Comment on "A Quantile-Based g-Computation Approach to Addressing the Effects of Exposure Mixtures"
- PMID: 33688746
- PMCID: PMC7945178
- DOI: 10.1289/EHP8739
Comment on "A Quantile-Based g-Computation Approach to Addressing the Effects of Exposure Mixtures"
Comment in
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Response to "Comment on 'A Quantile-Based g-Computation Approach to Addressing the Effects of Exposure Mixtures'".Environ Health Perspect. 2021 Mar;129(3):38002. doi: 10.1289/EHP8820. Epub 2021 Mar 10. Environ Health Perspect. 2021. PMID: 33688745 Free PMC article. No abstract available.
Comment on
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A Quantile-Based g-Computation Approach to Addressing the Effects of Exposure Mixtures.Environ Health Perspect. 2020 Apr;128(4):47004. doi: 10.1289/EHP5838. Epub 2020 Apr 7. Environ Health Perspect. 2020. PMID: 32255670 Free PMC article.
References
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- Bello G. 2014. Application and Extension of Weighted Quantile Sum Regression for the Development of a Clinical Risk Prediction Tool [dissertation]. Richmond, VA: Virginia Commonwealth University.
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- Curtin P, Kellogg JJ, Cech N, Gennings C. 2019. A random subset implementation of weighted quantile sum (WQSRS) regression for analysis of high-dimensional mixtures. Commun Stat Simul Comput, 10.1080/03610918.2019.1577971. - DOI
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