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Varying‐coefficient regression analysis for pooled biomonitoring

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  • Dewei Wang
  • Xichen Mou
  • Yan Liu

Abstract

Human biomonitoring involves measuring the accumulation of contaminants in biological specimens (such as blood or urine) to assess individuals' exposure to environmental contamination. Due to the expensive cost of a single assay, the method of pooling has become increasingly common in environmental studies. The implementation of pooling starts by physically mixing specimens into pools, and then measures pooled specimens for the concentration of contaminants. An important task is to reconstruct individual‐level statistical characteristics based on pooled measurements. In this article, we propose to use the varying‐coefficient regression model for individual‐level biomonitoring and provide methods to estimate the varying coefficients based on different types of pooled data. Asymptotic properties of the estimators are presented. We illustrate our methodology via simulation and with application to pooled biomonitoring of a brominated flame retardant provided by the National Health and Nutrition Examination Survey (NHANES).

Suggested Citation

  • Dewei Wang & Xichen Mou & Yan Liu, 2022. "Varying‐coefficient regression analysis for pooled biomonitoring," Biometrics, The International Biometric Society, vol. 78(4), pages 1328-1341, December.
    • Handle: RePEc:bla:biomet:v:78:y:2022:i:4:p:1328-1341
    DOI: 10.1111/biom.13516
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    References listed on IDEAS

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    1. S. Vansteelandt & E. Goetghebeur & T. Verstraeten, 2000. "Regression Models for Disease Prevalence with Diagnostic Tests on Pools of Serum Samples," Biometrics, The International Biometric Society, vol. 56(4), pages 1126-1133, December.
    2. Wang, Hansheng & Xia, Yingcun, 2009. "Shrinkage Estimation of the Varying Coefficient Model," Journal of the American Statistical Association, American Statistical Association, vol. 104(486), pages 747-757.
    3. Emily M. Mitchell & Robert H. Lyles & Amita K. Manatunga & Michelle Danaher & Neil J. Perkins & Enrique F. Schisterman, 2014. "Regression for skewed biomarker outcomes subject to pooling," Biometrics, The International Biometric Society, vol. 70(1), pages 202-211, March.
    4. Juexin Lin & Dewei Wang, 2018. "Single-index regression for pooled biomarker data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 30(4), pages 813-833, October.
    5. Jingru Mu & Guannan Wang & Li Wang, 2018. "Estimation and inference in spatially varying coefficient models," Environmetrics, John Wiley & Sons, Ltd., vol. 29(1), February.
    6. Yaakov Malinovsky & Paul S. Albert & Enrique F. Schisterman, 2012. "Pooling Designs for Outcomes under a Gaussian Random Effects Model," Biometrics, The International Biometric Society, vol. 68(1), pages 45-52, March.
    7. Dewei Wang & Xichen Mou & Xiang Li & Xianzheng Huang, 2020. "Local polynomial regression for pooled response data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 32(4), pages 814-837, October.
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    1. Luis A. Barboza & Shu Wei Chou Chen & Marcela Alfaro Córdoba & Eric J. Alfaro & Hugo G. Hidalgo, 2023. "Spatio‐temporal downscaling emulator for regional climate models," Environmetrics, John Wiley & Sons, Ltd., vol. 34(7), November.

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