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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2011
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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. |
format | Online Article Text |
id | pubmed-3129579 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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