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bmd: an R package for benchmark dose estimation
The benchmark dose (BMD) methodology is used to derive a hazard characterization measure for risk assessment in toxicology or ecotoxicology. The present paper’s objective is to introduce the R extension package bmd, which facilitates the estimation of BMD and the benchmark dose lower limit for a wid...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7750002/ https://www.ncbi.nlm.nih.gov/pubmed/33362981 http://dx.doi.org/10.7717/peerj.10557 |
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author | Jensen, Signe M. Kluxen, Felix M. Streibig, Jens C. Cedergreen, Nina Ritz, Christian |
author_facet | Jensen, Signe M. Kluxen, Felix M. Streibig, Jens C. Cedergreen, Nina Ritz, Christian |
author_sort | Jensen, Signe M. |
collection | PubMed |
description | The benchmark dose (BMD) methodology is used to derive a hazard characterization measure for risk assessment in toxicology or ecotoxicology. The present paper’s objective is to introduce the R extension package bmd, which facilitates the estimation of BMD and the benchmark dose lower limit for a wide range of dose-response models via the popular package drc. It allows using the most current statistical methods for BMD estimation, including model averaging. The package bmd can be used for BMD estimation for binomial, continuous, and count data in a simple set up or from complex hierarchical designs and is introduced using four examples. While there are other stand-alone software solutions available to estimate BMDs, the package bmd facilitates easy estimation within the established and flexible statistical environment R. It allows the rapid implementation of available, novel, and future statistical methods and the integration of other statistical analyses. |
format | Online Article Text |
id | pubmed-7750002 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-77500022020-12-24 bmd: an R package for benchmark dose estimation Jensen, Signe M. Kluxen, Felix M. Streibig, Jens C. Cedergreen, Nina Ritz, Christian PeerJ Computational Biology The benchmark dose (BMD) methodology is used to derive a hazard characterization measure for risk assessment in toxicology or ecotoxicology. The present paper’s objective is to introduce the R extension package bmd, which facilitates the estimation of BMD and the benchmark dose lower limit for a wide range of dose-response models via the popular package drc. It allows using the most current statistical methods for BMD estimation, including model averaging. The package bmd can be used for BMD estimation for binomial, continuous, and count data in a simple set up or from complex hierarchical designs and is introduced using four examples. While there are other stand-alone software solutions available to estimate BMDs, the package bmd facilitates easy estimation within the established and flexible statistical environment R. It allows the rapid implementation of available, novel, and future statistical methods and the integration of other statistical analyses. PeerJ Inc. 2020-12-17 /pmc/articles/PMC7750002/ /pubmed/33362981 http://dx.doi.org/10.7717/peerj.10557 Text en ©2020 Jensen et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Computational Biology Jensen, Signe M. Kluxen, Felix M. Streibig, Jens C. Cedergreen, Nina Ritz, Christian bmd: an R package for benchmark dose estimation |
title | bmd: an R package for benchmark dose estimation |
title_full | bmd: an R package for benchmark dose estimation |
title_fullStr | bmd: an R package for benchmark dose estimation |
title_full_unstemmed | bmd: an R package for benchmark dose estimation |
title_short | bmd: an R package for benchmark dose estimation |
title_sort | bmd: an r package for benchmark dose estimation |
topic | Computational Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7750002/ https://www.ncbi.nlm.nih.gov/pubmed/33362981 http://dx.doi.org/10.7717/peerj.10557 |
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