lacking. We select five recently developed methods and evaluate their performance in estimating the exposure-response function, identifying active mixture components, and identifying interactions in a simulation study. Bayesian kernel machine regression (BKMR) and nonparametric Bayes shrinkage (NPB) were top-performing methods in our simulation study. BKMR and NPB outperformed other contemporary methods and traditional linear models in estimating the exposure-response function and identifying active mixture components. BKMR and NPB produced similar results in a data analysis of the effects of multipollutant exposure on lung function in children with asthma." @default.
• W3136994940 created "2021-03-29" @default.
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• W3136994940 date "2021-03-25" @default.
• W3136994940 modified "2023-09-27" @default.
• W3136994940 title "Model choice for estimating the association between exposure to chemical mixtures and health outcomes: A simulation study" @default.
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• W3136994940 doi "https://doi.org/10.1371/journal.pone.0249236" @default.
• W3136994940 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7993848" @default.
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• W3136994940 hasPublicationYear "2021" @default.
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