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Estimating equations for biomarker based exposure estimation under non-steady-state conditions

Unrealistic steady-state assumptions are often used to estimate toxicant exposure rates from biomarkers. A biomarker may instead be modeled as a weighted sum of historical time-varying exposures. Estimating equations are derived for a zero-inflated gamma distribution for daily exposures with a known...

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Detalles Bibliográficos
Autores principales: Bartell, Scott M, Johnson, Wesley O
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3129579/
https://www.ncbi.nlm.nih.gov/pubmed/21668990
http://dx.doi.org/10.1186/1476-069X-10-57
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author Bartell, Scott M
Johnson, Wesley O
author_facet Bartell, Scott M
Johnson, Wesley O
author_sort Bartell, Scott M
collection PubMed
description Unrealistic steady-state assumptions are often used to estimate toxicant exposure rates from biomarkers. A biomarker may instead be modeled as a weighted sum of historical time-varying exposures. Estimating equations are derived for a zero-inflated gamma distribution for daily exposures with a known exposure frequency. Simulation studies suggest that the estimating equations can provide accurate estimates of exposure magnitude at any reasonable sample size, and reasonable estimates of the exposure variance at larger sample sizes.
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spelling pubmed-31295792011-07-06 Estimating equations for biomarker based exposure estimation under non-steady-state conditions Bartell, Scott M Johnson, Wesley O Environ Health Methodology Unrealistic steady-state assumptions are often used to estimate toxicant exposure rates from biomarkers. A biomarker may instead be modeled as a weighted sum of historical time-varying exposures. Estimating equations are derived for a zero-inflated gamma distribution for daily exposures with a known exposure frequency. Simulation studies suggest that the estimating equations can provide accurate estimates of exposure magnitude at any reasonable sample size, and reasonable estimates of the exposure variance at larger sample sizes. BioMed Central 2011-06-13 /pmc/articles/PMC3129579/ /pubmed/21668990 http://dx.doi.org/10.1186/1476-069X-10-57 Text en Copyright ©2011 Bartell and Johnson; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methodology
Bartell, Scott M
Johnson, Wesley O
Estimating equations for biomarker based exposure estimation under non-steady-state conditions
title Estimating equations for biomarker based exposure estimation under non-steady-state conditions
title_full Estimating equations for biomarker based exposure estimation under non-steady-state conditions
title_fullStr Estimating equations for biomarker based exposure estimation under non-steady-state conditions
title_full_unstemmed Estimating equations for biomarker based exposure estimation under non-steady-state conditions
title_short Estimating equations for biomarker based exposure estimation under non-steady-state conditions
title_sort estimating equations for biomarker based exposure estimation under non-steady-state conditions
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3129579/
https://www.ncbi.nlm.nih.gov/pubmed/21668990
http://dx.doi.org/10.1186/1476-069X-10-57
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